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Volume 9 - Issue 1


U CLINICAL STUDIES Your Resource for Multisite Studies & Emerging Markets


Clinical Trials in Russia & EAEU A Regulatory Update Bridging the Clinical Data Structure Gap To Empower Holistic Risk Management EU Paediatric Investigation Plans (PIPs) And Clinical Studies in Children Demand-Led Supply Increasing Efficiency in Clinical Studies Logistics

I Journal for Clinical Studies

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EDITOR Orsolya Balogh EDITORIAL ASSISTANT Emoke Karasz emi@pharmapubs.com DESIGNER Fiona Cleland RESEARCH & CIRCULATION MANAGER Evelyn Rogers info@pharmapubs.com ADMINISTRATOR Barbara Lasco FRONT COVER © istockphoto PUBLISHED BY Pharma Publications Unit J413, The Biscuit Factory Tower Bridge Business Complex 100 Clements Road, London SE16 4DG Tel: +44 0207 237 2036 Fax: +0014802475316 Email: info@pharmapubs.com www.jforcs.com Journal for Clinical Studies – ISSN 1758-5678 is published bi-monthly by PHARMAPUBS.

The opinions and views expressed by the authors in this magazine are not necessarily those of the Editor or the Publisher. Please note that although care is taken in preparation of this publication, the Editor and the Publisher are not responsible for opinions, views and inaccuracies in the articles. Great care is taken with regards to artwork supplied, the Publisher cannot be held responsible for any loss or damage incurred. This publication is protected by copyright. Volume 9 Issue 1 January 2017 PHARMA PUBLICATIONS


08 Latest FDA Guidance on Non-Inferiority Designs To obtain drug approval from the US Food and Drug Administration (FDA), manufacturers must establish efficacy by providing “substantial evidence” of effectiveness from “adequate and well‐controlled studies.” In November 2016, the FDA issued a final guidance for industry, Non-Inferiority Clinical Trials to Establish Effectiveness, to provide advice on the appropriate use of NI study designs for investigational drugs or biologics. In her article, Deborah A. Komlos, MS, Senior Medical & Regulatory Writer for the Cortellis Regulatory Intelligence US Module at Clarivate Analytics, explains the changes which have been made in this current guidance. 10 How Integration of Consumer and Medical Devices is Reshaping Clinical Trials The advent of continuous data monitoring using wearable technology and other connectable medical devices has opened the door to new insights into the lives of patients and their treatment interactions. However, as with all technological advances, it has also created a number of challenges for sponsors, which technology vendors must understand and overcome before incorporating such devices into patient data capture solutions. In this piece, Dr Chris Watson, Director of Product Strategy, Exco InTouch, talks about the usage of consumer- and medical-grade products. 12 Integrative Approach to the Conduct of Rare Disease Clinical Trials The planning and execution of rare disease clinical trials involves unique considerations. Examples include the role of patient advocacy groups, the value of outcomes registries and complete natural histories, the challenge in recruiting and retaining study participants, the special qualifications of investigators and clinical sites, unsettled clinical endpoints, and the variable availability of outcome assessment tools. In this Watch page, Judith Ng-Cashin, MD, Chief Scientific Officer, INC Research, underlines the importance of the patient-centred approach in the conduct of clinical trials. 14 Why would Cardiovascular Outcomes Trials and Rare Disease Studies have Anything in Common? Cardiovascular outcomes trials (CVOTs) are some of the largest interventional trials being conducted, enrolling several thousand subjects, sometimes with follow-up of several years to accrue the required number of major adverse cardiovascular events. By contrast, and for obvious reasons, rare disease studies are very limited in size. However, the general design of these two trials is similar. Philip Galtry, Vice President, Clinical Development and Cinzia Dorigo, Executive Director, Clinical Development for Rare Disease and General Medicine, INC Research, try to figure out why.

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Contents 16 Human Challenge Studies: An Effective Tool for Drug Development Human challenge studies (HCS) were introduced as an alternative to community clinical trials for anti-infective agents and vaccines, previously performed in regional clinics and hospitals. In an HCS, subjects may either be inoculated with a candidate vaccine before being exposed to a live challenge virus, or dosed with an investigative therapeutic agent following experimental infection. In this article, Adrian Wildfire, SGS Infectious Diseases project director, outlines the advantages of human challenge studies. REGULATORY 18 Policy 0070 Under the Microscope: The Trade-off Between Clinical Trial Transparency and the Risk of Revealing Patient Identities The last few months have seen a battle build between the pharma industry and the EMA, following the issue of new guidance promoting greater transparency in clinical trial reporting. Specifically, ‘anonymised’ clinical study reports should now be made centrally available at the time of marketing authorisation submissions, but risk-averse manufacturers are digging in their heels. Cathal Gallagher, Life Sciences consultant for d-Wise, reviews recent developments and considers how the situation will play out. 22 Five Reasons to Embrace the ICH E6 (R2) Addendum Now: Improve Study Efficiencies by Centralising Risk-based Quality Oversight and Trial Management In November 2016, the ICH E6 (R2) Addendum to Good Clinical Practice was implemented, delivering a breath of fresh air for clinical trial sponsors and CROs who have been looking for guidance on best practices for achieving true, riskbased quality management during clinical development. Brion Regan, Product Manager, ERT, introduces this Addendum and presents the reasons why sponsors and CROs should adopt a centralised approach to risk-based trial monitoring, oversight and quality management now — to not only stay ahead of guidelines and regulations, but also to reap significant benefits across many aspects of clinical development. 26 Bridging the Clinical Data Structure Gap to Empower Holistic Risk Management Per the suggestion of regulatory agencies, there is an increased focus on the merits of adapting a risk-based monitoring (RBM) approach. Effective RBM reduces costs, improves data quality and enhances oversight, but most of the existing RBM solutions in the marketplace have significant shortcomings, in part because they make it difficult to get a holistic view of data. In this article, Sudeep Pattnaik, President & CEO of ThoughtSphere, examines the benefits of RBM, the shortcomings of existing RBM solutions, and how a new approach to data integration and analysis that leverages the latest in technology developments can improve RBM to drive more benefits and move RBM from monitoring to management. 30 Compliance Data in Clinical Research There is a great deal of emphasis on streamlining the 2 Journal for Clinical Studies

Volume 9 Issue 1

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Contents regulatory process to get important drugs to subjects who need them expeditiously. This is of increasing importance because of the trend to personalised drug development and the realisation that classic randomised clinical trials are becoming prohibitively expensive. Allan Wilson MD, PhD who previously served in the position of Full Professor and Head, Section of Addiction Psychiatry at the University of Ottawa, shares his thoughts on compliance data in clinical research. MARKET REPORT 34 Clinical Trials in Russia & EAEU. A Regulatory Update Declining healthcare spending combined with increased pressure on the HC system budget is creating an incentive for patients to consent to new treatments, and fostering a positive environment for the development of the CT sector. There are a multitude of factors that influence companies’ decisions to open clinical operations in Russia for all types of clinical trials. In this article, Jane Gelfand, Managing Director and Kristina Dutchak, Programme Director at Adam Smith Conferences, analyse the key factors that are shaping the Russian and CIS market for clinical trials, and discuss the regulatory initiatives that are coming into force to facilitate its further development. 38 Why and How a Research Lab Should Embrace Research Quality The development of therapeutic products balances benefits and adverse consequences, so research quality is required for the development of the new therapeutic. Astute use of research quality earlier can add to the value of intellectual property (IP), especially when the IP is subject to quality assurance due diligence (QADD). Andrew King, Quality Assurance Manager for Q-Pharm, aims to explore the reasons for a lab to apply research quality to improve their science, its reliability and productivity, and to consider how to begin to apply research quality.

Trials, explain studies regarding the diagnostic criteria of PSP. IT & LOGISTICS 50 Latest IRT Systems Accelerate Trial Progress and Support Patient Safety IRT systems are commonly credited with helping to ensure that the right drug gets to the right patient at the right time. This digital side of the supply chain supports drug distribution activities as well as site-level patient interactions. As IRTs have grown more sophisticated in recent years, their automated functions can actually accelerate the drug’s journey to market and improve patient safety. This article is about the latest IRT systems, written by Robert Weney, Director of Production IT at Almac Clinical Technologies. 54 Demand-led Supply: Increasing Efficiency in Clinical Studies Logistics Cost pressures associated with the development of new medications are at an all-time high for the pharmaceutical industry. Drug development costs in general are rising and particularly so within therapeutic categories, for certain disease states where highly targeted and costly therapies such as biologics show promise. Kunal Jaiswal, Vice President, Strategic Development Solutions, Clinical Supply Services at Catalent, aims to compare the traditional supply model with the demand-led model. 58 Counting the Cost of Corrections in Clinical Trials Labelling Peter Muller, Managing Director, Schlafender Hase, Americas, says “Bringing a new drug to market costs millions, so it’s highly risky to leave product labelling and packaging to chance. Especially if it’s expensive professionals giving hours of their time to these repetitive manual processes.” With his 20 years of working experience in software and process improvement, in this article he focuses on the cost of corrections in clinical trials labelling.

THERAPEUTICS 42 EU Paediatric Investigation Plans (PIPs) and Clinical Studies in Children Since 2007, new drugs need a paediatric investigation plan (PIP) for EU registration. Without a PIP accepted by the European Medicines Agency (EMA)'s paediatric committee (PDCO), registration in adults and children is blocked. Klaus Rose is an independent consultant, who advises on paediatric drug development. In his article he talks about the paediatric investigation plans. 46 Refining Clinical Diagnosis of Progressive Supranuclear Palsy: Implications for Disease-modification Trials The importance of ensuring an accurate diagnosis of progressive supranuclear palsy (PSP) is critical for the development of effective disease-modifying therapies that are specifically directed at the reduction of tau aggregation in the pathogenesis of this disorder. Co-authors Tomislav Babic, MD, PhD, Vice President of Medical and Scientific Affairs/Neuroscience Franchise and Henry J. Riordan, Ph.D., Executive Vice President of Medical and Scientific Affairs and Global Lead for Neuroscience at Worldwide Clinical 4 Journal for Clinical Studies

Volume 9 Issue 1

© SGS Group Management SA - 2017 - All rights reserved - SGS is a registered trademark of SGS Group Management SA


SGS is a leading life sciences CRO providing clinical research and bioanalytical testing services. Delivering solutions in Europe and in the US, SGS offers Phase I to IV clinical trial services encompassing clinical project management and monitoring, biometrics, PK/PD modeling & simulation and regulatory & medical affairs consultancy. Clients benefit from our a wealth of expertise in regulatory and exploratory trials, viral challenge testing, complex PK/PD and biosimilars studies with a high patients therapeutic focus in Infectious Diseases, Vaccines, Oncology and Respiratory. Stay ahead in your drug development plan, contact us for reliable and adaptive clinical trial solutions.

WWW.SGS.COM/CRO lss.info@sgs.com




Foreword The industry is approaching a new age of trials that are streamlined, connected and more engaged with the patient – but only if pharma can embrace the changes. As patent cliffs approach and development costs reach record highs, pharma companies need to evolve their R&D efforts to ensure the core of their business keeps pace with the changes. Many firms are already looking at clinical trials in new ways, but as ever with R&D, it's going to be a slow process. Clinical trials are getting more complex and increasing amounts of data are being collected. We need better approaches and we need to apply our current systems and technology better in order to meet the challenges posed by this – such as increasing numbers of patient subgroups, difficulties in finding those patients, and trials in rare diseases and orphan drugs becoming more common. Technology categories that could change clinical trials are: cloud, analytics and mobile. When we evaluate under 'cloud' there is more than hosting, there's using tech as a means to seamlessly integrate and collaborate with external partners, which we are finding is a significant trend in R&D. Under 'mobile', wearables are the most obvious example, as well as smart devices and social media for patient enrolment and investigator interactions. It might sound like a bold statement, but trends suggest a future in which medical innovation will be born in a garage lab or a small startup company. In the last hundred years, advances in medicine belonged mainly to the R&D departments of pharma companies. Technological developments might change that forever. What if a startup can perform clinical trials in silico? Instead of spending billions of dollars and waiting for years, they might be able to test thousands of drug targets in seconds on billions of patient models without the need for testing drugs on real people. What if they can recruit the right patients for these trials through digital methods more easily and much more cheaply? Welcome to the 1st issue of JCS in the year 2017. We again thank all our authors and sponsors for making JCS one of the most valued publications in the industry. The Watch section starts with Deborah A. Komlos, MS, Senior Medical & Regulatory Writer for the Cortellis Regulatory Intelligence US Module at Clarivate Analytics, explaining the latest FDA guidance on non-inferiority designs Dr Chris Watson, Director of Product Strategy, Exco InTouch, talks about how integration of consumer and medical devices is reshaping clinical trials. We have two new contributors to the Watch columns. Judith Ng-Cashin, MD, Chief Scientific Officer, INC Research, underlines the importance of an integrative approach to the conduct of rare disease clinical trials, and Adrian Wildfire, SGS Infectious Diseases project director, discusses human challenge studies being an effective tool for drug development. In the Regulatory Section, Cathal Gallagher, Life Sciences Consultant for d-Wise, looks at Policy 0070 under the microscope, examining the trade-off between clinical trial transparency and the risk of revealing patient identities, and Sudeep Pattnaik, President & CEO of ThoughtSphere, examines the benefits of RBM and the shortcomings of existing RBM solutions. Country Analysis features a report on clinical trials in Russia & EAEU, in the form of a regulatory update by Jane Gelfand and Kristina Dutchak of Adam Smith Conferences In the Therapeutic section, Klaus Rose, an independent consultant who advises on paediatric drug development, writes on EU Paediatric Investigation Plans (PIPs) and clinical studies in children, and Tomislav Babic and Henry J. Riordan of Worldwide Clinical Trials present an article on refining clinical diagnosis of progressive supranuclear palsy and the implications for disease-modification trials. I hope you all enjoy this issue of JCS, and we wish you all a wonderful 2017. Orsolya Balogh Managing Editor

JCS features the national flower of one of the countries we have reported on in that particular issue. In this issue we have featured a report on Russia & EAEU states. Camomile is the national flower of Russia, which features on the front cover. I hope this journal guides you through the maze of activities and changes taking place in the clinical research industry worldwide.

Editorial Advisory Board Art Gertel, VP, Clinical Services, Regulatory & Medical writing, Beardsworth Consulting Group Inc.

Franz Buchholzer, Director Regulatory Operations worldwide, PharmaNet Development Group

Maha Al-Farhan, Vice President, ClinArt International, Chair of the GCC Chapter of the ACRP

Ashok K. Ghone, PhD, VP, Global Services MakroCare, USA

Francis Crawley. Executive Director of the Good Clinical Practice Alliance – Europe (GCPA) and a World Health Organization (WHO) Expert in ethics

Nermeen Varawala, President & CEO, ECCRO – The Pan Emerging Country Contract Research Organisation

Bakhyt Sarymsakova - Head of Department of International Cooperation, National Research Center of MCH, Astana, Kazakhstan

Georg Mathis, Founder and Managing Director, Appletree AG

Catherine Lund, Vice Chairman, OnQ Consulting Cellia K. Habita, President & CEO, Arianne Corporation Chris Tierney, Business Development Manager, EMEA Business Development, DHL Exel Supply Chain, DHL Global Chris Tait, Life Science Account Manager, CHUBB Insurance Company of Europe Deborah A. Komlos, Senior Medical & Regulatory Writer, Thomson Reuters Elizabeth Moench, President and CEO of MediciGlobal Eileen Harvey, Senior VP/General Partner, PRA International

Clearstone Central Laboratories

Heinrich Klech, Professor of Medicine, CEO and Executive Vice President, Vienna School of Clinical Research

Rabinder Buttar – President & Chief Executive Officer of ClinTec International

Hermann Schulz, MD, CEO, INTERLAB central lab services – worldwide GmbH

Rick Turner, Senior Scientific Director, Quintiles Cardiac Safety Services & Affiliate Clinical Associate Professor, University of Florida College of Pharmacy

Janet Jones, Senior Director, ICON Clinical Research Jerry Boxall, Managing Director, ACM Global Central Laboratory Jeffrey Litwin, MD, F.A.C.C. Executive Vice President and Chief Medical Officer of ERT Jeffrey W. Sherman, Chief Medical Officer and Senior Vice President, IDM Pharma. Jim James DeSantihas, Chief Executive Officer, PharmaVigilant Mark Goldberg, Chief Operating Officer, PAREXEL International Corporation

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Patrice Hugo, Chief Scientific Officer,

Robert Reekie, Snr. Executive Vice President Operations, Europe, Asia-Pacific at PharmaNet Development Group Sanjiv Kanwar, Managing Director, Polaris BioPharma Consulting Stanley Tam, General Manager, Eurofins MEDINET (Singapore, Shanghai) Stefan Astrom, Founder and CEO of Astrom Research International HB Steve Heath, Head of EMEA - Medidata Solutions, Inc T S Jaishankar, Managing Director, QUEST Life Sciences

Volume 9 Issue 1

OFFERING DEEP INSIGHTS INTO KEY AREAS OF CLINICAL DEVELOPMENT Bioclinica is specifically structured to create clarity in the clinical trial process — so you can make better decisions.

eHEALTH SOLUTIONS eClinical Solutions Safety & Regulatory Solutions Financial Lifecycle Solutions

GLOBAL CLINICAL RESEARCH Research Network Patient Recruitment & Retention Post-Approval Research

MEDICAL IMAGING & BIOMARKERS Medical Imaging Cardiac Safety Molecular Marker Laboratory

Watch Pages Latest FDA Guidance on Non-inferiority Designs To obtain drug approval from the US Food and Drug Administration (FDA), manufacturers must establish efficacy by providing “substantial evidence” of effectiveness from “adequate and well-controlled studies.” As stated in 21 Code of Federal Regulations (CFR) 314.126, there are four types of concurrently controlled trials that provide evidence of effectiveness; one of these is the non-inferiority (NI) design, which is typically used when it is not ethical for a trial to include a placebo arm. In November 2016, the FDA issued a final guidance for industry, Non-Inferiority Clinical Trials to Establish Effectiveness, to provide advice on the appropriate use of NI study designs for investigational drugs or biologics. This document finalises the 2010 draft guidance, NonInferiority Clinical Trials and supersedes the 2010 guidance for industry, Antibacterial Drug Products: Use of Noninferiority Trials to Support Approval, which will be withdrawn. Extensive changes have been made to the current guidance; these include additional recommendations on how to choose an NI margin and when NI trials can provide interpretable results, and detailed discussion on

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the choice of statistical tests for the NI hypothesis. Other additional information concerns statistical inference, statistical uncertainties, and quantification of the active control effect. Another noteworthy change in the latest guidance is the inclusion of a new example under the Appendix section, “Determination of an NI margin for CommunityAcquired Bacterial Pneumonia (CABP) When No Historical Trials Are Available.” This entry replaces former example 2, “The Determination of a Non-Inferiority Margin for Complicated Urinary Tract Infection (cUTI)—Fixed Margin Approach.” As explained in the November 2016 guidance, an NI study seeks to show that the amount by which a test drug is inferior to an active control is less than some prespecified NI margin (M). M can be no larger than the presumed entire effect of the active control in the NI study, and the margin based on the entire active control effect is generally referred to as M 1. The FDA emphasises that M 1 is not measured in the NI trial (in the absence of a placebo arm), but rather is estimated based on past performance of the active control. The effect is assumed

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Watch Pages to be present in the current study based on a thorough comparison of the characteristics of the current NI study with those of prior studies and an assessment of the quality of the NI study. With the CABP example, the FDA illustrates the point of determining the NI margin using observational data when randomised, placebo-controlled trials of active control drugs are lacking. The example cites a revised draft guidance for developing CABP treatments, issued in 2014, which describes in detail the justification for NI margins with respect to two endpoints: clinical response and mortality. Historical data from three published, nonrandomised studies of bacteremic and non-bacteremic patients with pneumococcal or lobar pneumonia were evaluated to justify NI margins for use in future CABP studies. The FDA points out two limitations in the use of these data to determine an NI margin: 1) only observational data are presented and 2) no recent studies were available, with the most current dating to the 1960s. The agency explains that significant improvements in the standard of care and the availability of improved treatment options for CABP patients compared to the pre-antibiotic era bring into question the relevance of these historical studies for estimating an active control effect on mortality.

The FDA has covered the topic of clinical trial design in relation to CABP at various public meetings, including: • November 4, 2016: The Antimicrobial Drugs Advisory Committee (AMDAC) considered two new drug applications (NDAs) sponsored by Cempra Pharmaceuticals, Inc for the use of Solithera (solithromycin capsules and solithromycin for injection) to treat CABP. The clinical development programme involved an NI design. • November 3, 2011: The Anti-Infective Drugs Advisory Committee (AIDAC) discussed design issues for clinical trials of antibacterials to treat CABP, and particularly the issues addressed in the FDA’s 2009 draft guidance, Community-Acquired Bacterial Pneumonia: Developing Drugs for Treatment (now outdated). • December 9, 2009: The AIDAC discussed endpoints and other clinical trial design issues for CABP product development. • April 1-2, 2008: The AIDAC discussed clinical trial design—specifically NI design—for products intended to treat community-acquired pneumonia (CAP). • January 17-18, 2008: A workshop was co-sponsored by the FDA and the Infectious Diseases Society of America (IDSA) to consider issues in the design and conduct of clinical trials of antibacterial drugs to treat CAP.

Despite the data limitations, the mortality rates among the treated patient cohorts are reasonably consistent (from 5% to 17%) across the three decades represented, the FDA notes. Mortality rates in the untreated cohorts are more variable. The older references provide estimates of 31% and 41%, while the more recent study gives an estimated mortality rate of 82%; this estimate, however, is based on a very small sample size (N = 17). Given the absence of any placebo-controlled trials of active control drugs in CABP, it is not possible to estimate M 1 using the methods advocated in this latest guidance document, according to the FDA. Still, it is clear that the untreated mortality is substantial. For this reason, the agency continues, it is reasonable to assume that the mortality rate due to CABP, if left untreated, will be substantially higher than the rates observed among the treated cohorts, based on the historical evidence described and the caveats noted about the nature and age of the studies. The FDA concludes in the CABP example that the use of an NI margin of approximately 10% is a valid approach for evaluating new CABP treatments and would clearly represent an effect superior to no treatment as well as, based on clinical judgment, an appropriate clinical margin. Comments on the November 2016 guidance document may be submitted to the FDA at any time to Docket No. FDA-2010-D-0075. www.jforcs.com

Deborah A. Komlos, MS, is the Senior Medical & Regulatory Writer for the Cortellis Regulatory Intelligence US Module at Clarivate Analytics, formerly the IP & Science business of Thomson Reuters. Her previous roles have included writing and editing for magazines, newspapers, online venues, and scientific journals, as well as publication layout and graphic design work. Email: deborah.komlos@thomsonreuters.com Journal for Clinical Studies 9

Watch Pages How Integration of Consumer and Medical Devices is Reshaping Clinical Trials The advent of continuous data monitoring using wearable technology and other connectable medical devices has opened the door to new insights into the lives of patients and their treatment interactions. However, as with all technological advances, it has also created a number of challenges for sponsors, which technology vendors must understand and overcome before incorporating such devices into patient data capture solutions. The first consideration for sponsors must be whether the study requires consumer- or medical-grade devices. Consumer-grade is commonly used to describe commercially available wrist-worn activity trackers from companies such as Fitbit, Garmin, and Fossil. These devices are typically designed to be aesthetically pleasing and easy to use, relatively affordable, and therefore simpler for sponsors to provision within their studies. The downside for sponsors is that data from consumergrade devices is not considered to be clinically validated (as they present a numerical calculation which represents activity data). This limits the use of consumer-grade devices to the provision of supporting evidence during clinical studies. When sponsors need a wearable or other type of device to gather validated data, they are advised to use medical-grade products such as those developed by ActiGraph (where calculated activity data and raw positional data is captured). In general, medical-grade devices cost more and are more complex to provision than consumer-grade devices, but the high volume of data they collect is seen as suitably reliable to facilitate regulatory decisions. To understand whether consumer- or medical-grade products are required, sponsors need to ask themselves what they want to learn from the data. If researchers are curious about aspects of subjects’ wellbeing, such as sleep patterns, and have no plans to use the data to directly support a marketing approval, consumer-grade devices are typically the best choice. Medical-grade products really come into their own when a sponsor needs a device to deliver data they can take to regulators, particularly given the recent trend towards collecting continuous data. There is a long history of companies successfully using such data in regulatory filings. Wyeth, for example, won an expanded label in the United States for Advil PM on the strength of ActiGraph data on sleep patterns in the mid-2000s. Expanding Insights into Patient Lifestyles The amount of information generated in studies has increased in recent years, and the ability to incorporate connected devices has broadened the variety of data that can be used in clinical research. For episodic data collection, alerts are sent to subjects to remind them 10 Journal for Clinical Studies

to take a reading at specific time points, which is then automatically transferred to subjects’ smartphones or tablets before being uploaded to the central trial database. For continuous data, as the term implies, data is continually collected and transferred to the patient’s connected device and then transmitted to the central trial database. Wearable technology is facilitating the shift from episodic site-based data collection to frequent, ‘athome’ data generation. For example, AliveCor’s Kardia Mobile device consists of two sensors that users attach to the back of their smartphone. When a user presses their fingers against the pads, the device acts as an electrocardiogram which can be used to detect atrial fibrillation if the heart rhythm is abnormal. As an FDA 510(k) and EU Class II-approved medical device, this generates regulatory-compliant data, and enables sponsors to gather electrocardiogram readings remotely. Similarly, peak expiratory flow meters are also being used to remotely collect regulatory-compliant data, while the integration of consumer-grade devices is giving researchers new insights into the day-to-day activities of patients, enabling them to understand and design trials of the future. Until recently sponsors have lacked truly compelling reasons to adopt devices in many studies. However, advances in technology and the recent request by the FDA for commentary on the use of technologies and innovative methods in the conduct of clinical investigations by FDA 1 mean we are likely to see guidance in the near future and, as a result of this clarification, we expect to see uptake increase. References 1. h t t p s : / / w w w . r e g u l a t i o n s . g o v / d o c u m e n t ? D = F DA 2015-N-3579-0001

Dr Chris Watson, Director of Product Strategy, Exco InTouch. Chris has a PhD in Behavioral Neuropharmacology and is an experienced product strategist with 18 years’ experience in the delivery of business and consumer-based solutions, the last eight of which have been focused in the clinical technology industry. He has an extensive knowledge of product and software development processes and is responsible for implementing mobile product strategy at Exco InTouch Volume 9 Issue 1

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Integrative Approach to the Conduct of Rare Disease Clinical Trials The planning and execution of rare disease clinical trials involves unique considerations. Examples include the role of patient advocacy groups, the value of outcomes registries and complete natural histories, the challenge of recruiting and retaining study participants, the special qualifications of investigators and clinical sites, unsettled clinical endpoints, and the variable availability of outcome assessment tools. Add to this a wide cast of participants including patient advocacy groups, specialised academic investigators, genetic counsellors and other medical experts, home nursing support companies, recruitment specialists, and communications experts – and the challenge of integrating and coordinating all these elements becomes apparent. Patient Engagement in Rare Disease Clinical Trials The most important participant in a rare disease clinical trial is the patient. The patient experience is central to the successful conduct of the clinical trial. Patient engagement acknowledges that patients and their families want to be recognised as partners throughout the lifecycle of research and therapy development. Recognising the patient’s voice might include facilitating their access to a clinical trial site or anticipating their logistical needs or disease specific burdens and addressing them within the protocol.

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Patient advocacy groups, support groups, and disease associations can give voice to valuable information about patient needs, desires, points of view, and treatment networks. Engaging with these groups ensures that patients’ voices are heard throughout the development of the clinical protocol. Rare disease patients may have preferences with regard to burden and frequency of clinical assessments; how they communicate with study clinicians; and how they can influence the endpoints, outcomes measures, and study design so that they are most meaningful. Collaborative Relationships Drive the Patient-centred Approach Understanding the challenges of coordinating all the parties that enable a high-quality patient experience and the generation of robust data are central to an integrative approach. Focusing on the rare disease patient is underpinned by strong medical, operational, and regulatory science, and driven by productive relationships between investigative sites, treating physicians, patient advocacy groups, academic thought leaders, and corporate sponsors. A critical point of contact for many of the groups needed to successfully design and execute a rare disease

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Watch Pages collaborative relationship among industry physicians and scientists, treating physicians, and academic thought leaders is critical not only for benefiting from their direct experience but also for sharing insights from crosssponsor clinical research in their area. Collaboration with patient advocacy groups and key academic investigators is the most effective way to identify protocol-eligible patients with a specific rare disease. These patients may be geographically sparse, in the case of ultra-rare diseases, or clustered in a few geographies due to genetic inheritance patterns. Conclusion Executing clinical trials in rare diseases have more in common with each other operationally than a rare disease like cystic fibrosis might have with another disease in its therapeutic area, such as asthma. Approaching rare disease clinical research by acknowledging this commonality helps make the planning and conduct of clinical trials more efficient. Cystic fibrosis and muscular dystrophy both require enrolment of paediatric populations, the need to interact with a parent caregiver, investigators who are usually in academic centres, etc. On the other hand, the biology underlying many rare diseases is poorly understood, and this can complicate the kinds of assessments and outcomes measures to be incorporated in a protocol. Integrating and coordinating physicians and scientists with expertise in rare diseases, operational experts, regulatory affairs specialists, epidemiologists, and reimbursement specialists accelerates the speed and efficiency of rare disease clinical research. This sort of approach ensures a holistic view of clinical trial planning and execution, and harnesses the passion and science of all stakeholders toward the goal of improving the lives of patients with rare diseases.

trial is the clinical research physician specialist who typically resides in the sponsor or the clinical research organisation (CRO). A close relationship between the study physician and the site principal investigator leverages shared training and a passion for patients. The result is effective collaboration during protocol design and later, during the clinical trial, as the inevitable questions, issues, and obstacles arise. This close relationship is particularly important during any long periods between subject enrolment. It can also cut down on protocol violations or needless amendments, and it can ensure that no opportunities to enroll have been lost. If a CRO is operationalising the study, a tight relationship between the clinical research study physician and sponsor study physician ensures connectivity between the sponsor and investigational sites; moreover, it is vital for timely review of emerging study data so that protocol adjustments can be made with agility. And a strong www.jforcs.com

Judith Ng-Cashin, MD, Chief Scientific Officer has 20 years of drug discovery and development, clinical research, bench science, and clinical medicine experience. Her expertise is wide-ranging, spanning all stages of clinical research, including targeted research in melanoma, HIV and other infectious diseases. Dr Ng-Cashin holds a Doctor of Medicine degree from Rush Medical College in Chicago. She completed her residency training in internal medicine at the University of Chicago Medical Center and her subspecialty fellowship training in infectious diseases and haematology at the University of North Carolina at Chapel Hill. Email: judith.ng-cashin@incresearch.com Website: www.incresearch.com Journal for Clinical Studies 13

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Why would Cardiovascular Outcomes Trials and Rare Disease Studies have Anything in Common? Cardiovascular outcomes trials (CVOTs) are some of the largest interventional trials being conducted, enrolling several thousand subjects, sometimes with follow-up over several years to accrue the required number of major adverse cardiovascular events. By contrast, and for obvious reasons, rare disease studies are very limited in size. Indeed, the ongoing anacetrapib CVOT (the REVEAL study) has enrolled 30,624 participants 1, which is almost four times the world total of 7713 diagnosed Fabry Disease patients 2. However, the general design of these two widely different and extreme types of trials is surprisingly similar. Does this have implications for other types of trials? Studies on rare diseases are inherently limited by the availability of participants. Many rare diseases are multi-organ genetic diseases which have different manifestations, depending on the specific mutation. Patients present with significant comorbidities, but such studies cannot afford to have extensive exclusion criteria. The variability of the population can lead to challenges in demonstrating efficacy. For example, the orphan drug, ixazomib, initially received negative EMA CHMP opinion because the data from the main study were insufficient to demonstrate a benefit. The company had proposed restricting the use of ixazomib to patients with refractory multiple myeloma, which relapsed after a treatment, and those whose disease had returned after at least two treatments. However, the data in these subgroups were not compelling enough and the risk-benefit-ratio was insufficiently favourable 3 (conditional approval was subsequently granted). CVOTs, as relatively late-phase large trials (III, IIIB or IV), generally try to target a broad range of subjects in an attempt to replicate the real-world use of the drugs. The expense of performing such huge studies can only be ventured in common conditions, where the potential return on investment exists, i.e. where large and widespread sales can be achieved. But just as in rare disease studies, the enrolment of subjects is the ratelimiting issue, and the designers of such trials need to be as inclusive as possible to maximise enrolment. It may be that the very different requirements of these two types of studies both tend to push the study designers towards the pragmatic end of the explanatory -> pragmatic continuum. This axis was first explored by Schwartz and Lellouch almost 50 years ago 4, but still generates discussion today 5. One might expect these two types of studies to lie at opposite ends of the pragmatic explanatory axis. While CVOTs could certainly not be described as pragmatic studies, they are certainly further down the continuum than the ‘average’ study. The shortage of subjects for rare disease studies and the 14 Journal for Clinical Studies

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Watch Pages Zwarenstein argue this would be better for patients in the long run. As for patient retention, this is just good science!

sheer number of subjects required by CVOTs means that the same pressures on inclusivity affect both types of studies. Retention of subjects is equally vital to both. For rare disease studies, the need to retain subjects is obvious, but identifying and enrolling patients is so difficult that having non-evaluable data is a critical waste. On CVOTs, the sample sizes for analysis are actually the endpoint events, and those numbers will be much smaller than the number of participants. An extreme example is the celecoxib PRECISION study that was reported recently in the NEJM 6. This study involved 24,081 subjects in three arms and ran for nearly 10 years. However the actual number of events in the primary analysis was only 607, and the difference in the number of events between the “best” and “worst”’ arms was only 30! This number is much smaller than the number of subjects that were lost to follow-up. Had this been an efficacy study (it was not), it is certain that the data would not have been acceptable to regulatory bodies. Similarly, in 2013, the FDA Advisory Committee recommended rejection of tolvaptan for the indication of slowing kidney disease in adults with autosomal dominant polycystic kidney disease (ADPKD), partially because of the amount of missing data, especially from the higher number of patients lost to follow-up in the tolvaptan group 7. Does this observation about rare disease trials and CVOTs, at opposite ends of the trial spectrum, have any implications for other trials? It is clear that purely exploratory studies are necessary to early phase research, but does the more pragmatic approach used in such disparate trials suggest that the same could be true for many more trials in the middle ground? Treweek and www.jforcs.com

References 1. ClinicalTrilas.gov website (accessed 12 December 2016): https://clinicaltrials.gov/ct2/show/NCT01252 953?term=anacetrapib&rank=9 2. Fabry Disease Foundation website (accessed 06 December 2016): http://www.fabrydisease.org/ 3. EMA CHMP Website (accessed 07 December 2016): http://www.ema.europa.eu/docs/en_GB/ document_library/Summary_of_opinion_-_Initial_ authorisation/human/003844/WC500207384.pdf 4. Schwartz D, Lellouch J: Explanatory and pragmatic attitudes in therapeutical trials. J Chronic Dis. 1967, 20: 637-648. 5. Treweek S, Zwarenstein M: Making trials matter: pragmatic and explanatory trials and the problem of applicability. Trials 2009 10:37 6. Nissen SE, Yeomans ND, Solomon DH, et al. Cardiovascular safety of celecoxib, naproxen, or ibuprofen for arthritis. N Engl J Med 2016; DOI: 10.1056/NeJMoa1611593 7. FDA Panel Vetoes New Tolvaptan Indication: Medpage Today, 05 August 2013 (accessed 13 December 2016): http://www.medpagetoday.com/nephrology/ generalnephrology/40844

Philip Galtry is Vice President, Clinical Development at INC Research, where he leads the Cardiovascular and Endocrine group. Philip holds a biochemistry degree from the University of Bristol, UK, and has worked on the management of large cardiovascular trials for almost 25 years. Email: phil.galtry@incresearch.com Website: www.incresearch.com

Cinzia Dorigo, PharmD, is Executive Director, Clinical Development for Rare Disease and General Medicine, and leads INC Research’s Rare Disease Consortium, which focuses on an effective strategic implementation for successful delivery of rare and ultra-rare disease studies. She has 17 years of experience in rare and ultra-rare clinical development, including extensive experience in earlyphase, adaptive study design and paediatric rare disease studies. Email: cinzia.dorigo@incresearch.com Website: www.incresearch.com Journal for Clinical Studies 15

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Human Challenge Studies: An Effective Tool for Drug Development Human challenge studies (HCS) were introduced as an alternative to community clinical trials for anti-infective agents and vaccines, previously performed in regional clinics and hospitals. In an HCS, subjects may either be inoculated with a candidate vaccine before being exposed to a live challenge virus, or dosed with an investigative therapeutic agent following experimental infection.

whether a therapeutic has direct effects on a subject’s wellbeing and the level of adverse effects associated with both the disease and the intervention. Trained clinicians and scientists within the unit have the knowledge and experience to distinguish between viral-associated adverse events and those related to treatment as well as the ability to contextualise them.

Ethics preclude challenge agents being associated with chronic, incurable diseases, but the concept has been extended from initial studies using rhinoviruses to a wide range of respiratory viruses and even bacterial and parasitic agents. Regulators still demand large-scale field trials for proofs of safety, but human challenge studies have become increasingly important in verifying proofof-concept regarding efficacy for drugs against certain infections.

There still remain drawbacks to challenge studies, as with all clinical trials, and subject recruitment can be difficult where challenge agent seroprevalence is high. Poor recruitment rates may also be compounded by the negative effect of asking subjects to remain in strict isolation for up to two weeks.

Challenge Studies Advantages One distinct advantage of using a characterised challenge agent in a human challenge study is that for seasonal infections, the natural incidence rate may be very low (0.5% for influenza), and recruiting sufficient subjects to achieve significance is problematic. Other advantages of undertaking a HCS include having known times of infection and recovery, allowing accurate observations and measurements of pharmacokinetic and pharmacodynamics data throughout the study. Such controlled infections may offer greater understanding of how a drug or vaccine intervention can affect symptomologies and viral shedding rates.

A Proof of Concept Model Current regulatory opinion is that challenge studies cannot wholly replace field studies. However, challenge studies may serve to generate early proof-of-concept (PoC) data and optimise dosing schedules in subsequent community trials. It has been argued that challenge studies offer an improvement over some field trials, for example travel vaccinations, and in such special cases, regulators have proved open to accepting challenge data alone as a PoC (e.g. Vaxchora – a live, oral cholera vaccine). Such limitations do not detract from regulatory observations on the general advantages of the human challenge model, but the necessarily small numbers of subjects enrolled into a challenge trial cannot provide the large body of data required for estimations of safety.

Recent advances in human challenge studies are associated with increased sophistication, including the use of dedicated, isolation facilities or human challenge units (HCUs). Ideally, an HCU should be situated within a hospital environment to ensure a high standard of medical intervention should adverse events ever occur. Such HCUs are staffed by specialist healthcare professionals, who can undertake complex techniques often unavailable or impracticable on a general ward. The use of isolation facilities also reduces the risk of cross-contamination between cohorts and the chances of a secondary infection.

Pharma and biotech companies are now looking seriously at the human challenge model as a predictive tool for late-phase (III) studies, as outcomes in the community are frequently unpredictable (e.g. Novavax – an RSV vaccine that failed to show efficacy in a late-phase trial). In the foreseeable future, for specific indications where field studies are particularly difficult or slow to recruit, a challenge study might be viewed by regulators as an acceptable alternative and, as the science progresses, the challenge model is likely to become more widespread and expand into efficacy trials for other pathogens.

Human challenge studies provide the opportunity for intense sample collection schedules, including those for pharmacokinetics and viral dynamics. Carrying out similar, complex protocols within the community can limit the potential to collect specimens in a timely manner and restrict the number of analyses possible. Having patients in a controlled environment allows for faster sample processing and the use of automated monitoring of requisite physiological markers. Physiological and serological measurements may provide insights into

Adrian Wildfire has 30 years’ experience in communicable diseases. He obtained his Fellowship in Medical Microbiology in 1990 and a Masters in Parasitology in 1998. He is the author / co-author of numerous papers with many of the UK’s leading infectious disease experts and KoLs in tuberculosis, HIV, and influenza. He trained at the Wolfson Institute and LSHTM before moving on to lead teams within various institutions. Email: adrian.wildfire@sgs.com

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Regulatory Policy 0070 Under the Microscope: The Trade-off Between Clinical Trial Transparency and the Risk of Revealing Patient Identities The last few months have seen a battle build between the pharma industry and the EMA, following the issue of new guidance promoting greater transparency in clinical trial reporting. Specifically, ‘anonymised’ clinical study reports should now be made centrally available at the time of marketing authorisation submissions, but riskaverse manufacturers are digging in their heels. d-Wise’s Cathal Gallagher reviews recent developments and considers how the situation will play out. It’s well accepted that transparency has ascended the life sciences agenda. Patient safety is sacrosanct and health authorities must be seen to do everything they can to drive up standards, improve quality and make manufacturers accountable. The European Medicine Agency’s Policy 0070 1, recently formalised in published guidance, addresses this need by ‘encouraging’ life sciences brands to open up their clinical study reports (CSRs) for easier interrogation. Yet this must happen in a way that continues to respect and protect the anonymity of subjects taking part in clinical trials. This is a fine line to tread, and although the industry understands the intention, organisations are deeply concerned about the new level of risk they will now be open to. Recently these concerns have reached a crescendo, voiced loudly at industry seminars and conferences and in test cases at the law courts. So how will this pan out, and what is companies’ best strategy for navigating the new requirements while keeping patient data safe? Under the new EMA guidelines, now published, anonymised versions of complete CSRs should be made generally available within 60 days of an authorisation decision (positive or otherwise), hosted centrally by or for the EMA. The idea is that other researchers as well as the wider public will be able to access and interrogate the documents, without having to make a special application or wait months for a select set of information to be issued. For life sciences manufacturers and brands this is a huge deal, and largely unwelcome – for they will gain little benefit in return for a lot of additional administrative work, and a considerable amount of risk (if something goes wrong and they inadvertently expose a patient’s identity, or for that matter commercially sensitive information about the company, its products or processes). Although the policy is not an enforceable law (for now, at least), there is considerable pressure on companies to adhere to the request to submit anonymised CSRs. EMA has expressed an intent to ‘name and shame’ companies that don’t play ball, by way of an annual list of non18 Journal for Clinical Studies

conformists. There is an inherent implication, too, that brands which hold back have something to hide. This could gnaw away at public perception and trust – the foundations on which life sciences brands are built and sustained. How Open is Open? Under previous EMA criteria (Policy 0043), requested clinical study reports could be supplied as redacted files (with patient references blacked out). But a big part of the current initiative is to maintain high utility of the materials being shared – maximising the insight that can be gleaned from each study. (It is quite telling that even though Policy 0043 was made law, the number of requests for report content to Clinical Data Request 2, the most popular repository, remains below 300.) With the new guidance, companies are encouraged to leave as much as possible of the original study report content open to analysis, preserving the integrity of the findings while protecting patients from discovery by making systematic adjustments (modifying all potential identifiers). One of the issues to have emerged, though, is the risk of inadvertent disclosure, particularly in the case of rare conditions – where human samples are small and variants more easily identifiable. EMA has tried to address this by setting the bar at a 9 per cent chance of identifying an individual. As samples get smaller, companies can adjust criteria so that someone becomes European rather than Irish, or is assigned to a broader age category – elevating the parameters until there are at least 10 comparable others. Date offsetting may be important too, so that patients can’t be identified from when they were known to be in hospital, for example. The ideal balance the industry is aiming for is something referred to as the Goldilocks Zone - between 0.05 and 0.09 - where data has maximum utility while maintaining an acceptably low risk of a patient being reidentified from their coordinates. Unfortunately, each company currently has its own set of rules for making these kinds of adjustments, which is adding to the complexity. If the industry is able to reach consensus, and companies can get this right, the EMA’s vision might be achievable. The danger comes when the balance shifts too far in one direction (towards utility at the expense of patient comfort, or towards subject reassurance at the expense of data’s usefulness), or when each company plays by a different set of rules.

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Regulatory Quite apart from the risk of paying out huge fines in the event of a data breach, no pharma company wants the reputational damage associated with compromising patient confidentiality. The new expectations are likely to have implications for staff recruitment and retention too. If you’re being paid £35,000 a year to do the job you’ve always done in regulatory affairs, it’s quite an undertaking to accept that you’re all that stands between your employer and a fine worth 4-6 per cent of the company’s global income. Not surprisingly, there has already been a backlash as companies (including PTC Therapeutics, in relation to a treatment for Duchenne’s muscular dystrophy) have challenged the EMA’s demands via the courts 3. Meanwhile, some countries have stricter laws on patient privacy than others, which could result in companies leaving those countries (such as France) out of the public versions of their clinical study reports, because of the increased risk. This in turn could compromise the validity of graphs, or averages being cited. Developing a Plan As the detail is digested, pharma companies are understandably anxious. A large majority of organisations are hanging back, waiting to see how trailblazers such as

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GlaxoSmithKline and Sanofi manage the process. The initial temptation for others has been to focus on the immediate need – i.e. to develop a capability that takes care of CSR documents specifically. But it is likely that this single-use approach will lead them down a dead end. Although the EMA has started out with CSRs as its target, the clinical study report is unlikely to be the sole source of focus for anonymising subject references. Indeed, the published EMA policy document indicates it is only a matter of time before all of the patient-level data behind those reports will need to be given the same treatment. This necessitates a more holistic approach to patient anonymisation – i.e. one that begins with the underlying patient-level data. Since everything else flows from that, it makes sense to start from this point. Being consistent and systematic from the outset ought to save a lot of time, expense and risk across the board as the EMA’s outlook broadens. Consistency is similarly important for ensuring that study findings retain their scientific meaning and value. If life sciences firms develop one type of process, or a particular algorithm, for anonymising clinical study reports and another for other documents or data, it could

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Regulatory become very difficult to re-join the dots if researchers later need to perform further cross-referencing and analysis. This risks undermining the broader value of the data, and could introduce risk to any wider conclusions that are later drawn from the source findings. Introducing new complexity could also create more work for companies down the line, as they are required to address follow-on queries once clinical trial findings are in the public domain. It could mean additional administrative work, tying up precious resources. Ideally, interested parties should be able to serve themselves with this additional information, finding all the answers they require online. EMA may have concluded that making CSRs the initial focus would make lighter work for organisations in the early stages of adapting to the new demands around clinical trial transparency, shielding companies from the need to worry about the technicalities of thousands of data fields that may be associated with broader data anonymisation. Concerned about the mounting time pressure, some life sciences organisations have turned to external agencies to process CSR documents. But in some cases this has introduced questions about quality, leading to work having to be redone. Meanwhile, given that a typical application for marketing authorisation may comprise 50 separate studies, keeping track of the different formulae that have been used to protect patients’ identities is creating its own issues.

Cutting Corners Could End Up Costing More The early signs are that this whole initiative is best handled internally, using software that can take original CSR content and produce a compliant, disguised study report in parallel – either by highlighting affected text so it can be changed, or by automating the scan-andreplace according to the rules or key the company has devised. Starting with the original data promises to be more economical in the long term, is more reliable, and means firms could prepare compliant, anonymised CSRs so that these are ready on the shelves at the time of marketing authorisation submission. It seems a much better approach all round, even if time is pressing now. Patient-level data is structured and well organised. This makes it easy to manage any transformations, because this can be done systematically and comprehensively in a few simple steps. Once they have found their stride, companies could expect to process an entire clinical study’s worth of data in just a day. Once the master data has been given the anonymisation treatment, amending the study reports becomes a simple matter of intelligent search and replace; the hard work has already been done.

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It’s also important to remember that the growing focus on transparency is not specific to Europe; the FDA has its own parallel ambitions, and other regions will surely follow. And companies should keep in mind the spirit and wider purpose of Policy 0070 too – which is to disseminate knowledge, and empower external communities to find the answers they need more readily – so that the benefits of research and of medicinal advances have the broadest possible reach. Embracing this aspiration and making the extra effort to deliver against its core values is a worthwhile position for pharma organisations to assume. Contesting EMA expectations won’t do companies any favours, certainly. EMA has already demonstrated its intention to stand its ground in the European law courts 4, confirming plans to appeal against initial court rulings that decided in favour of corporate privacy. The life sciences industry has enough battles on its hands at the moment; arguing against the greater good of patients shouldn’t be one of them. References 1. Policy 0070 is the latest transparency initiative of the EMA to publish clinical reports assessed as part of a marketing authorisation application, with a view to improving the transparency of assessment and aiding the development of new knowledge. First publications were due from October 2016 (http://www.ema.europa.eu/docs/ en_GB/document_library/Presentation/2016/06/ WC500209454.pdf) 2. https://clinicalstudydatarequest.com/Metrics.aspx 3. EMA Contests Two Judicial Decisions Over Clinical Trial Transparency Efforts, RAPS, September 2016: http://www.raps.org/Regulatory-Focus/ N e w s / 2 0 1 6 / 0 9 / 2 9 / 2 5 9 2 4 / E M A - Co n te s t s - T w o Judicial-Decisions-Over-Clinical-Trial-TransparencyEfforts/ 4. EMA Contests Two Judicial Decisions Over Clinical Trial Transparency Efforts, Regulatory Affairs Professionals Society, September 2016: http://www.raps.org/ Regulatory-Focus/News/2016/09/29/25924/EMAContests-Two-Judicial-Decisions-Over-Clinical-TrialTransparency-Efforts/

Cathal Gallagher has been working in the industry for several years now as a life sciences consultant for d-Wise. He is the stream chair at Phuse for Trends and Technologies and is part of an industry-wide working group for data anonymisation. Cathal’s expertise includes data transparency, reusable code, SDTM & ADaM templates, clinical data integration and Base SAS. Email: cathal.gallagher@d-wise.com www.d-wise.com Volume 9 Issue 1

Scientific excellence Customised solutions Personal accountability MLM Medical Labs is one of the leading Central Labs for clinical trials in Europe. For further information please contact Dr. Katja Neuer at kneuer@mlm-labs.com or visit us at www.mlm-labs.com.

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Regulatory Five Reasons to Embrace the ICH E6 (R2) Addendum Now Improve Study Efficiencies by Centralising Risk-based Quality Oversight and Trial Management In November 2016, the ICH E6 (R2) Addendum to Good Clinical Practice was implemented, delivering a breath of fresh air for clinical trial sponsors and CROs who have been looking for guidance on best practices for achieving true, risk-based quality management during clinical development. The Addendum is expected to increase the adoption of quality-by-design and quality risk management principles and methodologies in clinical development, while driving the use of innovative strategies and technologies for risk monitoring. It essentially mandates, harmonises and clarifies what FDA and EMA have been suggesting in their guidance about the value of embracing a centralised, technology-driven approach to risk monitoring that begins in planning and continues through the life of the research. The Addendum further defines the scope of clinical trial oversight responsibilities and describes the sponsor’s responsibility to establish a risk-based quality management system, ensuring the tools and methods used are “proportionate to the risks inherent in the trial and the importance of the information collected.” (792793) The ICH Addendum defines centralised monitoring as, “The remote evaluation of ongoing and/or cumulative data collected from trial sites, in a timely manner. Centralised monitoring processes provide additional monitoring capabilities that can complement and reduce the extent and/or frequency of on-site monitoring…” (1135-1138) The Addendum suggests sponsors and CROs should “…implement a system to manage quality throughout the design, conduct, recording, evaluation, reporting and archiving of clinical trials,” (786-787). It proposes that sponsors “…develop a systematic, prioritised, risk-based approach to monitoring clinical trials,” and suggests that “…a combination of on-site and centralised monitoring activities may be appropriate…” (1127-1131) It also specifically cites “evolutions in technology and risk management processes” as the reasoning behind the change, and encourages industry stakeholders to seek out new tools and processes that will help them take advantage of these efficiencies. FDA added information to the document on conducting a centralised monitoring programme and how to manage “significant noncompliance” to further establish unified standards across the trial site network. While the timeline of fully realising the vision of the ICH E6 (R2) Addendum may be measured in years vs. months, there are incremental yet critical gains that 22 Journal for Clinical Studies

sponsors and CROs can realise in the near term. Here we present five reasons why sponsors and CROs should adopt a centralised approach to risk-based trial monitoring, oversight and quality management now — to not only stay ahead of guidelines and regulations, but also to reap significant benefits across many aspects of clinical development. Improved Collaboration By implementing a centralised approach to trial and data monitoring, greater collaboration develops between sponsors, CROs and other vendors as they all have the opportunity to contribute to risk assessment planning and agree on mitigation strategies before the trial begins. With shared data visibility, sponsors and CROs benefit from a transparent approach to risk management that fosters shared responsibility, improved operational performance and more collaborative strategic relationships. Higher Data Quality The Addendum states: “The sponsor should periodically review risk control measures to ascertain whether the implemented quality management activities remain effective and relevant, taking into account emerging knowledge and experience.” (828-830). With centralisation, sponsors and CROs have access to more targeted data oversight, giving them greater insight into data quality trends as they are identified. For example, if a site forgets to enter critical data during a patient visit, the monitor is apprised and can act/react immediately so that the data is entered in a timely fashion. Faster Risk Mitigation The Addendum states: “The sponsor should identify those risks that should be reduced (through mitigating actions) and/or can be accepted. Risk mitigation activities may be incorporated in protocol design and implementation, monitoring plans, agreements between parties defining roles and responsibilities, systematic safeguards to ensure adherence to standard operating procedures, and training in processes and procedure.” (813-817) By implementing a centralised oversight component to their quality risk management (QRM) process, sponsors and CROs gain visibility into all trial data, which allows for real-time identification of risk trends across all trial sites. For example, standard algorithms may be used to track key risk indicators such as major protocol deviations, and send an alert when a site has exceeded acceptable thresholds, along with associated review workflows for intervention and training to improve results. The combination of a defined risk mitigation plan and insight with real-time data delivers the anticipatory oversight sponsors and CROs need to act or react to risks as they arise. Volume 9 Issue 1

Driving quality and integrity in scientific research and development As a not-for-profit association we have around 2,400 members of which 40% are based outside of the United Kingdom and located in over 50 countries worldwide, with many of our members working in an international environment and to international standards.

We continue to meet the needs of our members by: • Promoting quality standards in scientific research and development • Facilitating knowledge sharing through events, publications and networking • Liaising with regulatory agencies in the development and interpretation of regulations and guidance • Offering professional development opportunities • Working in partnership/cooperation with other organisations. Our membership caters for professionals including managers, scientists, auditors, inspectors and practitioners concerned with the quality and compliance of research and development. Our members focus on the safety and efficacy of pharmaceuticals, biologicals, medical devices, agrochemicals and chemicals in man, animals and the environment. More information on all of our first class services and products can be viewed on our website.

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Regulatory Greater Accountability With collaborative risk planning and shared data access capabilities, sponsors can hold CROs and other vendors accountable for executing risk mitigation strategies and achieving performance targets without the level of effort currently required to manage them. Improved Efficiencies and Reduced Trial Costs By adopting a centralised approach to risk-based trial oversight and quality management, sponsors and CROs can select sites based on experience, performance and behavioural data to reduce oversight burden. And, they can significantly reduce onsite monitoring costs with riskbased monitoring strategies, saving as much as 15-20% per trial. All of this leads to shorter study start-up and monitoring cycle times, which improves timelines. Choosing a Centralised Risk-based Quality Management Solution Before choosing a centralised risk-based quality management solution, sponsors and CROs should examine their current tools and strategies and draft a plan for updating their existing systems to meet regulatory compliance. This will help them to achieve efficiencies in the way they monitor the performance, integrity, and safety of clinical trials. That vision should include strategies for risk-based oversight that define key risk indicators and analytics with targeted thresholds, automated alerts, and action plans at the study level. These choices shouldn’t be made in isolation. To build the most efficient system, sponsors and CROs should implement industry best practices as much as possible, to avoid the pitfalls of customisation on every trial. Consideration for sponsors: When sponsors and CROs use technologies that provide different views or formats for trial information, they may have communication conflicts as well as the potential for redundant oversight, e.g., the sponsor’s system alerts the CRO to a potential risk that the CRO’s system has already identified but not yet acted upon. To avoid such redundancies, sponsors should involve CROs and speciality service providers in their vendor assessment process and decision-making on which riskbased management (RBM) solutions to implement. Such collaborations also enable better alignment around data review processes, system cadence and risk analysis, and create opportunities to build latency tolerance for followup actions into service agreements. This will further reduce the noise and resulting bottlenecks that may otherwise accumulate. Considerations for CROs: As CROs look to operationalise RBM, they should take into account the significant process and budgeting considerations that will result. In traditional outsourcing models, CROs can project resource allocation based on the study protocol, study plan, and variables such as complexity, number of sites, subjects, 24 Journal for Clinical Studies

and geographic distribution. This data helps them determine the number of CRAs and data management resources that will be required to meet the needs of the trial and sponsor. Implementing risk-based quality management and monitoring will require a more proactive and data-driven approach to risk management, using key risk indicators to drive investigator oversight. To get started, CROs can work with speciality service providers to help aggregate their vast amounts of data and make key plans for process modifications which can be fine-tuned over time by selecting the right infrastructure. It will make budgeting and resource allocation more challenging at first, but over time, sponsors and CROs will be able to adapt their processes and collect best practice information to inform future trials. In the meantime, sponsors and CROs should consider alternative budgeting strategies, with built-in flexibility to account for resource and workload fluctuations. Conclusion The ICH Addendum is expected to formalise trial process guidelines that will have a positive impact on data quality, so there’s no reason to hold off on implementation. The Addendum should be a wake-up call for trial sponsors and CROs that it’s time to change the way they think about — and address — quality risk management when planning and implementing clinical trials. By implementing a centralised QRM system now, sponsors and CROs can significantly reduce the time and cost of clinical trials while helping to reduce risk. Sponsors and CROs who adopt the philosophies outlined in the ICH Addendum sooner rather than later will benefit from competitive advantages driven by improved trial efficiencies.

Brion Regan, Product Manager, ERT Brion Regan has over 13 years of industry experience and has established himself as a thought leader in the application of data-driven process optimization and cloud-based technologies to the clinical research space. As Product Manager for ERT’s Trial Oversight Suite, he is leading the commercial development and management of the company’s growing portfolio of Software-as-a Service (SaaS) solutions. Prior to ERT, Regan served on the executive leadership team at technology start-up eClinical Insights as Head of Strategic Development. He has also previously held various positions in product marketing and business development at PharmaPros Corporation. Email: brion.regan@ert.com Volume 9 Issue 1

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Regulatory Bridging the Clinical Data Structure Gap to Empower Holistic Risk Management Per the suggestion of regulatory agencies, there is an increased focus on the merits of adapting a risk-based monitoring (RBM) approach. Effective RBM reduces costs, improves data quality and enhances oversight, but most of the existing RBM solutions in the marketplace have significant shortcomings, in part because they make it difficult to get a holistic view of data. They are not built to accommodate the complexities and myriad data sets of today’s clinical trials. To move beyond the functional focus on monitoring to a complete approach for riskbased management across a trial requires that critical data sources be integrated, in near real time.

of clinical investigations.” The FDA encourages sponsors to take advantage of these “innovations in modern clinical trials.” Although as an industry, we have indubitably made strides in our leveraging of technology, one of the biggest factors holding us back—in our effective use of RBM, as well as in other areas of clinical trial processes—is data integration. Data Integration’s Role in Effective RBM Clinical Data Today

RBM platforms could drive even more advantages by utilising technology to facilitate data integration, and in turn, a holistic approach to RBM. Let’s examine the benefits of RBM, the shortcomings of existing RBM solutions, and how a new approach to data integration and analysis that leverages the latest in technology developments can improve RBM to drive more benefits and move RBM from monitoring to management. Why RBM Matters The introduction of the ICH E6 (r2) addendum to Good Clinical Practice means that for most biopharmaceutical companies and CROs, taking a risk-based approach is no longer an option but a necessity. With an RBM approach, sponsors attempt to proactively identify risks and use resources more strategically to ensure patient safety and data integrity. The objective of the addendum is to encourage biopharmaceutical companies and CROs to adapt a more efficient approach to risk-based monitoring, one that combines centralised and on-site tactics. Research shows that when risk-based monitoring includes a “centralised, near real-time overview of the data with well entrenched risk detection and mitigation strategies, the result is one of the industry’s most effective tools for managing a clinical trial proactively.” Benefits include an earlier identification of potential risks, which in turn can help protect patients and allow sponsors to use resources more wisely; more reliable study data; better communication between sites; and, potentially, lower site monitoring costs, which is one of the leading expenditures contributing to the increasing costs of clinical trials. Technology can improve the effectiveness of both centralised and on-site monitoring. The FDA’s Guidance for the Industry on a Risk-Based Approach to Monitoring states that “increasing use of electronic systems and records and improvements in statistical assessments, present opportunities for alternative monitoring approaches (e.g., centralised monitoring) that can improve the quality and efficiency of sponsor oversight 26 Journal for Clinical Studies

Although many vendors market RBM solutions, many of these offerings have prodigious shortcomings that take away from the user’s ability to capitalise on the potential of RBM. When selecting an RBM solution, sponsors should consider how the solution can help with risk identification, risk monitoring and issue management. They should also, from the start, consider the tool’s approach to data integration and its ability to enable the needed reporting and analytics. At the earliest stage of the draft guidance from the FDA and EMA on RBM, they identified that the siloed approach of various clinical research activities, as well as the siloed nature of the supporting platforms, was often a key issue. The availability of an organisation’s data is often reflective of its siloed structure. For effective RBM, you need access to all the necessary data sets and the ability to integrate them. Data collection issues not only affect RBM, but also other aspects of trials. Data integration brings to life risks that are not apparent when you examine the data from one source alone, i.e. eCRF and audit trail, drug safety database, etc. More data means more knowledge, and that helps site sponsors make more informed and effective decisions. Volume 9 Issue 1

Regulatory The Current RBM Marketplace Some RBM solutions in today’s marketplace are simple analytic or reporting tools, or limited solutions built on predefined data models with loosely coupled analytics. Many of the solutions are not built for scale and cannot grow easily as an organisation’s needs expand and change. We can categorise the majority of existing RBM solutions into one of the following categories: 1. Business Intelligence and Visualisation Platforms These tools are commonly referred to as analytic tools. They are built to provide interactive data analysis. Data visualisation is a key component of effective RBM, but it is not the only component. These tools simply visualise existing data, but they do not aggregate data in real time and cannot perform interactive data discovery, data aggregation or RBM functionality. Plus, they require hard-coded or manual connections to data sources or data warehouses. 2. CROs/Service Providers CROs often build custom RBM solutions for trials that they are running on behalf of sponsors. They are built around proprietary data warehouses. CROs typically offer sponsors the ability to sign up for services that allow them to view the clinical data, but that is the extent of their visibility, and they are unable to merge additional data with the data from the CRO. Other service providers, such as consulting firms, offer data tools, but these companies usually do not have software development expertise and/or deep domain knowledge of clinical research processes. The solutions lack RBM functionality, data and system agnostic technology, and do not integrate with other functions, like medical review and payment solutions. 3. Platform Vendors A growing number of clinical informatics vendors that sell their own products (i.e. EDC, IWRS, CTMS, etc.) are offering solutions for RBM. These, too, are limited in functionality and lack data aggregation technology. They are also tethered to the vendor’s proprietary software. Although some vendors have developed payment systems which integrate with the RBM platform, users are then limited to the vendor’s payment system and cannot opt for other systems. -eClinical Reporting Solutions There are a variety of eClinical solutions on the market, which may integrate some data sources into a SaaSbased clinical data aggregation platform, but they are dependent on connectors or offer a “unified” but not integrated solution. The analytics functions are also tied to the data aggregation layer, so users cannot use a different analytic engine and often struggle to bring in data from external sources, particularly EDC and CTMS. These tools have been modified for use in RBM, but in general, they were not purpose-built for this use-case.

-Statistical-based With these solutions, data is manually mapped into a stats system and then run against models to make inferences. They do not make it simple to integrate data, perform operational RBM functions or integrate with medical review and site payments. The Clinical Data Lake Differentiator To manage the holistic risk associated with a clinical study, it is critical to have timely and quality connected data from the various sources collecting data for clinical research. Connected data allows users to identify the correlated risk signals earlier on in a clinical study process. A data integration solution that uses a big data lake, a newer approach to data storage, would facilitate connected data and make a tremendous difference for its users. The most common approach to clinical data aggregation today is the data warehouse. The approach of choice for big data companies like Facebook and Google is the data lake, which allows you to input massive amounts of data into the system, as is. In most clinical data solutions, data is extracted from a source, transformed and then loaded (ETL) into a common structure that can only accommodate a certain level of variability. Data lakes invert the process and instead use ELT, which means an RBM platform built on a data lake extracts data, loads it and then transforms it. It does not matter where the data is coming from or how it is structured. As long as it is related to clinical research, users can load it into the data lake-based system. Then, end users can transform the data on a near real-time basis for analysis and signal/risk/issue detection. The data lake architecture is better suited for the myriad sources of data coming from the many platforms and vendors companies and CROs are using. Additionally, because a data lake does not require predefined set models, extensibility is simpler. The solution can accommodate the changing clinical data structures over the course of a clinical development programme with changing vendors and source systems. DATA L AKE Stores data in a flat architecture. Data schemas are not defined until after data is queried. Eliminates silos and makes it possible to gain a holistic view of data. Store and retains all data. Supports all types of data, structured and unstructured (EDC, CTMS, IRT, lab, PK, biomarker, line listings, etc.). Flexible and easy to change. Used by data science experts like Facebook and Google.

VS .


Stores data in a hierarchical structure of files and folders. Schemas need to be defined before the data is inputted. Because data is aggregated, some viewability can be lost. If data doesn’t answer the pre-determined questions, it will not be stored. May not store all data types. Rigid and time-consuming to change. Used by the majority of clinical data solution providers.

Requirements for a Morefor Effective Platform Requirements a RBM More Effective RBM Platform Advancements technology and RBMfor “aapproaches Advancements in technologyin and RBM approaches represent an opportunity more holistic and proactive approach Off-site and Central to TransCelerate BioPharma represent anthrough opportunity forMonitoring,” “a moreaccording holistic and proactive Inc. Its position paper explains how technology advancements can facilitate efficiencies without approach through andmonitor Central impacting subject safety – in fact, it Off-site can help site sponsors safety even Monitoring,” more effectively. To do so requires twoto technology pillars: according TransCelerate BioPharma Inc. Its position 1. The explains integration of disparate data sources and formats to enable efficient remote monitoring. paper how technology advancements can 2. The development of relevant analytic to enable the identification of outliers and trends in large data sets.

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Volume 9 Issue Because RBM draws on such a vast array of data sources, it also requires technology solutions that 1 are flexible enough to load data from any application, contract, financial, LAB, EDC, IRT, CTMS, database, line listing, file or report. The system should also be able to learn from previous mappings

Regulatory facilitate efficiencies without impacting subject safety – in fact, it can help site sponsors monitor safety even more effectively. To do so requires two technology pillars: 1. The integration of disparate data sources and formats to enable efficient remote monitoring. 2. The development of relevant analytic to enable the identification of outliers and trends in large data sets. Because RBM draws on such a vast array of data sources, it also requires technology solutions that are flexible enough to load data from any application, contract, financial, LAB, EDC, IRT, CTMS, database, line listing, file or report. The system should also be able to learn from previous mappings and capable of mapping data into formats such as CDISC SDTM (study data tabulation model) and ODM (operational data model), as needed. A relational database solution in which a schema must be defined upfront will not work, as data is added and changing too frequently (i.e. additional EDC systems is added, a CTMS system is replaced, etc.) A documentoriented database allows clinical development teams to analyse clinical, operational or other data of interest. It

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can continuously and automatically bring data together from all of the disparate systems used in a clinical trial, allowing ongoing trial oversight through risk assessment. With complete data integration, RBM solutions can also enable integrated workflow processes, budgeting, contracting, clinical data review and payments. Data lakes can facilitate systems for the holistic riskbased monitoring needed to proactively identify and prevent inadequate site behaviours and processes as early as possible, and power solutions that will prove superior to reactive RBM approaches that only focus on reducing the amount of source document verification (SDV) and visits to sites where there may be a problem. The new breed of RBM solutions should allow users to categorise risks, determine what type of monitoring is needed, and help inform the development of an integrated quality risk management plan (IQRMP). Users could also develop study-specific key risk indicators (KRIs), with thresholds designed to trigger action. The Importance of In-stream Review of Data Clinical trial risks are incredibly time-sensitive. In-stream review of clinical data is imperative to identifying risks early in the clinical development process. Site sponsor must be able to review risks and take mitigation actions

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Regulatory and retention, further saving time and money along the clinical trial process. Conclusion With a combination of centralised and on-site monitoring, biopharmaceutical companies and CROs can proactively identify and prevent inadequate site behaviours and processes. To do so most effectively, they need a holistic approach to data—an ability to see all the information available to them, in near real time. The technology needed to facilitate this is on the market today, and already being used by leading companies around the world. A clinical data lake can power a fully-integrated and source system agnostic RBM solution. This solution can integrate data from clinical, operational and other data sources that previously existed in silos, facilitating a holistic approach to RBM. This will make it simpler to integrate analytics, medical review and site payments, further increasing the benefits of RBM by driving efficiency and cost-savings.

quickly. There are clinical data review solutions on the market today that allow for medical review of adverse events via reviewing graphical patient profiles and other medical data, but with a data lake approach, users can glean meaning even faster. They have the ability to gain insight into the clinical data being analysed (i.e. cleanliness, verified, not verified, etc.) before the clinical data analysis is even performed. It is embedded right into the RBM workflow. In today’s clinical data review solutions, medical reviewers have no visibility into the state of the data—they don’t know if the data they are looking at is clean or dirty. Because a data lake-based platform does not require a hardcoded connection, it can also allow users to connect with and analyse data from any EDC systems, SAS file, lab data, etc. Along with data review and RBM components, a data lake approach also makes it possible to connect with a payment module, and even to set up automatic site payment based on triggers, such as the data being cleaned. This not only benefits medical reviewers but also helps the sites and investigators, who will appreciate being paid on time and incentivised to perform well. The payment cycle for services provided by sites/ investigators is often more than three months and is a highly manual payment process. By integrating site contracts and payment management functionality, it becomes easier to pay sites and investigators promptly, which will in turn encourage improved site performance, and could also enhance improvements in site recruitment 29 Journal for Clinical Studies

References 1. Shapley, S., Sweeney, F. Addendum to ICH E6 (R2). (2015) 2. Shukla, B.K., Khan, M.S., Navak, V. Barriers, adoption, technology, impact and benefits of risk based monitoring. Int J Clin Trials. 3(1): 9-14 (2016), available online at http://www.ijclinicaltrials.com/ index.php/ijct/article/view/100/67 3. Sertkaya, A., Wong, H.H., Jessup, A., Beleche, T. Key cost drivers of pharmaceutical clinical trials in the United States. Clin Trials. 13(2):117-26. (2016) Available online at https://www.ncbi.nlm.nih.gov/ pubmed/26908540 4. U.S. Department of Health and Human Services Food and Drug Administration. Guidance for Industry: Oversight of Clinical Investigations—A Risk-Based Approach to Monitoring. (2013) 5. TransCelerate BioPharma Inc. Position Paper: RiskBased Monitoring Methodology (2013)

Sudeep Pattnaik is President & CEO of ThoughtSphere. Prior to founding ThoughtSphere, Sudeep was the global leader of products for Quintiles, the largest CRO Fortune 500 life science company in the world, creating and leading the strategy team behind a $60M integrated healthcare data hub. He also played a key role in defining the risk-based modelling approach for optimising the clinical development process and helped develop a bestof-breed RBM platform for the industry. He holds an MSc in computer science from Uktal University (India) and an MBA from Leeds School of Business at the University of Colorado, Boulder. Volume 9 Issue 1


Compliance Data in Clinical Research There is a great deal of emphasis on streamlining the regulatory process to get important drugs to subjects who need them expeditiously. This is of increasing importance because of the trend to personalised drug development and the realisation that classic randomised clinical trials are becoming prohibitively expensive. Whereas in the search for “blockbuster” drugs, recruiting a few hundred subjects for a trial was manageable, this is no longer the case for drugs to treat rare disorders. It is simply too costly to seek out and process these less prevalent subjects. Strategies to get investigational new drugs (INDs) approved more rapidly (and cheaply) abound. These include vaguely-described easing of regulatory requirements, accelerated approval, use of surrogate endpoints, patient registries and adaptive trials. While on the absolute scale these are all methodologically inferior to classic randomised ITT (intent to treat) methodologies, on the larger stage they offer considerable potential for addressing rare disorders. So why are such alternative strategies not in widespread use? Fear of the unknown inhibits their adoption. The classic research paradigms have a long history with the FDA and EMA, so researchers have confidence that, if they do things a certain way, a predictable regulatory response will follow. However, with innovative strategies there is no such history. Although regulators encourage their use, they do not give specific guidelines, and nobody wants to be the early adopter who has an expensive study turned down because of methodological innovation. Thus, changes in strategy are slow.

be overemphasised 6, as poor compliance can create a downstream effect that can persist long beyond regulatory approval. Despite the magnitude of the problem, very little effort has been made to address it. Clinicians and researchers alike agree their patients are poorly compliant, yet research and clinical care both proceed as if they were fully compliant. Research as a Signal-to-noise Ratio Few research reports mention subject compliance and fewer still make an effort to address it. Research can be viewed as an exercise in optimising a signal-to-noise ratio (S/N) where the signal is the desired therapeutic effect, and the noise all the factors that conspire to obscure the signal. The therapeutic effect is the variability between treatment groups (SS between groups in (1)) as measured by the primary outcome measure(s). Noise factors such as age, sex, body mass, activity level, gastrointestinal absorption, differences in metabolism, use of alcohol and drugs, use of herbal remedies, and myriad others both known and unknown obscure the therapeutic effect (Figure 1). These are typically lumped together and distributed at random over all subjects to give the SS within groups. The effectiveness of a treatment is evaluated by calculating a S/N such as the F (analysis of variance) or analogous test (1).

There is another way to expedite the approval process, and it can be used with both classic trial designs and alternative strategies. It is based on an idea that is older than research itself. Hippocrates, circa 390 BC, cautioned his students to ‘Keep watch also on the faults of the patients, which often make them lie about the taking of things prescribed’ 1. 2000 years later it is widely accepted that patients and subjects are poorly compliant with medication regimens, and a large volume of literature estimates that 50 to 65 per cent compliance is common 2.

Fig. 1. Sources of noise

To illustrate the magnitude of the problem, the current US Surgeon-General cites the annual cost of noncompliance in its broadest sense to US healthcare as between $100 and 200Bn 3, and other estimates are even higher 4. This is just for the US – the problem is global. A 2003 World Health Organization report opined “Increasing the effectiveness of adherence interventions may have far greater impact on the health of the population than any improvement in specific medical treatments” 5. In clinical research, the importance of compliance cannot

Various strategies are used to control within group variability in clinical trials, a common one of which is exclusion criteria. In this way the SS within is minimised, increasing the likelihood of detecting a signal. However this addresses only a small part of the noise spectrum and, as shown in Figure 1, a large source of noise is due to subject non-compliance. This is an untapped source of power than can be utilised to increase the efficiency of the drug development process. The terms compliance and adherence are used interchangeably in

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Regulatory the literature. Non-compliance poses a big problem for clinical trials, as poor compliance reduces the accuracy of a trial’s data, encouraging inaccurate conclusions about a drug’s effectiveness 7. Generally, this is in the direction of underestimation and may lead to effective medications being abandoned, or approved drugs being commercialised at higher than optimal dosing that increases the chance of side-effects which can in turn prompt subjects to discontinue the drug 8. Measuring Subject Compliance Subject self-reports have been used to assess compliance, but there is considerable anecdotal evidence that subjects overestimate their compliance. As an alternative, medication diaries may be used, but these also result in overestimation, frequently being filled out with less than perfect recall while the subject awaits a follow-up visit. By default, pill counts and added pill counts are now widely used in clinical trials. In 1986, Aardex marketed the first reliable electronic compliance monitor (ECM) in the form of a vial cap (MEMS ®) that recorded opening and closing events as a proxy for medication taking. The MEMS ® and, more recently, Information Mediary Corp’s eCAP™, have been used extensively since, providing the ability to quantify baseline compliance dynamics and confirming the ineffectiveness of self-reports, medication diaries and pill counts. However simple opening and closing events cannot reliably account for a number of non-compliant scenarios such as the subject taking several or all the tablets from a vial at one time, opening and closing the cap without taking any tablets, or leaving the cap off the vial. With increasing interest in blister packaging, 2000 saw the first smart blister packages, introduced by both Information Mediary Corp in Canada and Cypak in Sweden, that could monitor medication-taking at the individual dose level. Smart blister packages are now widely available and deployed in clinical trials worldwide. Compliance data are now easy to capture. This raises the question of what to do with the compliance data. As shown in Figure 1, non-compliance is a large source of noise in the S/N and removing this noise from the denominator would give a larger S/N – the clinical effect would stand out more clearly. This is particularly important where there is a lot of variability within subjects such as in patient registry or natural history studies. Applying Subject Compliance Data Power is the ability of a study to detect a real clinical effect (significant S/N). The most effective way of increasing a trial’s power is to measure and control for poor compliance, reducing the denominator of the S/N. Power increases with sample size and decreases with noise. The relationship between power, sample size and compliance is shown by the modelling data in Figure 2. www.jforcs.com

Fig. 2. POWER by COMPLIANCE by N 1) The basic use of compliance data is to give the sponsor confidence that it has done everything to ensure the accuracy of the data. This confidence will flow through to the regulatory agency overseeing the trial. Did the subjects take their medication as prescribed? What was the incidence of non-compliance and was it distributed equally among groups? Were there outliers and could they have distorted the results? Was there missing data? What was done to compensate for missing data? In these roles, compliance data are examined post hoc, documented in an organised way, and used to support the validity of the process that led to the results. In this role compliance data do not affect the primary outcome measures but simply speak to the overall rigour of the trial. 2) Compliance data can be used to screen for problematic compliance prior to enrolling subjects in a trial. Subjects who drop out of a trial or are grossly non-compliant are highly undesirable as they distort the results and conclusions. For ITT trials, this distortion is amplified, and the increasing focus on drugs for rare disorders and the associated difficulty (cost) of recruiting subjects exacerbates the dropout problem and lengthens the regulatory cycle. In short, the ideal trial would see all subjects fully compliant with no dropouts. A brief placebo pre-trial can identify those who are prone to non-compliance and they can either be removed from further consideration or given targeted education to increase their compliance before being enrolled in the study proper. 3) Compliance data can be used to assess the subjects’ compliance post hoc. Data mining can throw light on many aspects of subject behaviour and can be tailored to the interests of the sponsor and regulator. For example, a recent ECM-enabled trial found that 40 per cent of Journal for Clinical Studies 31


subjects deblistered their medication on at least one occasion, obviating the advantages of blister packaging. Without compliance monitoring, this would have gone undetected. This implicated poor package design (the package was unwieldy and utilitarian) and the subjects did not like carrying it around. As a result, the sponsor switched to a more compact and appealing format for subsequent trials. 4) In accordance with Surgeon-General C. Everett Koop’s widely cited: “Drugs don’t work in patients who don’t take them”, subjects can be stratified according to their compliance. For example, a recent study found no significant difference between treatment and placebo groups, auguring poorly for the drug’s future. However, when the subjects were divided into tertiles according to compliance, a subsequent analysis showed a highly significant between-group effect for the third of the subjects that actually took the medication (i.e. had a greater than 85 per cent compliance rate). Had subject compliance not been monitored, a promising IND might have been abandoned. 5) If preplanned, ECM data can be used to adjust primary outcome measures for compliance using analysis of covariance or similar adjustment techniques. These are variants of stratification that have more complex inherent advantages and disadvantages. 6) ECM can detect subtle medication-related bias effects that can lead to erroneous conclusions about drug 32 Journal for Clinical Studies

efficacy. For example, subjects in a treatment group might experience mildly euphoric or mildly unpleasant side-effects that control subjects do not. Such subtle effects would typically go unreported by the subjects and might bias the results and confound standard tests of significance. However, differential between-group compliance rates might signal a bias problem. 7) ECM can serve as part of a REMS (risk estimation and mitigation strategy) for trials where non-compliance can have serious consequences beyond those of simple data inaccuracy. Opioids, for example, can result in fatal overdose when taken to excess, and these drugs are often diverted for sale on the street. ECM detects the deblistering that suggests such activities and allows the investigator to implement an intervention strategy. 8) Using ECM may in itself improve subject compliance although this has not been demonstrated due to the ethics of monitoring compliance without informing the subject. 9) The highest and best use of compliance data is to give feedback to subjects about their compliance as they progress through a clinical trial. At follow-up visits, smart packages are scanned and the compliance data reviewed with the subject. Those subjects with less than perfect compliance are targeted for motivational counselling in an effort to improve their compliance for the duration of the trial; those with perfect compliance are encouraged to continue. Standardised motivational techniques are Volume 9 Issue 1

Regulatory used to ensure the process does not bias the results that will later flow from the primary outcome measures. While the clinical monitors have access to the compliance data at follow-up interviews, the primary dependent measures remain double-blinded until the study is completed. If treatment and control groups participate similarly in the motivational counselling process, the use of ECM data does not bias the study. To avoid introducing bias, the motivational interviews are semi-structured, with all subjects receiving similar feedback regardless of their level of compliance. The interviews are also timed to avoid the Hawthorne effect. Done properly, this process gives increasing mean compliance over the course of the study, reducing the error variance (noise) and increasing the accuracy of the study results (signal). In statistical terms, the study will have increased power, where power is the ability to detect real differences between treatment conditions. ECM is even more important for adaptive trials due to the increased number of decision points and the consequent inflation of the probability of making erroneous decisions (type I error). If an adaptive trial has five preplanned decision points and decisions are to be made at the 0.05 level, the probability of arriving at one erroneous conclusion is (5 * 0.05) or 25 per cent. Increasing the accuracy of the data by controlling the noise due to non-compliance will minimise this risk. This argument is even more compelling for the newly legitimised patient registry and natural history studies as means of addressing rare disorders. These studies involve large numbers of subjects with associated high noise levels due to individual differences, so it is more difficult for the therapeutic signal to be seen over the noise. Measuring and controlling for non-compliance is critical if these kinds of study are to give meaningful results. Return on Investment Positive return on investment (ROI) occurs with all of the above applications, although for most the ROI will be subjective. Monetising “confidence” in one’s data is difficult. However, for the best use scenario (9), ROI can be calculated. Modelling studies show that for each per cent increase in mean compliance, the calculated sample size (N) can be reduced by two per cent. Since mean compliance tends to be from 50 to 65 per cent, targeted coaching can realistically increase compliance by 10 to 15 per cent. This would allow for a 20 to 30 per cent reduction in the N determined pre-trial from power calculations, without reducing the power of the study to detect real differences between treatments. Cost savings result both from the reduced cost of recruiting and processing the smaller number of subjects, and the reduced time to regulatory approval that gives longer subsequent patent protection. The ROI in this scenario is typically dramatic, as demonstrated by the ROI calculator at http://www.informationmediary.com/roi/ roi-calculator. Given the fact that electronic compliance monitoring more than pays for itself in addition to having significant non-monetary value, there is no rational barrier to achieving the prediction of eminent statistician www.jforcs.com

Bradley Efron: "At some point, perhaps not in the far future, it will seem as wrong to run a clinical trial without compliance measurement as without randomization.” Bradley Efron, Professor of Statistics, Stanford 9 References 1. Hippocrates of Cos, Decorum XIV, circa 390 BC. 2. Nichol MB, Venturini F, Sung JCY. A critical evaluation of the literature on medication compliance. Annals of Pharmacotherapy, 1999, 33, 531-540. 3. Benjamin RM. Medication compliance: helping patients take their medicines as directed. Public Health Reports, 2012, 127(1), 2-3. 4. IMS Institute for Healthcare Informatics. Avoidable Costs in U.S. Healthcare, June 2013, 7. 5. Sabaté E (Ed). Compliance to Long-term Therapies: Evidence for Action. Geneva: WHO, 2003, 53. 6. Czobor P, Skolnick P. The secrets of a successful clinical trial: compliance, compliance and compliance. Molecular Interventions, 2011, 11I(2), 107-110. 7. Smith DL. Patient nonadherence in clinical trials: could there be a link to postmarketing patient safety? Therapeutic Innovation and Regulatory Science, January 2012, 46(1), 27-34. 8. Capgemini Consulting/HealthPrize. Estimated Annual Pharmaceutical Revenue Loss Due to MedicationNonAdherence, November 26, 2012, 11-14. 9. Efron B. Forward: Limburg compliance symposium. Statistics in Medicine, 1998, 17, 249-250

Allan Wilson MD PhD was Full Professor and Head, Section of Addiction Psychiatry, at the University of Ottawa for over 25 years. He co-founded Information Mediary Corporation in 2002, and is now devoted full time to the study of medication compliance. Allan has worked as a consultant in the healthcare field for both public and private sectors, and his research interests lie in clinical pharmacology, biotechnology and large data systems. He is an internationally known researcher in the field of addiction medicine, and has published over 100 academic papers in the areas of pharmacology and clinical outcome research. Journal for Clinical Studies 33

Market Report

Clinical Trials in Russia & EAEU's Regulatory Update Declining healthcare spending combined with increased pressure on the HC system budget is creating an incentive for patients to consent to new treatments and fostering a positive environment for the development of the CT sector. There are a multitude of factors that influence companies’ decisions to open clinical operations in Russia for all types of clinical trials: the patient pool, relevant investigators’ expertise and cost-efficiency, to name just a few. This article analyses the key factors that are shaping the Russian and CIS market for clinical trials in the short term, and discusses the regulatory initiatives that are coming into force to facilitate its further development, in particular the introduction of the regulatory framework affecting the clinical trials sector within the Eurasian Economic Union (EAEU). Having a projected value of 21 billion dollars in 2019 1, the Russian and CIS pharmaceutical markets remain attractive for the international pharmaceutical industry. There are many unmet medical needs in the region, particularly in the treatment of non-communicable diseases and lifestyle disorders, such as cardiovascular diseases, diabetes and cancer. The Healthcare, Pharmaceutical and Clinical Trial Environment in Russia With the increasing price pressure on international pharma, and with promotion of cheaper generic alternatives in the region, it remains unclear how the current deteriorating economic situation in Russia and the CIS will affect patients’ access to innovation. Russia does not have a well-defined reimbursement system and there is no clarity as to what path the reimbursement in Russia will take in the near future – either opting to concentrate on socially unprotected categories, patients with treatable conditions, severe stages of diseases or the working population. An additional challenge in bringing innovative drugs to market lies with the current procedure for registration of pharmaceutical products that may appear daunting and lengthy to the companies that do not have substantial local knowledge of the political, cultural and regulatory differences. However, the slowing of HC spending and increasing pressure on the HC system budget create an incentive for patients to consent to new treatments and create a positive environment for the CT sector development. How is Russia Positioned in the Clinical Trial Landscape? Growth in the number of clinical trials conducted in the country has increased considerably over the past five years, with an average of close to 100 new trials being conducted every year. The number of trials outsourced to CROs is also growing, offering pharma an opportunity to benefit from local resources and specialised expertise. 34 Journal for Clinical Studies

Figure 1. Clinical Trials in Russia in 2016 (Source: Synergy Research Group) The EUEA region is positively ranked in terms of costsaving opportunities, and in 2016 clinical trials in Russia alone were sponsored by companies from 39 countries.

Figure 2. Russian vs International Sponsors in 2016 (Source: Synergy Research Group) Among other factors that were mentioned by the industry experts were: fast patient recruitment (averaging between two and four months), especially in speciality disease areas where access to modern medicines is limited; and access to educated, experienced and compliant investigators who are motivated to participate in clinical trials to advance new drug development. How is it Possible to Increase the Competitiveness of Russia and the CIS? Stability and predictability in the regulatory process could be a game-changer: improving opportunity for direct discussions with authorities on dossier submission, greater transparency, simplifying the process and reducing the time needed for clinical trial applications were mentioned by the industry players as key improvements that would be welcomed by the market players. Krishnan Ramanathan at Novartis commented that the “Greater focus on pediatric critical trials and granting priority for early stage studies (Phase II Vs. Phase III) will help to address unmet needs.” He also Volume 9 Issue 1

Market Report added that “such improvements as increasing digitisation and availability of electronic medical records can lead to accurate planning and patient selection. Creation of local registries and epidemiology data for better surveillance of different diseases could help demonstrate healtheconomic benefit in addition to clinical-benefit.”

Commission, explained the guiding principles of the new legislation. He announced mid-2017 as a release date for the much-anticipated uniform procedure of clinical trials in the EAEU, as well as the document containing requirements for the inspection of clinical trials. The new regulation incorporates the best European practices and is aimed at ensuring unity of the mandatory requirements for the quality, effectiveness and safety of drugs which are circulated in the territory of the EAEU. At present, those documents are displayed at the Eurasian Economic Commission’s website and are open for public discussion.

Figure 3. The clinical trials map of the world (Source: QuintilesIMS) Clinical Trials – New Legislation One of the most noteworthy changes that the market expects is a long list of regulations of the Eurasian Economic Union that will enter into force in the next 1-10 years, including those related to clinical trials and aiming at further harmonising procedures of registration and control in circulation of medicines in Russia and the EU/ US. The Introduction of the Regulatory Framework Affecting the Clinical Trials Sector within the Eurasian Economic Union (EAEU) The Eurasian Economic Union includes the Russian Federation, the Republic of Armenia, the Republic of Belarus, the Republic of Kazakhstan and the Kyrgyz Republic. The creation of a single market will have an enormous impact on the development of the pharmaceutical industry as a whole and will particularly affect the clinical trials sector. The legal framework for the medicines and medical product circulation in the EAEU is in the final stage of development. A number of documents have been shaped by the Department for Technical Regulation and Accreditation, Eurasian Economic Commission in the past couple of years. During the Clinical trials in Russia Forum organised by the Adam Smith Conferences in November 2016, Moscow, Dmitry Rozhdestvensky, Deputy Head of the Department for the Coordination of Formation of the Common Market for Drugs and Medical Devices, Department for Technical Regulation and Accreditation, Eurasian Economic www.jforcs.com

What to Expect from the New Regulatory Framework in the EAEU All new drugs will be analysed based on the new standards that are in line with the Guideline for Good Clinical Practice (GCP), while genetic parameters will be in line with those outlined in the Good Laboratory Practice (GLP). As for previously approved generic drugs, they will have to undergo a procedure of “bringing the dossier into compliance” (in order to ensure that the dossier is in line with the new Union’s requirements). Mr Rozhdestvensky announced that producers will have a lead time of up until the end of 2025 to ensure that the volume of the investigation (data used) is compliant with the new Union’s standards. Industry players are encouraged to look for the supporting data across the published scientific research papers. Time lead for the approval of the clinical investigation is still considered rather long, compared to EU countries, which has an immediate impact on commercial motivation. While 30 days for designing a protocol is considered sufficient for the experts to raise any issues, it is unlikely that this period will be shortened by the regulator. Addressing the audience’s questions regarding the prospects of implementing seamless Phase II/III designs, Dmitry Goryachev, Head of Expertise and Control of Ready Medicaments, FSBI "Scientific Centre for Expert Evaluation of Medicinal Products" of the Ministry of Health of the Russian Federation, reassured the industry that if properly applied, there is no regulatory objection in principle to a seamless Phase II/III design forming one part of a confirmatory evidence base. At the same time, in order to merge Phases II and III, regulators will require strong scientific proof and statistical data, outlining the grounds. He also mentioned the necessity of the submission of the intermediate data analysis, in order to share the scientific and statistical evidence with the regulator. With year-on-year growth in the number of approved clinical trials, fast patient recruitment rates, experienced investigators and further development and increased transparency of the legislative framework regulating the Eurasian Economic Union, EAEU countries are staying Journal for Clinical Studies 35

Market Report

in the spotlight for sponsors and CROs alike. Increasing digitalisation and further use of innovative technologies, as well as creation of the unified electronic medical records, would further facilitate development of clinical trials and would approve availability of the innovative medicines to the patients. References 1. IMS Health Market Prognosis, June 2015 2. Clinical Trials in Russia Forum, Adam Smith Conferences, November 2016, Moscow 3. Synergy Research Group, Orange Paper (quarterly and annual reports, 2016) 4. QuintilesIMS report, November 2016

Jane Gelfand is Managing Director at Adam Smith Conferences. Jane has started her career in early 2002 and occupied various managerial roles in industryleading organisations, including Informa plc and Marcus Evans. While at Informa, Jane has been the Divisional Head for the life sciences portfolio, conceptualising and growing one of the key verticals. She has been instrumental in creating and developing clinical trials, market access, regulatory, legal & compliance and medical affairs events across the emerging markets (including Russia & CIS, MENA and Eastern Europe). Currently, Jane is managing London and Moscow offices and is responsible for developing the company growth strategy across seven emerging markets. Email: janeg@adamsmithconferences.com Kristina Dutchak is a Programme Director at Adam Smith Conferences. With over 10 years of business development experience across various industries, and with a particular focus on life science, financial, technology and innovations, Kristina conceptualises and develops business events across emerging markets. Having worked with government ministers, business leaders and industry experts across the CIS, Europe, UK, Asia and the US, Kristina produces content-driven programmes, securing international and regional KOLs and engaging key market players, providing a fertile ground for participants to gain up-to-the-minute market intelligence and invaluable opportunities to network and generate new business. Email: kristinad@adamsmithconferences.com

36 Journal for Clinical Studies

Volume 9 Issue 1

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Who managed the supply chain

Across 20 different countries

With our global network of audited and approved suppliers, total quality focus and worldwide distribution capabilities, you can trust Clinigen to make your trial a success. To trial Clinigen CTS, contact: Email: ctsinquiries@clinigengroup.com Web: www.clinigengroup.com/clinical-trial-services

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Why and How a Research Lab Should Embrace Research Quality Discussing the need for quality in medical research with each group of research colleagues I shared this with, each were aware of a worker whose use of a local technique was flawed. On discovery of the problem, several months’ work sometimes had to be discarded. My latest colleague offered support with a comment I didn’t expect – “try years”. Introduction The development of therapeutic products balances benefits and adverse consequences so research quality is required for the development of the new therapeutic. Astute use of research quality earlier can add to the value of intellectual property (IP), especially when the IP is subject to quality assurance due diligence (QADD). This is recognised in RQA publications supporting non-regulated research 1. Problems with the reliability and integrity of research have large, complex and lasting negative effects. Requirements for research quality are enforced in regulated research but there is no common agreement of when a quality system or quality assurance should begin. Outside regulated research, an approach that includes quality is traditionally considered unnecessary or even counter-productive. The aim of this article is to explore the reasons for a lab to apply research quality to improve their science, its reliability and productivity and to consider how to begin to apply research quality. Logical Reasons for Research Quality The complexity of research is greater than ever as we expand our understanding of life and the universe, even in a confined area of medical research. Further layers of growing complexity continue to develop in compliance areas of the research environment – animal and human research ethics, research grant governance, health and safety, protection of the environment and waste disposal, to name some. Clearly a system for each is impractical when a single lab system can provide workers with guidance approved by the lab’s and the organisation’s research leader(s) to both produce reliable research data and satisfy the requirements of multiple regulators simultaneously.Productivity may be the most significant benefit of research quality. The reduction in wasted research should be reflected by less research that needs to be repeated, corrected or retracted. Compelling Evidence of Problems with Research Reliability If logical reasons aren’t enough, there are sufficient compelling reports of problems in research to suggest the real magnitude of problems needs attention. Here are some of those reports.

38 Journal for Clinical Studies

Irreproducibility is a pervasive, systemic problem that has multiple direct and systems-level causes. These causes range from individual laboratory decisions, such as lack of an appropriate control for a particular experiment; to variability in journal publication requirements; to lack of consistent research quality systems. Fundamentally, irreproducibility stems from undefined variance in reagents, practices and assays between laboratories. Global Biological Standards Institute (GBSI) 2. GBSI’s comprehensive report, The Case for Standards in Life Science Research 2, found widespread problems. Begley 3 provides evidence for the commercial damage from lack of reproducibility: “scientific findings were confirmed in only 6 (11%) cases” of 53 papers deemed ‘landmark studies’. ‘Loss of confidence can affect research funding, delay discoveries and provide ammunition to attacks on proven science.’ Possibly more telling is that this didn’t seem to have sparked outrage. Is it possible the price of IP is discounted by an order of magnitude to allow for irreproducibility? Research quality would be a useful tool to demand and defend QADD audit and ask the full price for IP. Withdrawal of about 80 of Boldt’s publications has not stopped the damage from their previous influence on emergency department choice and use of blood volume fluids. The damage was quoted by Ian Roberts, a lead Cochrane review author, as “probably killing between 200 and 300 people every year in the UK” 4. It is ironic that academic research influential in the use of approved therapeutics isn’t subject to any of the regulation needed for market authority. “Royalty deal lower than hoped” is a headline (Australian Life Scientist, 14 th February 2012) no one wants. Powerful reasons exist, though, for under-reporting of this problem. But how do the owners and sellers of IP really know if shareholder value is maximised? Financial due diligence is well known but QADD may significantly write down the value of IP. QADD can be defined as: the process of analysis (usually by an investigative audit) prior to an acquisition of a technology, product or business or before entering into a partnership with a third party (the licensing sponsor) in order to determine the status of compliance with the applicable GxPs, the validity of processes, data and the inter-compatibility of regulatory and quality systems 1. Retractions, from various sources, also show problems continue. British media reporting, ca. 2002, of the mixVolume 9 Issue 1

Market Report up of cattle and sheep brains in bovine spongiform encephalopathy research was short of a retraction that may have had a greater effect on confidence in research data.

standards entities and professional associations. Some examples include:

Flaws in contemporary science harm society on multiple levels, within research and more generally. They damage the productivity of the work, wasting precious research funds, and demotivate scientists, some of whom move to more fulfilling endeavours. Loss of confidence can affect research funding, delay discoveries and provide ammunition to attacks on proven science. At worst, poorquality research can result in harm.

Doing the Right Thing The need for research quality exists because, one way or another, the investment in science isn’t reaching its potential and we shouldn’t simply react to the problems. Research quality should be adopted for the right reasons: •

• •

The public deserves the best use of and greatest productivity from taxpayer funding of research. Industry research should be a good use of shareholder funds High-quality research data generates greater prosperity, needed for a country to lift healthcare and for industry to stay in business Patients benefit sooner if research doesn’t need to be repeated in a ‘GLP’ facility IP is better protected if the research quality is demonstrably high.

Doing the right thing should be reason enough. Embrace a System Published systems are available from regulators,


• • • •

ISO 9001. The global system, can be applied to any activity ISO 17025. A system for testing and calibration laboratories OECD GLP. The management system for non-clinical safety testing RQA R&D. System for non-regulated R&D RQA GCLP. System for analysing samples as part of a clinical trial RQA QSW. Quality Systems Workbook is a tool for mapping the scope of a facility’s quality management system needs.

The value of these systems is that they provide a taxonomy that has broad understanding. This can have benefits for the training of new staff and for hosting future audits. For the lab worker, the taxonomy provides signposts to important information. Getting the System to Work Like any change process, the first essential is recognising the need and gaining the commitment from the team. Making the system beneficial is critical. Each team member should find what they need in the system. It works even better if everyone can see their contributions in the system. We need to be respectful of the sceptics and mindful their views are important and often correct. Remember The Private Cooper Hat (Quasar 129): I use the term ‘morale man’ to describe a soldier whose personality means that everyone around him will feed off his morale, high or low.

Journal for Clinical Studies 39

Market Report

Working to a SOP or lab method can save time in recording and permits the experimenter to be more observant of the experiment. Lab methods also assist with knowledge management, especially when key staff leave. Checklists can help beyond reducing errors. For example: equipment may require user specific adjustment – expensive loupes that need to be shared can have a method that includes each user’s inter-pupillary distance, making for rapid adjustment each time. There is much more than this but it is beyond this article. Fortunately it is within quality assurance skills. A final thought – it doesn’t have to be called a quality system. Some organisations don’t mention ‘Quality’, but they apply it rigorously. Conclusion A quality system, however named, is a powerful tool for lab productivity and research reliability. With new staff correctly inducted, the old habit of showing people what to do and then ‘letting them loose’ should disappear. The frequency and magnitude of flawed research should diminish.

A sceptic whose concerns are addressed may become a champion of the new system. With this in mind, start the discussion – RQA’s Quality Systems Workbook provides an excellent template for doing this.

References 1. Quality in Research Guidelines for working in nonregulated research RQA 2. The Case for Standards in Life Science Research Global Biological Standards Institute http://www. gbsi.org/gbsi-content/uploads/2015/10/The-Casefor-Standards.pd 3. Drug development: Raise standards for preclinical cancer research. C G Begley L M Ellis. Nature 2012 483, 531–533 4. Boldt: the great pretender. J Wise BMJ 2013;346:f1738 5. Quality Assurance in Pharmaceutical Due Diligence RQA

Many questions should flow from an early discussion. What is the scope of activities and what must we achieve? Are there risks in need of management? Are there improvements we can make? Are benchmarks available and applicable? Choose a framework to provide the taxonomy or skeleton for our system. Add flesh to the skeleton as needed. Be pragmatic – where available, use pre-existing material. Research plans or protocols approved by research ethics committees provide ready-made peer-reviewed research plans. Righteously ignore factors we believe can be ignored and record this, not to blame but to learn and justify. Where an expected benchmark exists, measure our success to prove it or point to the need for changes. A research institute that offers cell line testing generates either proof of good practice or defines the improvement needed. 40 Journal for Clinical Studies

Andrew King is Quality Assurance Manager for Q-Pharm, an early phase clinical trials unit. A biochemist keen on quantitative analysis, he began medical research in 1984. Development of a lab manual which morphed into a quality system led to quality assurance. He designed and defended at inspection, quality systems designed for GCP, GCLP, GLP and Research and Development; result of the last was a world’s first R&D accreditation. Volume 9 Issue 1


Journal for Clinical Studies 41


EU Paediatric Investigation Plans (PIPs) and Clinical Studies in Children It has been necessary to submit EU paediatric investigation plans (PIPs) for new drugs since 2007, unless the PIP is waived. The PIP lists paediatric clinical studies and other "measures". Without PIP, EU registration is blocked. PIP decisions are published on the EMA website. Individual PIPs may appear reasonable, but not when all PIPs in a disease are analysed. Paediatric studies for all new drugs are unfeasible where a disease is so rare in children that not enough patients exist. In hay fever, PIPs demand five-year double-blind placebocontrolled trials for ten thousand minors. PIPs reflect the belief that all persons under 18 years old need studies that mirror adult studies. Babies and infants do have immature organs, with potential over- or underdosing of drugs, but their organs mature. The PIP system equalises the legal end of childhood with a biological border and demands studies regardless of whether they are feasible or make medical sense. Two unfeasible multicentre international melanoma studies in adolescents had to be terminated in 2016. Institutional review boards/ ethics committees should not have approved them, should reject questionable PIP studies, and should suspend those ongoing. Since 2007, new drugs have needed a paediatric investigation plan (PIP) for EU registration. Without a PIP accepted by the European Medicines Agency (EMA)'s paediatric committee (PDCO), registration in adults and children is blocked 20,23,25. Paediatric legislation (PL) is a late reflex to modern pharmaceutical legislation (MPL) that followed the thalidomide catastrophe of 1959-1962, when thousands of children were born with malformed limbs 17,25. MPL and modern labels protect against wrong claims and quack medicines; it also led to broad off-label use in children, on which the American Academy of Paediatrics has a pragmatic view 15. Decades before, few efficient drugs existed. This changed dramatically since World War II. Numerous new drugs became available, initially welcomed by medical doctors, patients and the general public 17. A more critical view evolved thereafter with debates about profits of the chemical industry, which became pharmaceutical and is the life science industry today. After 1962, clinical trials were organised by companies; today most are outsourced to clinical research organisations (CROs). Drug development is complex, expensive, and controversial. MPL reflects that modern drugs can help, can have side-effects and need control. Modern labels guarantee that new compounds go through clinical and other testing before becoming broadly available. Regulatory authorities (RAs) became a third pillar in healthcare development, complementing the medical 42 Journal for Clinical Studies

profession as the oldest, and the pharmaceutical industry as the second, pillar. Soap operas and medical doctors'/ academia's selfperception characterise medical doctors as good, profitmaking as bad, sportsmen as nice, and managers as brutal and arrogant. Life shows that there are also bad doctors, good managers, and nasty sportsmen. While the pharmaceutical industry does not have the best image and new drugs are often accused of enhancing profit-making, for serious health challenges one key hope is better drugs. When MPL was introduced, clinical trials were usually performed in young males, often prisoners. Children were perceived as vulnerable, needing protection against research. MPL approved new drugs for adults. Shirkey's term of children as "therapeutic orphans" reflected two concerns: (1) legal trouble for the doctor in a court trial following some mishap if the used drug was not licensed in children; and (2) concern that children were not the main focus of drug development 33. Paediatric clinical pharmacology (PCP) showed that in babies and infants the organs are immature and more testing is needed to avoid under- or overdosing 18. US PL (PL) in 1997 defined children in legal terms. Rewards were offered to industry for "paediatric" studies in persons <16/18. The legal age boundary into adulthood thus became a biologic boundary. Antibiotics in adolescents work the same as in adults. Babies and infants differ much from adults in absorption, distribution, metabolism, excretion (ADME), but school children and adolescents much less so. The European Union (EU) PL (EUPL) ambitiously demands PIPs for rare diseases, exclusively paediatric diseases, biologics and vaccines. As of 19 th January 2017, 1420 PIP decisions are listed on the EMA website. The EMA reports as success an increase in the percentage of trials involving children compared to all trials, from 9.3% in 2006 to 11.5% in 2015 [13, Figure 2]. Do these trials make sense? Two PIP-triggered international studies in adolescents with metastasised melanoma had to be terminated in 2016 due to slow recruitment: a vemurafenib trial with 26 centres in the US, EU and Australia 5, and an ipilimumab trial with 30 centres in the US, EU and Mexico 21. In 2008, the EMA removed melanoma from the list of class waivers (no PIP required), claiming that enough patients exist for clinical trials 9,26,31. But the EMA's justification omitted that 75% of juvenile melanoma patients are cured by excision alone without systemic therapy. And the statistics it referred to grouped 15-19 years olds together, of whom 40% (18/19 years olds) are legally adults. The EMA calculations were wrong; this was published several times since 2014 26,29-31. Four more studies continue to recruit minors with melanoma and other solid tumours 2,3,4,34. And Volume 9 Issue 1

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Therapeutics more companies will initiate such trials because they want to register in the EU. Such studies are reported as "successes" in EMA reports 13, but in terms of medicine and ethics they are a disaster. PIPs demand 15 studies in paediatric multiple sclerosis (pMS), although the international clinical pMS group estimates that only 1-2 parallel pMS studies are possible worldwide 6,29. In all diseases that are rare in childhood, PIPs demand paediatric studies for every new drug in development, disregarding whether these studies are feasible. The mere number of studies makes them altogether unfeasible. IRBs/ECs are not yet aware of this challenge. They will learn. Ongoing trials are listed in www. clinicaltrials.gov and www.clinictrialsregister.eu. Once institutional review boards (IRBs) / ethics committees (ECs) become aware of the danger PIPs represent for children, they will look. One bizarre PIP consequence is that pharmaceutical companies/ CROs must protect children against the EMA and need help from IRBs/ECs. Questionable PIP-triggered trials are not limited to diseases rare in children. Hay fever is frequent. It can be treated and prevented by specific immunotherapy (SIT), described since 1911 28. In the decades thereafter, allergens were increasingly processed industrially, but continued in a niche apart from MPL. When in 2008 Germany introduced a law requiring registration of SIT allergen products as drugs, PIPs were mandatory. The German Paul-Ehrlich-Institut and the EMA jointly elaborated an allergen standard PIP 28, resulting in >100 PIPs demanding five-year double-blind placebocontrolled clinical studies in children and adolescents. Fifty-eight PIPs with such studies must be executed until 2031, or manufacturers will have to withdraw their products 7,28. While MPL was triggered worldwide by the thalidomide catastrophe, no catastrophe triggered USPL/EUPL. Shirkey's concerns met several streams of thoughts. Initial enthusiasm over new effictive drugs (antibiotics, steroids, beta-blockers) had given place to a more critical view of drug development. Pediatric clinical pharmacology (PCP) had shown the potential for over- and underdosing in babies and infants. Pharmacists were unhappy to pulverise tablets and reconstitute them into liquids: children below six years cannot swallow tablets. The USPL excludes rare diseases from mandatory requirements, limits paediatric requirements to the same indication as adults, and requests paediatric study plans late in development. EU regulators made bold claims, e.g. "lack of availability of appropriate medicines for children" 24 or "neglect of children in the development of effective and safe medicinal products" 20. But neonatology evolved with new drugs, mostly used off-label 22. Paediatric oncology (PO) evolved off-label by systematic testing of adult chemotherapy compounds in children with cancer 1,25. The USPL was the result of talks between PCP, clinicians, industry and the FDA. Its adaption by the EU aimed at outperforming the original. By removing all caveats, 44 Journal for Clinical Studies

it results in exaggerated demands for clinical studies in everybody under 18. Instead of outperforming the US, EMA/PDCO have created a situation where, despite obvious failings, the chosen strategy is intensification, not moderation. Revoking the melanoma class waiver in 2008 was a mistake. In 2015, class waivers for even rarer diseases were revoked, including liver or kidney cancer, both extremely rare in minors 11. This will not bring "better medicines for children" 12. Few will object to a statement like "Children and infants deserve the same right to treatment as adults" 35. But this was written >30 years after introduction of MPL in the UK. Times had changed. Children, women, non-classic sexual orientation and minorities were now more respected. MPL had introduced minimal control over compounds that before could become broadly available with potentially catastrophic consequences. Equalisation of legal age definition of adulthood with biological maturation reflects shortsightedness at this interface of medicine and law and leads to a medical disaster. Eventually, this needs tackling from two sides: (1) adolescents whose bodies become adult before legal adulthood, and (2) babies and infants. Expanding drug labels from adults to adolescents might require a separate law to remove fear from medical doctors when they prescribe off-label. Methods of modelling & simulation (M&S), followed by PK/PD dose confirmation in small paediatric trials, have advanced. Automatic demand for separate safety & efficacy trials in 2-17 years olds are not based on science. In infants and babies, not every new drug developed for adult use needs paediatric testing. There is, e.g., no doubt about the efficacy of antibiotics. There are the questions of dosing and safety. But most PIP-demanded safety & efficacy (S&E) studies follow a rigid regulatory tunnel view logic. In PO young patients need other compounds than adults. Some initiatives, e.g. the US Creating Hope act, facilitate truly new drug development for rare paediatric and adult rare diseases. We need more such facilitation 27. Institutional review boards IRBs/ ECs should reject questionable PIP-demanded paediatric studies and suspend those ongoing. References 1.

Adamson PC. Improving the outcome for children with cancer: development of targeted new agents. CA Cancer J Clin. 2015;65: 212â&#x20AC;&#x201C; 220. www.ncbi.nlm.nih.gov/pubmed/25754421


A Phase I/II, Multicenter, Open-Label, Dose-Escalation Study Of The Safety And Pharmacokinetics Of Cobimetinib In Pediatric And Young Adult Patients With Previously Treated Solid Tumors. https://www. clinicaltrialsregister.eu/ctr-search/search?query=2014-004685-25 Accessed 20JAN2017


A Study of Pembrolizumab (MK-3475) in Pediatric Participants With Advanced Melanoma or Advanced, Relapsed, or Refractory PD-L1Positive Solid Tumors or Lymphoma (MK-3475-051/KEYNOTE-051). https://clinicaltrials.gov/ct2/show/NCT02332668


A Study to Determine Safety, Tolerability and Pharmacokinetics of Oral Dabrafenib In Children and Adolescent Subjects. https://clinicaltrials. gov/ct2/show/NCT01677741

Volume 9 Issue 1

Therapeutics 5.

BRIM-P. A study of Vemurafenib in pediatric patients with stage IIIC or stage IV melanoma harboring BRAFV600 mutations. https:// clinicaltrials.gov/ct2/show/NCT01519323


Chitnis T, Tenembaum S, Banwell B, Krupp L, Pohl D, Rostasy K et al. Consensus statement: evaluation of new and existing therapeutics for pediatric multiple sclerosis. Mult Scler. 2012 Jan;18(1):116-27 http:// www.emsp.org/wp-content/uploads/2015/11/Chitnis-IPMSSG-MSJ.pdf


Eichler I, Sala Soriano E. Close collaboration between academia, industry and drug regulators is required in the development of allergen products for specific immunotherapy in children. Allergy 2011: 66: 999–1004. http://onlinelibrary.wiley.com/doi/10.1111/j.1398-9995.2011.02582.x/ epdf Accessed 20JAN2017


EMA website. www.ema.europa.eu Accessed 20JAN2017


EMA 2008. EMA class waivers, http://www.ema.europa.eu/ema/ index.jsp?curl=pages/regulation/general/general_content_000036. jsp&mid=WC0b01ac0580925cca. Accessed 20JAN2017

10. EMA 2010. European Medicines Agency decision P/345/2010 of 20 December 2010 on a class waiver on condition(s) in accordance with Regulation (EC) No 1901/2006 of the European Parliament and of the Council. http://www.ema.europa.eu/docs/en_GB/document_library/ Other/2009/11/WC500011500.pdf. Accessed 20JAN2017 11. EMA 2015. European Medicines Agency decision CW/0001/2015 of 23 July 2015 on class waivers, in accordance with Regulation (EC) No 1901/2006 of the European Parliament and of the Council. www. ema.europa.eu/docs/en_GB/document_library/Other/2015/07/ WC500190385.pdf 12. E MA 2015. Better Medicines for Children. www.ema.europa.eu/docs/ en_GB/document_library/Leaflet/2009/12/WC500026493.pdf 13. EMA2016. 10-year Report to the European Commission. General report on the experience acquired as a result of the application of the Paediatric Regulation. http://ec.europa.eu/health//sites/health/files/ files/paediatrics/2016_pc_report_2017/ema_10_year_report_for_ consultation.pdf. Accessed 20JAN2017 14. FDA. Best Pharmaceuticals for Children Act and Pediatric Research Equity Act July 2016. Status Report to Congress. www.fda.gov/downloads/ S c i e n c e Re s e a r c h / S p e c i a l To p i c s / Pe d i a t r i c T h e ra p e u t i c s Re s e a r c h / UCM509815.pdf 15. Frattarelli DA, Galinkin JL, Green TP, Johnson TD, Neville KA, Paul IM, et al. Off-label Use of Drugs in Children. Pediatrics 2014, 133 (3), 563-567 Link: http://pediatrics.aappublications.org/content/ pediatrics/133/3/563.full.pdf

benefits and perspectives. Italian Journal of Pediatrics 2010, 36:56 Link: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2933611/pdf/18247288-36-56.pdf 25. Rose K. Pediatric Pharmaceutical Legislation in the USA and EU and Their Impact on Adult and Pediatric Drug Development. In: Bar-Shalom D & Rose K: Pediatric Formulations – A Roadmap, AAPS & Springer, 2014: chapter 28, pp. 405-420 26. Rose K. European Union Pediatric Legislation Jeopardizes Worldwide, Timely Future Advances in the Care of Children With Cancer. Clinical Therapeutics 2014, 36 (2), 163-177 http://www.clinicaltherapeutics. com/article/S0149-2918(14)00018-6/pdf 27. Rose K. New Drugs For Rare Diseases in Children. Clin Ther 2017, in press 28. Rose K & Kopp MV. Pediatric investigation plans for specific immunotherapy: Questionable contributions to childhood health. Pediatr Allergy Immunol. 2015 Dec;26(8):695-701 29. Rose K & Mueller T. Children with Multiple Sclerosis Should Not Become Therapeutic Hostages. Ther Adv Neurol Disord 2016, Vol. 9(5) 389–395 http://tan.sagepub.com/cgi/reprint/9/5/389. pdf?ijkey=QMcFYoLcpF0m8Pn&keytype=finite 30. Rose K & Walson PD. The contributions of the European Medicines Agency and its pediatric committee to the fight against childhood leukemia. Risk Manag Healthc Policy. 2015 Nov 5;8:185-205. https:// www.dovepress.com/the-contributions-of-the-european-medicinesagency-and-its-pediatric-c-peer-reviewed-fulltext-article-RMHP 31. Rose K & Walson PD. Do the European Medicines Agency (EMA) Decisions Hurt Pediatric Melanoma Patients? Clin Ther 2017, in press 32. Rose K & Senn S. Drug development: EU paediatric legislation, the European Medicines Agency and its Paediatric Committee—adolescents’ melanoma as a paradigm. Pharmaceutical Statistics 2014; 13(4): 211213 33. Shirkey H. Therapeutic Orphans. Pediatrics 1999 Sep;104(3 Pt 2):583584 http://pediatrics.aappublications.org/content/pediatrics/104/ Supplement_3/583.full.pdf 34. To Find a Safe Dose and Show Early Clinical Activity of Weekly Nabpaclitaxel in Pediatric Patients With Recurrent/ Refractory Solid Tumors https://clinicaltrials.gov/ct2/show/NCT01962103 35. Turner S, Nunn AJ, Fielding K, Choonara I. Adverse drug reactions to unlicensed and off-label drugs on paediatric wards. Acta Paediatr 1999, 88: 965-968

16. Gonzalez D, Melloni C, Yogev R, et al. Use of opportunistic clinical data and a population pharmacokinetic model to support dosing of clindamycin for premature infants to adolescents. Clin Pharmacol Ther. 2014 Oct;96(4):429-37. https://www.ncbi.nlm.nih.gov/pmc/articles/ PMC4862454/pdf/zac2888.pdf 17. Hilts PJ. Protecting America's Health: The FDA, Business, and One Hundred Years of Regulation. University of North Carolina Press 2004 18. Kearns GL, Abdel-Rahman SM, Alander SW, Blowey DL, Leeder JS & Kauffman, RE. Developmental Pharmacology - Drug Disposition, Action, and Therapy in Infants and Children. N Engl J Med. 2003;349(12):11571167. 19. Laughon MM, Benjamin DK Jr, Capparelli EV, et al. Innovative clinical trial design for pediatric therapeutics. Expert Rev Clin Pharmacol. 2011 Sep;4(5):643-52 https://www.ncbi.nlm.nih.gov/pmc/articles/ PMC3184526/ 20. Mentzer D. Progress review of the European Paediatric Regulatory Framework after six years of implementation. Int J Pharm. 2014 Aug 5;469(2):240-3. 21. Phase 2 study of Ipilimumab in children and adolescents (12 to <18 Years) with previously treated or untreated, unresectable stage III or stage lV malignant melanoma. https://clinicaltrials.gov/ct2/ show/ NCT01696045 22. Philip AG. The Evolution of Neonatology. Pediatr Res. 2005 Oct;58(4):799815. http://www.nature.com/pr/journal/v58/n4/pdf/pr2005743a.pdf 23. Regulation (EC) No 1901/2006 Of The European Parliament And Of The Council of 12 December 2006 on medicinal products for paediatric use and amending Regulation (EEC) No 1768/92, Directive 2001/20/EC, Directive 2001/83/EC and Regulation (EC) No 726/2004. Official Journal of the European Union, 27.12.2006, L 378/1 - L 278/19 http://ec.europa. eu/health/files/eudralex/vol-1/reg_2006_1901/reg_2006_1901_en.pdf 24. Rocchi F, Paolucci P, Ceci A, Rossi P. The European paediatric legislation: www.jforcs.com

Klaus Rose studied psychology, Latin languages and medicine. After postgraduate clinical training in Germany and England he joined pharmaceutical industry. He was Global Head Pediatrics Novartis 2001-2005 and Global Head Pediatrics Roche 2005-2009. Since 2011 he is independent. He advises on pediatric drug development, speaks at conferences, and publishes. He co-edited three textbooks in the area of pediatric drug development. Email: klaus.rose@klausrose.net. Journal for Clinical Studies 45

Therapeutics Refining Clinical Diagnosis of Progressive Supranuclear Palsy: Implications for Disease Modification Trials The importance of ensuring an accurate diagnosis of progressive supranuclear palsy (PSP) is critical for the development of effective disease-modifying therapies that are specifically directed at the reduction of tau aggregation in the pathogenesis of this disorder. This rare, (incidence of 0.3-1.1/100.000/year; prevalence of 1.3-6.4/100.000) and devastating neurodegenerative disorder presents as an akinetic-rigid syndrome with a variety of signs and symptoms, including ocular motor dysfunction, postural instability, frontal lobe and bulbar dysfunction. The manifold symptoms and broad phenotypic variability of PSP may in part account for its diagnostic challenges, particularly in the early stages of the disease. This review will delineate various diagnostic schema in defining PSP with an overall aim of improving diagnostic accuracy in clinical trials, resulting in decreased patient heterogeneity with accompanying improvement of signal detection in the assessment of putative therapeutic agents. PSP is considered a tauopathy, a class of neurodegenerative diseases characterised by the pathological aggregation of the microtubule-associated protein known as tau in the brain. Tau protein binds to microtubules, and plays an important role in neuronal cytoskeletal stability. The hyperphosphorylation of tau results in tau protein aggregates, sometimes referred to as paired helical filaments. Alternative splicing of exons 2, 3, and 10 of the tau gene generates six tau isoforms. The inclusion or exclusion of exon 10 produces isoforms with four (4R) or three (3R) microtubule binding sites. Normal brains have similar levels of 4R and 3R; however, in PSP, 4R dominates and PSP is often referred to as a 4R tauopathy. To date, disease-modifying trials in PSP have sought to demonstrate neuroprotective effects primarily by decreasing tau pathology through various mechanisms that reduce tau phosphorylation and/or increase microtubule stability. Typical neuropathological signs of PSP include excessive intra-axonal accumulation of phosphorylated tau protein in the basal ganglia and brain stem producing neurofibrillary tangles (NFT) which spread transynaptically throughout the brain, resulting in neuronal loss and gliosis in a manner that seems to correlate with the clinical progression of the disease. The neuropathological criterion for diagnosis of definite PSP requires a high presence of NFT in at least three of the following brain areas: striatum, oculomotor complex, medulla, or dentate nucleus, and unfortunately requires sampling cerebral tissue in order to ensure accurate diagnosis. Contrasting with this distinctive neuropathological profile, the clinical presentation of PSP is quite heterogeneous and is associated with pronounced variability in regional distribution, severity of abnormal tau accumulation and neuronal loss associated with different stages of disease progression. 46 Journal for Clinical Studies

The characteristic pattern of signs and symptoms of PSP can be quite dissimilar from patient to patient. The most frequent initial symptom of PSP is a loss of balance while walking (i.e. unexplained falls or a stiffness and awkwardness in gait), followed by personality changes, bulbar symptoms, and visual problems. PSP patients typically present with a peculiar akinetic-rigid motor disorder that in most cases differs markedly from that observed in Parkinson’s disease (PD). PSP symptoms tend to be more prominent in axial segments, leaving limb function relatively preserved, and unlike the onset of symptoms in PD, postural stability is compromised early on in the course of illness. Although individuals with PD can benefit from levodopa, patients with the classic PSP phenotype called Richardson’s Syndrome (PSPRS, which accounts for approximately 55% of all PSP) 1 respond marginally and only briefly to levodopa therapy. Auspiciously, this lack of motoric response to dopaminergic drugs can be supportive in differentiating the PSP-RS phenotype and PD. This is important as PSP patients are often misdiagnosed for several years as having PD, and in the absence of diagnostic biomarkers, this misdiagnosis often goes uncorrected until relatively late in the disease course. This is particularly problematic as patients with PSP-RS have the most rapid clinical decline trajectory and may become dependent on caregivers within three to four years from the onset. Regrettably, patients with PSPRS classically have a survival rate of only approximately seven years. Other clinical subtypes of PSP include PSP-parkinsonism (PSP-P) and PSP-pure akinesia with gait freezing (PSPPAGF) which typically have a more benign course, and a slower rate of disease progression that PSP-RS 2, with a sur¬vival period of at least a decade or more. Both of these subtypes have an overall tau burden that is comparatively less than that seen in PSP-RS with the distribution of abnormal tau being relatively restricted to the brain stem. As such, the phenotypes of PSP-P and PSP-PAGF are sometimes referred to as the ‘brain stem’ variants of PSP, as opposed to the more ‘cor¬tical’ variants which present with predominantly cor¬tical features. These more cortical clinical subtypes include the behavioural variant of frontotem¬poral dementia (PSP-bvFTD) which accounts for 5% of all PSP; PSP-corticobasal syndrome (PSP-CBS), PSP- and PSP-progressive non-fluent aphasia (PSP-PNFA) which both account for 1% of all PSP. Finally, a PSP-cerebellar subtype accounts for less than <1% with the remaining percentage made up of a combination of these subtypes or still unrecognised forms of PSP. 1 A study of autopsy-confirmed PSP cases 3 casts doubt on the above clinical proportions and supports an even greater degree of clinical heterogeneity than has been clinically appreciated to date. The post mortem data Volume 9 Issue 1

Therapeutics suggest that only 24% of the cases present as pure PSPRS, with a large proportion of patients having overlapping neuropathological features of several predefined phenotypes, (PSP-P; PSP-CGS; PSP-bvFTD) or features not fitting proposed classification criteria (atypical) for PSP phenotypes. Importantly, most phenotypes were rare in their pure form and almost 40% of patients could not be classified into any one specific phenotype, most often due to an absence of specific clinical features but also due to the presence of important exclusion criteria. Adding to the confounding nature of an accurate diagnosis, is the fact that mixed PSP pathologies may be found in patients with late-adult onset neurodegenerative diseases. In a contemporary study evaluating 64 cases of pathologically confirmed PSP, 36% also had concomitant Alzheimer’s disease, 20% PD, 1% dementia with Lewy bodies, 44% argyrophilic grains, 52% cerebral white matter rarefaction and 25% cerebral amyloid angiography. 4 Given this overlap of concomitant illnesses, the numerous clinical phenotypes and large clinical heterogeneity of PSP, it is easy to appreciate that one of the greatest challenges to current trials designed to assess PSP treatments is the accurate diagnosis and inclusion of an appropriate PSP patient sample. In an effort to improve diagnostic accuracy, the National Institute of Neurological Disorders and Stroke and the Society for PSP (NINDS-SPSP) criteria have been proposed for use in clinical trials. 5 These criteria define three diagnostic categories of increasing certainty: possible, probable, and definite. The diagnosis of possible and probable PSP depends primarily on the presence of specific clinical features (gradual progressive disorder with an age of onset over 40 years, falls within the first year, signs of vertical supranuclear gaze palsy or slowing of verti¬cal saccades), as well as on meeting salient exclusion criteria (i.e. cortical sensory loss; psychosis not related to dopaminergic therapy). A definite diagnosis requires a typical PSP neuropathological lesion distribution pattern with cellular inclusions that are tau-positive. Although these diagnostic criteria have been used widely in the research community, there is still disagreement as to their value. Validation of these criteria in independent populations of patients demonstrated a high positive predictive value, albeit low sensitivity particularly during the early course of the disease. 6 Specifically, the NINDS-SPSP criteria appear to be adequate at clinically defining the PSP-RS phenotype, whereas all other variable phenotypic presentations of PSP, especially those described after the development of these criteria (1996), have not been characterised in a reliable manner. Further, it has been estimated that the NINDS-SPSP criteria accurately detect only 50–75% of PSP-RS patients within three years of disease onset. Although evidencebased revised clinical criteria for diagnosis of PSP are currently being developed by the Movement Disorders Society (MDS) PSP research group, there are currently no accepted diagnostic guidelines for the clinical diagnosis of other pheno¬typic presentations of PSP available to clinical triallists. www.jforcs.com

Given this lack of diagnostic accuracy and the broad clinical heterogeneity of PSP, both diagnostic and predictive biomarkers such as magnetic resonance imaging (MRI) and tau imaging will undoubtedly play an increasingly important role for inclusion criteria in clinical trials assessing disease-modifying drugs. Ultimately the biomarkers with the best utility are likely to be some combination of imaging markers designed to exclude specific pathologies (e.g. Alzheimer’s or PD) and to define the presence of specific 4R tauopathy. For example, volumetric MRI imaging may show midbrain atrophy, a finding that differentiates patients with PSP from healthy controls and those with PD and other disorders with symptoms of atypical Parkinsonism. Interestingly, the midbrain atrophy seen on mid-sagittal scans characteristically resembles a penguin or hummingbird silhouette in up to two-thirds of patients with PSPRS, but unfortunately, can also be seen in patients with multisystem atrophy (MSA) and spinocerebellar ataxia (SCA), therefore confounding differential diagnosis. 7 Diffusion-weighted imaging (DWI) has shown significantly higher rADC (regional apparent diffusion coefficient) values in both the putamen and globus pallidus in patients with PSP than in those with PD, but this pattern can also be seen in patients with MSA. 8 Diffusion tensor imaging (DTI) studies have suggested that white matter tract degeneration especially in the superior cerebellar peduncles and superior longitudinal fas¬ciculus is characteristic of patients with PSP-RS. 9 Focal midbrain hypometabolism on fluorodeox-yglucose (FDG)-positron emission tomography (PET) has also been consistently identified in patients with PSP-RS. 10 This is especially important as PET tau imaging agents have shown considerable promise in both differentiating PSP from other Parkinsonian conditions and other subtypes of PSP, and in serving as a possible marker of disease progression. 11 There are several tau selective tracers in development, but the most widely utilised to date are [18F]AV-1451, a series of [18F]-labelled arylquinoline derivatives ([18F]-THK) compounds, and 2-((1E,3E)-4-(6(11C-methylamino)pyridin-3-yl)buta-1,3-dienyl) benzo[d] thiazol-6-ol ([11C]-PBB3). A better understanding of what targets these tau imaging agents are actually binding to, as well as the best reference region and analyses methods, is urgently required to optimise their use in disease-modifying clinical trials. In one of the first registration studies of a diseasemodification agent, as well as one of the largest Phase II/III studies PSP studies conducted to date, 313 PSP-RS patients were randomised in a double-blind fashion to Davunetide 30 mg or placebo administered intranasally twice daily for 52 weeks. 12 Patients all met modified National Neuroprotection in Parkinson’s Plus (NNIPPS) criteria for possible or probable PSP and were assessed via co-primary endpoints of change from baseline in PSP Rating Scale (PSPRS) and Schwab and England activities of daily living (SEADL) scale which measure overall disability/function and the ability of patients to function independently, respectively. Approximately 78% of Journal for Clinical Studies 47

Therapeutics the patients completed this trial which concluded that Davunetide was well tolerated but regrettably not an effective treatment for PSP. 7 Despite the lack of positive findings, this study suggested that clinical trials of disease-modifying therapy are indeed feasible in PSP and should be pursued, utilising other promising tau-directed therapies. Importantly, this trial garnered essential information regarding the utility of various outcome measures and data on potential predictive and surrogate biomarkers for use in future PSP disease-modification trials. Boxer and team 12 reported a mean annual rate of decline on the PSP rating scale (PSPRS which rates overall PSP symptoms 1) of 11.0 (9.9-12.3) points and a survival rate of approximately 93.1% over approximately one year; which is slightly higher than predicted from the PSPRS validation study (86.9%) based on the mean baseline PSPRS score of 40. 12 For the co-primary endpoint, the SEADL, an annual rate of decline of 17 per cent 15-19 was shown. This information can be used to determine clinical relevance for slope differences between treatment groups in future disease-modification trials. Boxer et al. 12 also reported a mean annual brain atrophy rate of 1%; a mean annual ventricular volume expansion rate of approximately 9.4%; a midbrain atrophy rate of 3.6%; and a 7.3% annual rate of superior cerebellar peduncle atrophy â&#x20AC;&#x201C; all useful for future disease-modification studies powered on tissue sparing/salvage. A more recent review of this data, which also included numerous exploratory cognitive assessments and CSF measures (in a subset of patients) in addition to volumetric MRI measurements, reported that shorter PSP disease duration, more severe depression, and poorer cognitive performance overall at baseline were all associated with faster progression of PSP symptoms on the PSPRS for those 243 patients who completed the 52-week trial. 13 When those patients who dropped out of the study were included in the analyses, these same cognitive measures of executive function and activities of daily living had a significant effect on PSPRS trajectory, further supporting that baseline cognitive status and depression influence the rate of disease progression in PSP-RS. Conversely, patients with longer disease duration at baseline had a relatively slower rate of progression and thus would require a longer treatment duration in order to show significant changes associated with treatment. This slower rate of decline might be attributed to the inclusion of patients who had variant forms of PSP such as PAGF or PSP-P preceding their progression to Richardson's syndrome. Of note is that multivariate models that included baseline clinical and MR imaging variables were no better at explaining variance in annual PSPRS progression than simple univariate models of individual variables. These data suggest that patient samples could be readily enriched for more rapid progression in diseasemodification trials using a few crucial baseline variables and these researchers identified cut-off values that could be used to identify patients with a more rapid or 48 Journal for Clinical Studies

Volume 9 Issue 1

Therapeutics predictable disease progression.. In summary, the above-mentioned studies suggest that the diagnostic criteria for PSP are suitable, if not optimal, for recruiting mild to moderately impaired PSP patients into multicentre trials, and that once enrolled, such patients follow a highly predictable rate of clinicaland biomarker-related decline that can be used to power future trials of disease-modifying drugs in a reliable manner. Furthermore, these patient populations can be enriched on progression in order to save time and money in disease-modifying trials which are relatively lengthy and have larger sample sizes than comparative trials of symptomatic drugs. Finally, it is possible that, like many of the failed disease-modifying trials in Alzheimer’s disease, it may have been too late in the course of the PSP to show any reliable and consistent changes in symptomatology associated with disease-modifying treatments such as Davunetide. Rather, it has been proposed that it may be better to evaluate potential disease-modifying therapies in PSP patients much earlier in the disease process and researchers have emphasised the value of PET tau imaging as a promising biomarker that may not only help to demonstrate target engagement but also permit identification of PSP patients at earlier stages of the disease when tau directed therapeutics are more likely to be effective. 13 References 1. Golbe L, Ohman-Strickland PA. A clinical rating scale for progressive supranuclear palsy. Brain; 2007; 130(Pt 6):1552-65 2. Williams DR, Holton JL, Strand C, Pittman A, de Silva R, Lees AJ et al. Pathological tau burden and distribution dis¬tinguishes progressive supranuclear palsy-parkinsonism from Richardson’s syndrome. Brain 2007;130(Pt 6):1566-1576. 3. Respondek G, Stamelou, M, Kurz C et al. The phenotypic spectrum of progressive supranuclear palsy: a retrospective multicentre study of 100 definite cases. Mov Disord 2014;29:1758-1766. 4. Dugger BN, Adler CH, Shill HA et al. Concomitant pathologies among a spectrum of parkinsonian disorders. Parkinsonism Relat Disord 2014;20:525529 5. Litvan I, Agid Y, Calne D et al. Clinical research criteria for the diagnosis of progressive supranuclear palsy (Steele-Richardson-Olszewski syndrome): Report of the NINDS-SPSP International Workshop. Neurology 1996;47:1-9. 6. Osaki Y, Ben-Shlomo Y, Lees AJ et al. Accuracy of clinical diagnosis of progressive supranuclear palsy. Mov Disord 2004;19:181–9. 7. Kato N, Arai K, Hattori T. Study of the rostral midbrain atrophy in progressive supranuclear palsy. J Neurol Sci 2003;210:57–60. 8. Seppi K, Schocke MFH, Esterhammer R et al. DWI discriminates PSP from PD, but not from the Parkinson variant of multiple system atrophy. Neurology 2003;60:922 –7. www.jforcs.com

9. Whitwell JL, Avula R, Master A et al. Disrupted thalamocortical connectivity in PSP: a resting-state fMRI, DTI, and VBM study. Parkin¬sonism Relat Disord 2011;17:599-605. 10. Brooks DJ, Ibanez V, Sawle GV et al. Differing patterns of striatal 18-F-Dopa uptake in Parkinson`s disease, multiple system atrophy and progressive supranuclear palsy. Ann Neurol 1990 ;28:547–55. 11. Villemagne VL, Fodero-Tavoletti MT, Masters CL, Rowe CC. Tau imaging: early progress and future directions. Lancet Neurol 2015; 14(1):114-124. 12. Boxer AL, Lang AE, Grossman M et al. Davunetide for Progressive Supranuclear Palsy: a multicenter, randomized, double-blind, placebo controlled trial. Lancet Neurol. 2014; 13(7): 676–685 13. Bang J, Lobach IV, Lang AE et al. Predicting disease progression in progressive supranuclear palsy in multicenter clinical trials. Parkinsonism Relat Disord. 2016; 28:41-8.

Tomislav Babic, MD, PhD is Vice President of Medical and Scientific Affairs/Neuroscience Franchise at Worldwide Clinical Trials Inc. Dr Babic is a board-certified neurologist and clinical pharmacologist, with particular interest in drug development for Alzheimer’s disease, Parkinson’s, and MS. He is the author of more than 60 peer-reviewed articles and books and has been integral to the development of many approved drugs for PD. His expertise has been widely noted in neurodegenerative disorders in both industry and academia for the past 25 years. Email: tomislav.babic@worldwide.com Henry J. Riordan, Ph.D. is Executive Vice President of Medical and Scientific Affairs and Global Lead for Neuroscience at Worldwide Clinical Trials. Dr Riordan has been involved in the assessment, treatment and investigation of various CNS drugs and disorders in both industry and academia for the past 20 years. Dr Riordan specialises in clinical trials methodology and has advanced training in biostatistics, experimental design, neurophysiology, neuroimaging and clinical neuropsychology. He has over 100 publications, including co-authoring two books focusing on innovative CNS clinical trials methodology. Email: henry.riordan@worldwide.com Journal for Clinical Studies 49

IT & Logistics Latest IRT Systems Accelerate Trial Progress and Support Patient Safety IRT systems are commonly credited with helping to ensure that the right drug gets to the right patient at the right time. This digital side of the supply chain supports drug distribution activities as well as site-level patient interactions. As IRTs have grown more sophisticated in recent years, their automated functions can actually accelerate the drug’s journey to market and improve patient safety. These less-known benefits are especially timely as clinical trials are growing more complex (1)— often involving more patients, more sites, and more countries. Sponsor companies can often manage supplies and drug assignments for very small clinical trials involving a handful of patients without an IRT system. Few, however, would ever attempt to do so for global trials and/or those involving hundreds, much less thousands of patients. The value of IRT systems is well known in projecting patient demand, managing product expirations, preventing stock-outs, automating drug assignments, and protecting blinded information. Less recognised, though, is the fact that the newer, more sophisticated IRT systems have added features and functionality that address the two overarching goals that sponsors have for their trials: ensuring patient safety and speeding time to approval. Ensuring Patient Safety Minimising Human Error IRT systems are the backbone of medication-related functions within a trial, encompassing: • • • • • • • •

Patient screening/rescreening; Run-in phase registration; Screen failure reporting; Randomisation/enrolment; End of study reporting; Unblinding; Medication reorder/replacement; and Tracking the status of medications.

IRT systems are validated against the sponsor’s requirements, guiding end users along a pre-determined workflow in each of these functions, allowing them to simply follow the on-screen steps as they complete transactions. This prevents users from skipping necessary steps or performing them out of order—issues that could compromise both patient safety and the integrity of study data. Modern IRT systems also have built-in business logic that is defined by the needs of the particular trial, but in general, it is designed to minimise the amount of manual intervention in study-critical points such as randomisation and dispensing. For example, an IRT’s business logic can: •

Perform dosing calculations, which helps take

50 Journal for Clinical Studies

the onus off of site pharmacists to ensure that doses are administered in the correct volume and concentration; Prevent data from being entered that falls outside of acceptable parameters or that is in the wrong format; and Ensure that critical fields are completed so that a patient’s participation need not be invalidated for lack of critical information.

This business logic can be especially important in trials involving hundreds of sites across multiple countries. The IRT, if designed well, can provide an intuitive interface that encourages consistency while decreasing the need for extensive, costly, and time-consuming site training. While an IRT cannot prevent all human errors in study administration (someone could still enter the wrong information or do something incorrect with the information the system provides), it can minimise the opportunity for human error and increase the detectability of any errors made. In the event that erroneous data did make its way into the system, the IRT provides an audit trail of any data corrections performed. Monitoring Adverse Events Traditionally, sponsor companies have captured reports of adverse events (AEs) through the electronic case report form (eCRF) that investigators complete during patient visits, and the details are collected via the electronic data capture (EDC) system. What many progressive companies are now discovering is that all of the same functionality within the IRT that is used to monitor and control trial progress towards milestones (such as screening, enrolment, and randomisations) can be leveraged to monitor AEs. When a patient discontinues trial participation, the investigator records this fact in the IRT, and increasingly, sponsors are requiring that investigators use the available fields to indicate the reason for discontinuation. Often the reason is related to an AE. Similarly, any unblinding events (which are almost always indicative of AEs) are recorded in the IRT. Very likely, the notification of the unblinding event would be received before the details in a completed eCRF. The IRT supports near real-time monitoring (in the best systems, data are refreshed multiple times a day), which is important both in terms of immediately identifying events that may be relevant to patient safety and for complying with regulators’ timelines. (The US Food and Drug Administration (FDA) requires notification within 15 calendar days for AEs and within seven calendar days for serious AEs.) And, rather than having to go in search of the Volume 9 Issue 1

IT & Logistics information, trial monitors can be automatically notified when the system registers a patient discontinuation or an unblinding event, or when the number of such instances reaches a pre-defined threshold. Sophisticated IRTs can accommodate “transaction-based alerts” that are set to notify trial monitors based on certain triggers. Thresholds can be defined by site, country, study, or treatment so that study monitors can initiate investigations when and where needed. Speeding Time to Approval Accelerated Data Submission Some IRTs are capable of providing information in the specific format needed for submission to regulators. They convert the database through a valid transformation process into any structure required, such as what is outlined in the Study Data Tabulation Model (SDTM), for example. (The SDTM is part of the Clinical Data Acquisition Standards Harmonization (CDASH) Standard.) This means that when the study closes, the data captured in the IRT are ready to go, without needing to be reformatted— which can be a protracted process. Another benefit of newer IRTs is that they allow for interim analyses of safety and efficacy at any point in the course of the trial; the data export is always ready. This is particularly helpful for products receiving breakthrough therapy or fast track designations in which the FDA conducts rolling reviews of marketing application materials. Automated Accountability, Reconciliation, Returns, and Destruction The trial administration process can also be shortened when IRT systems extend to accounting for supplies from their manufacture until they are either consumed by the patient or destroyed. Regulatory agencies around the world mandate that sponsors be able to prove that study medications were administered only to the correct patients and according to the protocol. As drugs move through the trial, the following documentation must be kept: •

• •

Site personnel must maintain logs when they receive drugs from depots, dispense them to patients, or accept them as returns from patients; Clinical monitors must verify that the logs for all received, utilised, and returned drugs at each site match the physical quantities and status of materials; Monitors must maintain a record of any returned drugs to a collection destination; and Sponsors must receive a certificate that identifies and quantifies any drugs that were shipped to a designated destruction facility and destroyed.

Any discrepancies identified must be investigated, explained, and resolved in order to fulfill regulatory requirements and support the study findings. When sponsors rely on a paper-based system to track the www.jforcs.com

Poor Resupply Strategy Leads to Patient Loss… Potential Trial Delays The sponsor of a Phase III trial spanning more than 700 sites in 49 countries was experiencing a high rate of “insufficient product alerts” in the company’s IRT system. In one year, 838 patients— between two and three a day—were being turned away at sites because there wasn’t enough of the right dose strength in the right country at the right time to meet patient demand. This situation had the potential to extend the timeframe of the trial significantly. The issue was that the resupply strategy was not synched with actual patient demand, and frustration was mounting at clinical sites as well as within the sponsor’s operations team. An inordinate number of patients were leaving the study and enrolling in competing trials, of which there were many. The solution was to prepare a new forecast and resupply strategy based on real-time updates on patient enrolment, product usage, and expiry dates. Over time, as the sponsor’s product production “caught up” with the more accurate forecast, the rate of insufficient product alerts dropped sharply from its high of 4.7 per cent to a reasonable 0.2 per cent, patient discontinuations decreased dramatically, and complaint calls from sites dropped in equal measure. disposition of supplies, they typically have to contend with disparate and/or duplicate entries. And, because the information is recorded in many formats, it can be difficult to consolidate for reporting and analysis. Often, study teams spend as much time verifying and correcting logs as it took to perform the actual accountability and reconciliation functions in the first place. An automated system that is an extension of the IRT, in contrast, reduces errors through logic checks and using drop-down selections rather than free text, notifies monitors of discrepancies as they happen, supports real-time queries as to the status of drugs, and allows for reporting to auditors at any point in time. These capabilities vastly improve the efficiency of drug supply management and shorten the trial administration process. Users have an opportunity to resolve issues as they arise, rather having to deal with them en masse prior to study close. Avoidance of Delays from Stock-outs IRT systems play an integral role in managing medicines during trials, including the assignment of kits, ordering of drugs for sites, managing product expiration dates, and tracking the inventory of products as described above. With an IRT system, site inventory levels are tracked in real Journal for Clinical Studies 51

IT & Logistics

time, and resupply orders are automatically generated when the inventory level at the site reaches a minimum value. In addition, reset values can be configured to initiate alerts when the inventory at a site or depot reaches a critically low level or when products are about to expire. This helps to ensure that proactive measures are performed to reduce the likelihood of a stock-out. Also over the course of a study, the initial baseline forecast is continuously refreshed based on real-time updates of what is happening with patient enrolment and product inventory as reported in the IRT. Supply chain managers, alerted to variances from the baseline forecast, can modify the forecast and know with great precision how much drug to produce and when. Such dynamic management aids with budget preparation, prevents the wastage that comes from stockpiling supplies, avoids the risk of stock-outs, and reduces emergency measures needed to replace expiring drugs. Without this virtuous cycle of information, companies can easily get caught with insufficient supplies to continue enrolment or even to follow the treatment regimen for enrolled patients, given that the lead-time to get products through the manufacturing, packaging, labelling, and distribution cycle can be many months. There have been instances in which poor inventory planning has led to stock-outs that forced sites to delay patient recruitment by many months. The automated tasks performed by an IRT system obviously create efficiencies throughout the clinical trial 52 Journal for Clinical Studies

supply chain, but less obvious is how these efficiencies can speed a trialâ&#x20AC;&#x2122;s progress toward closure and how the checks and balances built into an IRT can improve patient safety. The features and functions of the most sophisticated IRTs minimise human error (especially at critical junctures such as randomisation and drug assignment), provide real-time monitoring of AEs, speed the preparation of data for submission, and prevent stock-outs that lead to patient loss and trial delays. References 1. h t t p : / / w w w . b u s i n e s s w i r e . c o m / n e w s / h o m e / 2 0 1 5 0 1 3 0 0 0 5 6 2 1 / e n / Re s e a r c h - M a r k e t s 2015-Trends-Global-Clinical-Development, visited on December 29, 2016.

Robert Weney is Director of Production IT at Almac Clinical Technologies. For the past 10 years, Bob has been heavily involved in software testing for IRT systems, during which time he has seen a steady increase in their adoption by sponsors and contract research organisations. Today, he is responsible for operational effectiveness at Almac, with a focus on business intelligence, analysis, and process effectiveness for project delivery. Bob holds a B.S. degree in Mathematics and Computer Science and is a Certified Foundation-Level Tester. Email: robert.weney@almacgroup.com Volume 9 Issue 1


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IT & Logistics Demand-led Supply: Increasing Efficiency in Clinical Studies Logistics Cost pressures associated with the development of new medications are at an all-time high for the pharmaceutical industry. Drug development costs in general are rising and particularly so within therapeutic categories, for certain disease states where highly targeted and costly therapies such as biologics show promise. The cost burdens are further exacerbated by the need to target smaller populations with rare disease conditions, very high cost for comparator or standard of care medicines, and the utility of adaptive clinical trial designs. In addition, for many drugs currently in the pipeline, their very nature often adds to the cost of their development. Biologics tend to be far more expensive to develop and difficult to manufacture than traditional pharmaceutical products, and thus, each dose is more costly. The result is a spiralling in the complexity of many clinical trials. Large numbers of potential subjects may have to be screened to identify those who might benefit from the drug, and if the patient pool is limited, it is almost inevitable that multi-site global trials will be necessary to reach the recruitment target. Potential competition between sponsors seeking the same type of patients for their studies can make successfully recruiting enough patients for a study even more challenging. As a result, study sites in regions where the infrastructure to support clinical trials may be less than ideal will often be used to increase the pool of potential patients. Developing a supply chain to support all of these sites reliably poses a significant logistical challenge. Regardless, it is vital to bear in mind that clinical trials impact real patients, who need to receive their study medicines on time. The development of innovative clinical supply chain solutions, designed to better meet these changing requirements, is gaining traction. Traditionally, the decades-old supply-led approach (a PUSH model for supplies) was the standard method for the packaging, distribution and delivery of clinical supplies. However, this approach generally requires long, up-front lead times for packaging to establish pre-determined inventories of finished clinical supplies. The linear and fixed nature of this approach means that any variability introduced once production has begun, such as a change in the number of sites to be supplied, has the potential to cause problems such as delays or inadequate stock to fulfil demand. Under this traditional approach, it is also important to note that although required stock levels at each site are typically forecast well in advance of the study start, variability in patient recruitment rates can result in insufficient supplies at one clinical site, while there may be too much inventory at another. A shortage of 54 Journal for Clinical Studies

investigational medicine often means some patients cannot be treated and the validity of the trial data gathered by that site could potentially be called into question. Less serious, but still problematic, is the opposite case, where sites hold an excess amount of aging inventory which may then expire before it can be dispensed. Both of these situations ultimately introduce risk, push up waste, and potentially study costs. Demand-led supply (a PULL model) is a more flexible approach to clinical supply, which is better suited to address the variability and increased level of risk that often goes hand-in-hand with complex studies. Unlike the traditional approach to clinical supplies, the demand-led approach is flexible and does not rely upon the upfront production of a fixed quantity of finished supplies. This seemingly simple, but powerful, difference allows clinical supply inventories to match the actual patient recruitment rate at each site. Traditional Supply Model (The PUSH Model) The traditional supply-led model has been largely unchanged for decades, and in many circumstances remains the appropriate choice. For example, if patient recruitment is expected to be relatively easy, the study drugs are relatively inexpensive, easy to obtain or have long expiry dates, and the list of clinical sites is unlikely to change, this may be the most cost-effective model to use. With the supply-led model, each trial protocol requires that discrete primary and secondary packaging runs well in advance of the study start. These packaging runs typically have very long lead times. Studies spanning multiple countries will often opt to employ booklet labels which encompass the demands of multiple jurisdictions and languages. Booklet labels are not a trivial endeavour: they are expensive to design, translate and print, and have long lead times associated with productionâ&#x20AC;&#x201D;often they find themselves on the critical path to study start. Though they offer some flexibility once designed within the countries in the booklet; they also suffer with many constraints: 1) adding new countries is a significant challenge which leads to obsolescence of very costly labels, 2) regulatory changes for label requirements after the booklets have been printed is also a cause for re-work or obsolescence, and finally (and most importantly), 3) they are NOT patient friendlyâ&#x20AC;&#x201D;connecting the variable data to patient instructions buried in the labels may lead to diminished utility of the label by the patient. Since the precise quantity of labelled product that will be required for the trial is subject to variability, forecasts are used to determine how many packaging runs are likely to be needed to support the study over time, including Volume 9 Issue 1

IT & Logistics the batch size and timing of each run. Every site involved in the study will receive a bulk shipment of individually numbered patient kits at the outset and periodic resupplies based upon the future production schedule. Even if reforecasting is used mid-study to inform any adjustments to site volume levels, a substantial overage, which can exceed 200%, will have to be built into the process to ensure supplies do not run out. This is the “push” of supplies to meet patient needs and results in substantial amount of clinical supply waste. This waste is either the opportunity cost of API that could have been used for product development, or the real dollars spent on costly comparator and standard-of-care medicines purchased in the marketplace. Since in the real world, patient recruitment rates are rarely predictable, a modified version of the supply-led model introduces the concept of just-in-time labelling. This modified approach can prove beneficial if there are multiple trials being run in the same region that require the same base clinical supplies, but with different protocols and, therefore, different labels. Under this approach, clinical supplies are still produced in advance, however the final (patient) label is not applied until the patient has been identified and scheduled. The just-in-time model is more likely to be appropriate than the supply-led model if some variability in patient recruitment is expected, or the study drugs are likely to be in short supply. Just as under the supply-led model, discrete primary and secondary packaging runs will be carried out according to plan, resulting in partially complete patient kits that just require final labelling. These kits are held at a central facility where they will await final labelling and shipment to the clinical site, either directly or via an incountry depot depending upon the site location. An interactive response technology (IRT) system is used as the mechanism by which clinical sites request the necessary supplies from the central storage facility. This IRT “order” triggers the process of applying the final pre-printed label, protocol information and patient number to the partially finished patient kit, quality release and distribution to the clinical site. As with the supply-led model, initial forecasts and mid-study reforecasts are used to predict the levels of supplies that should be required. However, although some flexibility has been introduced and stock inventory levels will be lower, it remains difficult to make changes to the kits, and wastage levels are still high. Demand-led Supply (The PULL Model) Both the traditional and just-in-time models can lead to a mismatch in demand and supply, resulting in a significant amount of inefficiency in the supply chain alongside a high amount of clinical waste. For a trial involving highly targeted, and therefore much smaller populations of patients, it is important to develop a better understanding of what – and where – the demand is likely to be.


Consequently, there is a growing shift from the static, traditional model and semi-flexible just-in-time approach, to a more dynamic one. Demand-led supply is a fundamentally different concept, relying on a continuous chain of cGMP steps to permit the secondary packaging, label release and distribution of assembledto-order patient kits (with single panel labels specific for country), based on actual patient need. Patient needs at sites “pulls” required supplies. Those trials that should benefit most from a demandled supply model include ones where the sponsors are looking to be able to quickly activate new sites, where patient recruitment rates are expected to be highly variable, if the number and location of study sites are likely to change, or when clinical waste must be kept to a minimum to maximise a very costly or difficult -toobtain study drug. It is also more appropriate than the just-in-time model for any trial where the patient kits are particularly complicated, especially for a long-running study where the need to update an expiry date may come into play. The key to the demand-led model’s potential for improving supply chain efficiency and predictability is in its dynamic approach that decouples primary packaging from secondary packaging. Just like in the traditional approaches, primary packaging is completed in advance of the study start, with additional runs scheduled at predetermined points in the future based upon forecasted demand. However, unlike the traditional approaches, all secondary packaging (kit assembly and labelling) is carried out at one or more regional packaging facilities situated closer to where the trials are being run versus a central facility. These regional locations hold primary packaged “bright stock” in inventory. Bright stock identification is accomplished in the form of a batch lot barcode, which is scanned into a central inventory tracking system. Batch analysis and quality release takes place on samples of each lot just after the primary packaging process in order to streamline future quality inspections. And, as there is no secondary packaging done in advance of actual need, it is straightforward to pool stock across multiple protocols. Secondary packaging is performed in response to “orders” that arrive via the IRT system for the study. The requested kits are assembled, country specific labels are applied, supplies are released, approved and shipped directly to the clinical site within a matter of days. The bright stock barcodes are scanned during the secondary packaging process for quality control purposes, and also so that the centrally tracked inventory is updated accordingly. In addition to supporting a clinical supply chain that is reliable and responsive, the dynamic nature of a demand-led approach has other advantages as well. Journal for Clinical Studies 55

IT & Logistics Firstly, it eliminates the need for time-consuming and bulky booklet labels, since country-specific single-panel labels are applied during secondary packaging. Patient kits assembled under the demand-led approach carry the latest possible expiry date available at the time of secondary packaging. Studies using protocol designs that demand supply chain flexibility, such as an adaptive trial, the demand-led approach can more effectively handle mid-study changes that impact clinical supplies, such as dosage changes or adding new countries. Finally, the labels created are more patient friendly as variable, dosing, and storage/handling information are readily available. How can Demand-led Supply be Successfully Implemented? Key to the success of a demand-led supply model is the availability of a global network of facilities with secondary packaging and clinical storage capabilities. These should be located in countries within easy reach of all the study sites that are being supported, in order to facilitate quick distribution. By relying upon multiple locations, versus a single location, it may be possible for these regional facilities to also provide backup capacity for other locations. For example, in case of unforeseen events such as 2010’s Icelandic volcano eruption that disrupted air travel over Europe, packaging facilities in locations unaffected by the event may be able to temporarily supply sites within the affected region.

all this is the need to maintain product integrity in this challenging global network, which can be particularly challenging when products requiring a cold chain are involved. Any supply chain model will have to deal with all these challenges and future changes. One of the main advantages in shifting to demandled supply is the potential for significant time savings, both over the traditional model and the just-in-time variant. The dynamic approach of the demand-led service model means that is both flexible and responsive to study changes and has the potential to get necessary clinical supplies to study sites faster, which is important in light of the increasing reliance on adaptive trials and increasing competition for patients, where it can make all the difference between a study running on time and one that is challenged, or even compromised by supplyrelated delays.

Implementing a demand-led supply model is a strategic commitment that, once in place, provides the sponsor with a flexible solution that can better absorb variability and ultimately service the needs of clinical sites and patients. The demand-led supply approach creates a flexible model that works globally, regionally and locally, and once put in place, can be leveraged for future studies as appropriate. However, putting a demand-led model in place is not as simple as flipping a switch and shifting instantly from a supply-led to a demand-led model. The necessary systems, processes and integration points must first be established to support a demand-led supply chain. Among these processes is a tight integration with IRT to aggregate demand forecast. Adoption and implementation of IT systems designed to support demand-led inventory management, order scheduling and supply release specific to demand-led packaging activities are to be required as well. Conclusion A multi-site global trial is far more complex to manage than a single-site trial, or even a multi-site trial where all the sites are within the same jurisdiction. Despite efforts at harmonisation, differences between the requirements and standards of regulatory authorities still exist. But even on a practical level, there are differences in infrastructure between countries and regions, and the processes and rules regarding customs differ too. Across 56 Journal for Clinical Studies

Kunal Jaiswal, Vice President, Strategic Development Solutions, Clinical Supply Services. Mr. Jaiswal joined Catalent in October 2016 and brings over ten years of clinical supply chain operations experience. Most recently he was Director of Clinical Supply Packaging Operations at Pfizer, and previously Head of Supply Chain Strategy at Merck. Mr. Jaiswal is a former Chair of the ISPE’s (International Society for Pharmaceutical Engineering) Investigational Products Steering Committee. He holds a bachelor’s degree in pharmacy from Purdue University and a master’s in business administration from Western Michigan University. Email: solutions@catalent.com Volume 9 Issue 1

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IT & Logistics Counting the Cost of Corrections in Clinical Trials Labelling Bringing a new drug to market costs millions, so it’s highly risky to leave product labelling and packaging to chance. Especially if it’s expensive professionals giving hours of their time to these repetitive manual processes, says Peter Muller of Schlafender Hase

that precedes this will have been for nothing: certainly it will not deliver the expected return. So life sciences companies need robust processes in place to ensure that products are taken absolutely correctly, leaving no scope for error in dosage, for example.

The cost of bringing new drugs to market has soared, not least because of rising regulatory requirements. New analysis published earlier this year by Tufts Center for the Study of Drug Development (Tufts CSDD) puts the bill for developing and gaining marketing approval for a new drug at over $2.5 billion, climbing to $2.87 billion when post-approval R&D costs (of $312 million) are factored in 1.

The product runs in clinical trials may not be on the same scale as for mass production, but the stakes are enormously high and the authorities and brand owners will be paying close attention to accuracy and results.

The $2.5+ billion figure (per approved compound) is based on estimated average out-of-pocket costs of $1.4 billion and time costs (expected returns that investors forego while a drug is in development – typically many years) of $1.16 billion. That’s before any cost for postapproval studies, required by the US FDA as a condition of approval, to assess new indications, new formulations, and new dosage strengths and regimens, and monitor safety and long-term side-effects in patients. Maximising Trial Success Despite the Odds Within all of this, the clinical trials process carries its own particular share of risks and associated costs. If drugs do not pass human testing – and most don’t – all of the work

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In all aspects of product labelling and packaging, relying on manual processes for checks and corrections is inefficient and error-prone, yet the practice is still commonplace in life sciences. This affects all product labelling, from the lab to the pharmacy shelves. The more regulatory requirements there are, and the more frequently these specifications change, the greater the scope for error. Similarly, the more products, variants and markets a company is dealing with, and the shorter the release cycles, the bigger the chance that something could go awry with the labelling. The media archives are laden with examples of big names that have fallen foul of regulations, by simply failing to spot a misprint until it’s too late, or neglecting to meet new guidelines in a particular market. From children’s cough medicines to dietary supplements, the

Volume 9 Issue 1

IT & Logistics simplest error in how consumers should store or take the product could result in serious side-effects. There are all sorts of risks associated with manual proofreading, with the main ones highlighted below. Exposure to Error Humans make mistakes. Even with two sets of eyes on a document, proofreaders can develop blind spots – either because they’ve looked at the same content for too long, or because the task is so repetitive and unstimulating that the brain has become distracted 2. Yet even the smallest editing or artwork oversight can have serious consequences. In life sciences, the difference between “store this product at 2-8°C” and “store this product at 28°C”; “take 1-2 a day” and “take 12 a day”; or “do not chew and swallow” and “do not not chew and swallow” could be a matter of life and death. People are Expensive Manual tasks are unrewarding, demotivating and a poor use of qualified professionals’ time. Yet pharmaceutical companies don’t typically employ proofreaders; rather they use scientific writers with PhDs to check over content, at great expense. The cost per hour of work from the employee doing the proofreading doesn’t just include the salary, but also tax, benefits, insurance, holidays, office space, training, recruitment costs and so on, which can more than double the gross salary. In the case of graphic designers, there may be additional costs for re-work. When budgets are tight, and skills in regulatory affairs and quality assurance at a premium 3, it doesn’t make commercial sense to use experts to do routine administrative tasks, however vital the outcome. In the worst cases, people who feel un-challenged or under pressure to do extensive manual tasks on top of already demanding workloads, will leave the organisation, and studies suggest that losing a salaried employee can cost as much as twice their annual salary 4, especially for a high-earner. Adding to employees’ faltering morale is the stress caused by being at fault for an error – errors that are very easy to make, yet equally easy to avoid. Lack of Flexibility Manual proofreading isn’t especially flexible. It requires specialist knowledge, native language experts and dedicated, uninterrupted time. It can tie talented people to their desks, and detract from higher-value work. Where Automation has Traditionally Fallen Short In the past, attempts to automate proofreading and document comparison – to relieve skilled professionals from mundane tasks – have fallen short. This has been due to technology limitations, language restrictions, and insufficient accuracy to fit the purpose.

Document Conversion Problems Traditional text comparison tools have clear limitations. They convert content to PDF format and then compare them visually. This option is inadequate for heavilyregulated markets. Converting from one format to another is far from ideal: it can introduce anomalies, and the process doesn’t allow teams to work from original documents, which may be important mid-way through a drug approval process. In addition, document conversion for the purposes of comparison is a violation of GMP processes and can lead regulators to question the validity of comparisons, and the entire packaging review process. Content Corruption Graphic designers often take the blame for errors caused by conversion errors, because of the different software packages they have to work with. Typically designers will take a Word file, import it into InDesign/QuarkXPress/ Illustrator, work on it and then convert it back to a PDF file. The problem is that the various software systems originate from different companies (e.g. Microsoft/ Quark/Adobe). The fonts they use may have different names, and even change certain characters (a classic one in pharma is “µg” being changed to “mg” by certain artwork creation software). Language Limitations Markets are becoming ever more global, and it isn’t just Europe that presents a range of disparate language and regulatory requirements. Asia and Africa bring additional demands. Relying on software to read and interpret a human language has traditionally been a challenge, despite advances in technology. The issues are similar to those associated with performing the original translation. As specialist agencies note, “MT [machine translation] is not the way to go. Yes it’s cheap and there’s minimal effort required on your part, but at the end of the day do you really want to lower the value of the high quality content you’ve created for your home market?” 5 Inadequate Levels of Accuracy Where file conversion is taking place, or comparisons rely on certain fonts, language or specialist content knowledge, accuracy starts to suffer. And when teams can’t depend on automation for the highest levels of accuracy, their confidence in technology diminishes until they stop using the software, undermining any return on investment. For the users whose necks are on the line, it’s better to play safe. 6 Complexity & Cost Costs and long deployment cycles have also proved prohibitive. Inflexible licenses can drain capital budgets, while the typical software procurement and implementation cycle is 9-18 months. 7 Improvements in Automation Technology has improved a great deal, however, and


Journal for Clinical Studies 59

IT & Logistics there are now new and more robust approaches to text comparison that promise to relieve quality assurance teams of several rounds of manual work – reliably. Better still, these tools can be sourced and run via the cloud now, making them more accessible and affordable than previous options. A particularly powerful approach to label checking uses text’s underlying universal code (‘Unicode’), rather than the actual words of a given language. This means that, whatever the format, font or operating system, the software understands what this represents. When it makes document comparisons, it is comparing the code behind the characters – allowing it to compare two files in any language and any font, as long as these support Unicode. Unicode allows data to be retrievable with a simple keyword search in a database or document management system, and allows documents to be transferred to other applications without content changing or being corrupted. This offers unprecedented levels of accuracy, and incredible speed, because this kind of text verification approach is able to home straight in on the subtlest changes and anomalies, so that these can be addressed swiftly without the need to painstakingly go through entire documents manually. It’s possible to do the same with images too, allowing teams to compare logos, charts, chemical formulae, etc., and highlight the tiniest discrepancies. Improved Speed & Productivity With this kind of automation tool, typical like-for-like document comparison typically takes seconds – versus several hours if done manually – even if the language is unfamiliar. This can free up expert time for frontline regulatory or quality assurance work. If companies save an estimated five hours per week on manual proofreading/text verification, that could be a $13,500 saving against the salary of a qualified regulatory affairs employee – capacity that could be redeployed to more useful effect. Growing regulatory demands are increasing the pressure on RA and QA teams, which have never been busier or as overstretched. Unsurprisingly, quality assurance and regulatory affairs are now among the main growth disciplines in life sciences . Yet there is a gap in the available talent pool, and rising concern among life sciences organisations that failure to keep employees stimulated could result in key people moving on. And, of course, service quality is at risk where people’s hearts aren’t in the task, which is the last thing QA teams need. Reducing reliance on manual processes isn’t just a riskavoidance or insurance strategy. In life sciences, the rise in merger and acquisition activity and the growing 60 Journal for Clinical Studies

trend of smaller batch numbers and increased drug personalisation means label demands are soaring and becoming more complex to manage. Each new demand, each new regulation multiplies the burden on regulatory affairs, quality assurance and marketing to be responsive, accurate and thorough at a time when skilled employees have little or no capacity to spare. This isn’t just a clinical trials requirement, of course, but one with far-reaching application across the life sciences product lifecycle. As regulatory demands continue to increase, the associated cost and risk can only intensify, so life sciences firms need to find new ways of managing the workload. Find the right solution, and everyone stands to benefit. References 1. Tufts CSDD Assessment of Cost to Develop and Win Marketing Approval for a New Drug Now Published, March 2016: http://csdd.tufts.edu/news/complete_ story/tufts_csdd_rd_cost_study_now_published 2. What’s Up with That: Why It’s So Hard to Catch Your Own Typos, Wired.com, August 2014: http://www.wired. com/2014/08/wuwt-typos/ 3. Spotlight on: European employers 2014 (p5), Real Staffing Group 2014: http://assets.realstaffing.com/ images/site/Recruiting_and_retaining_a_competitive_ workforce.pdf 4. The Dirty Truth: Employee Turnover Costs, TalentKeepers: https://www.talentkeepers.com/wp-content/ uploads/2015/03/Talentkeepers-The-Dirty-TruthEmployee-Turnover-Cost-Whitepaper.pdf 5. The Dangers of Machine Translation, Webcertain Translates: http://blog.webcertain.com/the-dangers-ofmachine-translation/09/07/2014/ 6. The High Costs of Small Mistakes: The Most Expensive Typos of All Time, Six Degrees: https://www.six-degrees. c o m / t h e - h i g h - c o s t - o f - s m a l l - m i s ta ke s - t h e - m o s t expensive-typos-of-all-time/ 7. Spotlight on: European employers 2014 (p5), Real Staffing Group 2014: http://assets.realstaffing.com/ images/site/Recruiting_and_retaining_a_competitive_ workforce.pdf

Peter Muller, Managing Director, Schlafender Hase, Americas. For the last 20 years, Peter Muller has worked on software and process improvement projects with Fortune 500 companies from various industries: pharmaceutical, consumer goods, food, aerospace and defence. He has a wealth of experience working with international clients to define their organisation's goals and help them leverage new technologies to achieve productivity gains, process improvements and cost savings. Contact: www.text-verification.com Email: peter.muller@sh-p.com Volume 9 Issue 1


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Book Review Cardiovascular Safety in Drug Development and Therapeutic Use: New Methodologies and Evolving Regulatory Landscapes Title: Cardiovascular Safety in Drug Development and Therapeutic Use: New Methodologies and Evolving Regulatory Landscapes Co-authors: J Rick Turner, Dilip R Karnad and Snehal Kothari Publisher: Springer Science, New York, NY 10013 (2017); 333 pages. ISBN: 978-3-319-40345-8 Price: Hardcover: £82.00/$129.00/€109.99 eBook: €|$ 24.99 Co-authored by Turner, Karnad and Kothari, three experienced and respected scientists in the field of investigating cardiovascular safety of drugs, this book brings together a wealth of information, being a compilation of the regulatory requirements, stateof-the-art knowledge on the mechanisms involved in drug-induced adverse cardiovascular effects and the investigational strategies available to characterise drugs for these effects.

Drug-induced proarrhythmias, although well recognised by the mid-1980s, did not attract sufficient research or regulatory interest, as evidenced by the relatively muted withdrawals of prenylamine (1988) and lidoflazine (1989) from the market due to their welldocumented torsadogenic effects. Terfenadine (1989), terodiline (1991), the Cardiac Arrhythmia Suppression Trial (1991) and the SWORD study (1994) dramatically changed the regulatory landscape. Today, potential proarrhythmic effects of drugs occupy a centre stage in drug development and as a result of experience with other drugs, cardiac safety of drugs has also acquired a much wider connotation beyond their proarrhythmic potential. Drug-induced proarrhythmic potential is one of the two Achilles heels of drug development, the other being druginduced hepatotoxicity. Interestingly, the evaluation of both during drug development relies on measurements of imperfect surrogate biomarkers (QT interval and serum liver function tests). The book contains 15 chapters, divided into six parts. Topics in each chapter are covered in exemplary detail with clarity. Chapters are well referenced with provision of further reading recommendations for those with a greater in-depth interest. The Introductory Part 1, which provides an overview of the contents of the book, is followed by two others that deal with the biological basis of drug development, genetics and drug response, pathophysiology of cardiovascular system and aspects of statistical considerations in designing, analysing and reporting of clinical trials. Chapter 5 on “Analyzing and Reporting Safety Data” is particularly detailed and well-presented. Part 4, which includes chapters 7-9, focusses quite rightly on the proarrhythmic safety of drugs. We have today a much better, though still incomplete, appreciation of the mechanisms that underpin proarrhythmias and, given the efforts expended in developing newer paradigms (comprehensive in vitro proarrhythmia assay (CiPA)) in quantifying the clinical risk of proarrhythmias instead of its surrogate (QT interval), chapters 7-9 are probably the core of the book. Chapter 7 begins with a historical account of events and electrophysiological research that have led to the current non-clinical (ICH S7B) and clinical (ICH E14) regulatory requirements, followed by detailed discussion of ECG recording techniques, use of central laboratories, QT correction formula, data analysis and use of newer biomarkers such as Tp-Te interval, transmural dispersion of repolarisation and T-wave morphology. Refreshingly, it

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Volume 9 Issue 1

Book Review

includes a critical review of alternative approaches when an ICH E14-compliant thorough QT study is not practical. Chapter 8 is an excellent discussion of the merits and challenges of exposure-response (ER) analysis, especially in early-phase clinical pharmacology studies, as well as a critique of the design and results of the IQ-CSRC study published in 2015. The authors also illustrate vividly the conundrum arising from discrepancy between a TQT study and ER analysis. Chapter 9 explains the background to, and the need for, the evolving CiPA paradigm, including its electrophysiological basis. The authors provide an account of its current state and future prospects, without overlooking the challenges in its implementation. Part 5 is concerned with safety of drugs used in oncology and diabetes. Given that many oncology drugs have profound adverse cardiovascular effects such as hypertension, prothrombotic effects and cardiomyopathy, the authors discuss the wider cardiovascular safety of drugs (using anticancer drugs as examples) and the use of more modern techniques and biomarkers available to characterise drugs for these effects. Specifically included is also a chapter devoted to regulatory requirements for drugs for diabetes, using rosiglitazone as an excellent case study. It provides an antithesis to empagliflozin recently (December 2016) approved by the FDA for a new indication to reduce the risk of cardiovascular death in adult patients with type 2 diabetes mellitus and cardiovascular disease. Part 6 is principally concerned with issues related to post-marketing surveillance which includes consideration of (sometimes controversial) use of experimental and non-experimental therapeutic trials. The book concludes with a chapter on other safetyrelated perspectives such as adherence and compliance, pharmacogenetics, rare diseases and registration of clinical trials. It is unreasonable to expect a book with such a broad perspective to cater for everything for everyone and no www.jforcs.com

doubt, there will be a few disappointments. For me, the book would have benefitted from chapters on effects of drugs on conduction (QRS and PR intervals), potassium channel activators with greater emphasis on regulatory implications of drug-induced QT interval shortening (e.g. rufinamide) and arteriothrombotic effects of drugs such as rofecoxib and ponatinib which, both when juxtapositioned, provide a sharply contrasting risk/benefit perspective. The authors deserve our congratulations for their immense efforts and well-presented contribution to the scientific community. Importantly, despite the affiliations of the authors, the book is refreshingly free from any bias. It caters for all professionals interested in cardiovascular safety of drugs, including academic, regulatory and pharmaceutical scientists. I have no hesitation in recommending this book as a valuable reference source. The hardcopy is priced at ÂŁ82 but given the cost of failing to characterise adequately the cardiovascular safety of drugs, the price seems like a very worthy investment.

Reviewed by: Dr Rashmi Shah served as a Senior Clinical Assessor at the Medicines and Healthcare products Regulatory Agency of the UK from June 1987 to December 2004 and has represented the UK at a number of EU committees and Working Parties. With a main interest in cardiac safety of drugs, he was the principal co-author of the CPMP â&#x20AC;&#x153;Points to Considerâ&#x20AC;? strategy on drug-induced QT interval prolongation. Having authored about 25 papers and lectured widely on this subject, he also represented the EU at the ICH initiative that led to ICH E14 guidance. Email: clinical.safety@hotmail.co.uk Journal for Clinical Studies 63

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