Journal for Clinical Studies – ISSN 1758-5678 is published quarterly by Senglobal Ltd.
4 FOREWORD
WATCH PAGES
6 The Importance of Clinical Trial Preparation for Biotech Companies – A UK Perspective
Many biotechs still underestimate the importance of solid regulatory and clinical trial preparation-particularly when expanding into the UK. The UK biotech sector is thriving and with significant investment flowing into research, the opportunities for growth and innovation are considerable. Yvanne Enever of PHARMExcel discusses that by integrating regulatory and trial design and conduct considerations into the development process from the outset, biotechs can avoid unnecessary delays and set themselves up for UK success.
8 Regulatory Perspectives on the FDA’s Use of Artificial Intelligence in Drug Development
As Artificial Intelligence (AI) gains prominence in drug development, regulatory agencies are creating and implementing frameworks to promote the responsible use of AI for medical products. AI is a machinebased system that can, for a given set of human-defined objectives, make predictions, recommendations, or decisions influencing real or virtual environments. Jennifer Nguyen of Clarivate discusses how the four main areas of focus are to foster collaboration to safeguard public health; advance development of regulatory approaches to support innovation; promote harmonised standards, guidelines and practices; and support research monitoring AI performance.
MARKET REPORT
10 The Clinical Development Market in APAC:
Opportunities, Growth and Challenges
The Asia-Pacific (APAC) region has rapidly emerged as one of the most dynamic markets in global clinical development. Over the past decade, demand for innovative therapies, a large and diverse patient population and favourable government initiatives have transformed APAC into a preferred destination for conducting clinical trials. Clareece West and Alison Cundari of Linical discuss the APAC clinical development landscape, highlight country-specific opportunities, explores drivers of growth and examines the challenges and concerns that sponsors must navigate.
14 Challenges in the Post-marketing Investigations for Medical Devices
The opinions and views expressed by the authors in this journal are not necessarily those of the Editor or the Publisher. Please note that although care is taken in the preparation of this publication, the Editor and the Publisher are not responsible for opinions, views, and inaccuracies in the articles. Great care is taken concerning artwork supplied, but the Publisher cannot be held responsible for any loss or damage incurred. This publication is protected by copyright.
Volume 17 Issue 3 Autumn 2025, Senglobal Ltd.
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As the European and overall worldwide regulation strives to become clearer, unambiguous, harmonised and as a result, more restrictive and demanding, this tendency still seems to leave behind the post-marketing studies for medical devices. Consequently, the manufacturers may discontinue certain medical devices or remove them from the EU market, leading to a device shortage. Dilyana Stoeva of Ramus Medical discusses the serious challenges faced by medical device manufacturers in demonstrating compliance with the MDR. Following the increase in cases, the manufacturers will have to go through an actual PMCF investigation to satisfy the clinical evidence expectations sufficiently.
18 Harmonising Global Approaches to Transformative Theranostics
Cancer prevalence is rising globally. Radiopharmaceuticals and Theranostics offer precise, targeted diagnostic and therapeutic solutions for safer, more tolerable oncology therapies. Dr. Divya
Mishra of ICON explores the landscape, regulatory considerations, infrastructural and operational requirements along with future directions for expanding these therapies into clinical settings. Achieving the potential of theranostics on a global scale will require concerted efforts from stakeholders, including policymakers, developers, CROs, academic medical centres and payers.
22 Supercharging Rare Disease Drug Development Through Human Connection
Technological advancements in recent years have brought forward a focus on how to make the drug development process more efficient and cost-effective, including for clinical trials. Kate Shaw of Innovative Trials discusses how in this increasingly digital world, empathetic engagement remains a key component of clinical trial patient recruitment and retention. Combining human connection with AI capabilities will optimise patient recruitment and retention strategies, reduce drop-out and subsequently increase data reliability for the regulatory stage.
26 Beyond Enrolment: How Community-Based Oncology Practices Drive Patient Retention in Early-Phase Trials
Recruitment remains a well-known hurdle in Phase 1 oncology clinical trials, but what happens after enrolment is equally vital: patient retention. Keeping patients on a trial through its duration presents an equally critical challenge that directly impacts study validity, operational efficiency and future patient willingness to participate in research. Dr. Justin A. Call of Rana Health discusses how retention is not only about completing one protocol – it’s about building an environment that supports patients over time. From trial design to site operations, from the first appointment to communication with referring physicians, every interaction can either strengthen or weaken a patient’s willingness to continue, thus making support vital.
CLINICAL TRIAL MANAGEMENT
28 Redefining Site Relationships in Clinical Trials: Insights from the WCG 2025 CenterWatch Global Site Relationship Survey
At the heart of every clinical trial lies a complex network of relationships between sponsors, contract research organisations (CROs), trial sites, investigators, coordinators and patients. Melissa Hutchens of WCG discusses that the future of clinical research depends on the ability of sponsors, CROs and sites to listen, adapt and collaborate. Through these principles, the industry can tap into the expertise and dedication of the individuals who make clinical trials possible to accelerate scientific discovery.
32 AI in Clinical Trial Recruitment: Proceed with Cautious Optimism
Historically, patient recruitment has been a consistent operational challenge in clinical trials. Traditional methods including physician referrals, site databases and advertising campaigns, often resulted in slow enrolment, high dropout rates and underrepresentation
of diverse populations. Earl Seltzer of CTI discusses the promise, limitations and future direction of AI in clinical trial recruitment. Seltzer goes further to discuss that by embracing Artificial Intelligence (AI) it will rapidly reshape the landscape of clinical research, offering transformative solutions to longstanding challenges in trial design, execution and data management.
TECHNOLOGY
34 Reimagining Clinical Trial Management: AI as the Virtual Team Member
With the rising complexity of clinical trials, the workload on clinical project teams correspondingly increases. Furthermore, the clinical research ecosystem is under increasing pressure to conduct trials more efficiently and cost-effectively. Dr. Ashok Ghone of MedInventas discusses that by embracing digital transformation it presents an opportunity to reconsider methodologies for conducting trials through the integration of Artificial Intelligence (AI)-driven, automated and data-centric systems. Ashok explores how AI is taking the form of the ‘virtual team member,’ that will enhance essential functions such as patient recruitment, site selection, data monitoring, risk assessment and protocol adherence.
40 Harnessing Data Visualisation for Clinical Research: From Insights to Action
The future of clinical research belongs to the curious, the bold and the resilient. It is not the size of the company or the depth of experience that determines impact, but the willingness to innovate, adapt and put people at the heart of every solution. Craig Mcilloney of Catalyst discusses by embracing data visualisation it becomes a powerful lever for transformation, rendering the complex simple, the invisible visible and the inert actionable. In effect it can bridge the gap between insights and action – delivering not only improved research outcomes, but tangible benefits for patients and society.
LOGISTICS & SUPPLY CHAIN
44 Beyond Manufacturing: Strategic Clinical Supply Management for Global Trial Success
Clinical trials are the critical stages in which scientific innovation is tested and validated in patients, collecting data that will transform experimental therapies into approved treatments. Edward Groleau and Brian Keesee of PCI discuss that while therapeutic efficacy remains the ultimate driver, the practical execution of packaging, labelling and distribution determine whether an investigational therapy reaches trial participants on time, in stable condition and in full regulatory compliance. Selecting the right partner to execute these activities is not simply procurement exercise. It is a strategic decision that directly influences patient safety, cost control and trial continuity.
48 Clinical Trial: A Logistical Nightmares?
Clinical trials are one of the most demanding areas within life science logistics and requiring efficient delivery of novel, sensitive medicines all over the world. These trials often involve numerous cross-border shipments with associated customs requirements. Bailey Coppage of Biocair discusses how logistics experts, packaging teams and cold chain providers must work together to simplify the process and create solutions that maintain the desired temperature for extended periods and reduce the potential for hazards, mitigating risk against unexpected transit delays.
As the leaves begin to turn and days become shorter, we welcome you to our third edition of JCS in 2025. We hope you enjoy reading! This Autumn issue of JCS comprises of valuable research and forward thinking that will continue to strengthen the progress in the sphere of clinical trials.
We begin our Therapeutics section with the discussion that Artificial Intelligence (AI) models can help identify patients faster and improve diversity by analysing patient records, ease the burden on busy research sites by automating workflows and personalise communications. Though this is true, Kate Shaw of Innovative Trials asserts that no matter the numerical scale of participants you need for your study or how fast you can identify them, the challenge of retention remains strong. Shaw states that in order to succeed in building patient-centricity into enrolment and retention the need to adopt strategies from the outset and use human connection to power the type of empathetic engagement that keeps patients feeling respected, heard and involved are needed from start to finish.
Craig Mcilloney defines data visualisation as a powerful lever for transformation. He explores the benefit of delivering not only improved research outcomes but tangible benefits for patients and society. Craig explains that a successful visualisation does not merely display data; it anticipates the questions and contexts of its audience – be they are researchers, clinicians, policymakers, or regulators. When executed correctly, visualisation empowers these stakeholders to accelerate decision-making, improving both
the speed and the impact of clinical trials, but only if it is simple and intuitive to use. By embracing the best of technology and the wisdom of user-centric design, we can bridge the gap between insights and action – delivering not only improved research outcomes, but tangible benefits for patients and society.
Come join us as Edward Groleau and Brian Keesee discuss how the therapeutic efficacy remains the ultimate driver for the practical execution of packaging, labelling and distribution, as it determines whether an investigational therapy reaches trial participants on time, in stable condition and in full regulatory compliance. PCI goes further to explain how selecting the most suitable partner to execute these activities is a strategic decision that directly influences the patient’s safety, cost control and trial continuity. Therefore, reaffirming the view that in order to successfully manage a trial rather than cause one to stall, the need to anticipate the risk of disruptions from supply chains is vital.
Ashok Ghone opens a discussion centring around the subject of AI taking the form of the ‘virtual team member,’ as he asserts that with the increasing workload involved with clinical trials AI will enhance essential functions such as patient recruitment, site selection, data monitoring, risk assessment and protocol adherence. Despite this being true Ashok does drive forward the thinking that AI should not be the sole approach, instead he pushes for a collaborative model that employs both human expertise and machine capabilities to generate an environment where they can work side by side as a digitally enabled, virtual project team.
Melissa Cavner, Editor
JCS – Editorial Advisory Board
• Ashok K. Ghone, PhD, VP, Global Services MakroCare, USA
• Bakhyt Sarymsakova – Head of Department of International Cooperation, National Research Center of MCH, Astana, Kazakhstan
• Catherine Lund, Vice Chairman, OnQ Consulting
• Cellia K. Habita, President & CEO, Arianne Corporation
• Chris Tait, Life Science Account Manager, CHUBB Insurance Company of Europe
• Deborah A. Komlos, Principal STEM Content Analyst, Clarivate
• Elizabeth Moench, President and CEO of Bioclinica – Patient Recruitment & Retention
• Francis Crawley, Executive Director of the Good Clinical Practice Alliance – Europe (GCPA) and a World Health Organisation (WHO) Expert in ethics
• Georg Mathis, Founder and Managing Director, Appletree AG
• Hermann Schulz, MD, Founder, PresseKontext
• 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
• Maha Al-Farhan, Chair of the GCC Chapter of the ACRP
• Rick Turner, Senior Scientific Director, Quintiles Cardiac Safety Services & Affiliate Clinical Associate Professor, University of Florida College of Pharmacy
• Robert Reekie, Snr. Executive Vice President Operations, Europe, AsiaPacific at PharmaNet Development Group
• 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
Ramus Medical
is a part of Ramus Corporate Group. The company is managed under a centralised quality management and has developed an integrated QMS as well as specific standard operating procedures tailored for the clinical trials department that are fully harmonised with the GCP guidelines, and the local and European legislation.
Ramus Medical EOOD is a full-service contract research organisation (CRO) in Sofia, Bulgaria.
The company was created in 2009 as a natural development of the Medical Laboratory Ramus Ltd., the largest privately-owned medical laboratory in Bulgaria.
The company independently manages clinical research projects in Bulgaria and provides partnerships in multinational clinical projects providing a comprehensive range of clinical research services:
Core Services include:
• Medical writing
Our staff has extensive expertise in the preparation, adaptation and translation of a wide range of clinical trial documents that are fully compliant with the Good Clinical Practice (GCP) standards, the client’s specifications and the regulatory requirements.
• Study start-up
We offer full or partial study start-up assistance for different types of studies throughout Bulgaria.
• Regulatory submission
• Project management
• Monitoring
• Data Management
• Pharmacokinetic evaluation
• Biostatistics
• Regulatory advice and services
• Readability User Testing
• Registration of medicinal products on the territory of Bulgaria
• Pharmacovigilance services
• Logistic department
• Destruction of IMPs/IMDs & clinical samples – agreement with PUDOOS
• Archiving services
• DDD activities
Ramus Medical has gained its expertise during the completion of numerous clinical projects carried out over the past decade:
• Phases I to IV drug trials
• Non-interventional studies
• Pilot and Pivotal Medical Device investigations
The clinical trials we conducted facilitated the MA/CE mark granted by various European Agencies/Notified Bodies and Third Country Agencies.
Ramus Medical offers flexible clinical research services in various domains, with extensive experience in fields.
Our team comprises qualified, appropriately trained, experienced, motivated and collaborative professionals and is competent to
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communicate effectively across geographical and cultural boundaries to resolve any arising issues. We adhere strictly to the agreed timelines during the clinical investigations and strive to complete the tasks on time.
Why are we the solution for your projects? Ramus has its own:
Medical and Bioanalytical Laboratory
In 2018 the Medical Centre Ramus was established, located in Sofia, Bulgaria. Up to date, it has three separate locations, one of which is developed as an independent clinical research centre in compliance with the requirements for the phase I unit.
The Medical Centre Ramus allows the conduct of clinical trials in all phases in many therapeutic areas.
The Medical Centre meets all requirements for performing highquality clinical research and is designed to maximise the delivery of high-quality research data and was GCP-inspected.
Ramus Medical retains an extensive database of investigators and sites compiled through years of mutually beneficial collaboration.
Our bioanalytical laboratory is equipped with leveraging state-ofthe-art instrumentation (LC-MS/MS), techniques, and facilities, our team of experts has experience in a broad range of small molecules. Our Analytical laboratories provide method development, transfer, validation, and analysis of preclinical and clinical biological samples. We have extensive expertise in developing sensitive methods for LCMS/MS-qualifying multiple analytes and metabolites.
• Logistical company, certified for hazardous and biological samples transportation
• Clinical site facility and own catering company for hospitalised patients
The Importance of Clinical Trial Preparation for Biotech Companies – A UK Perspective
The UK biotech sector is thriving and with significant investment flowing into research, the opportunities for growth and innovation are considerable. In 2024, UK biotech investment reached £3.5 billion, a significant boost that shows the confidence in the sector’s potential. However, amid this excitement, many biotechs still underestimate the importance of solid regulatory and clinical trial preparation-particularly when expanding into the UK. By truly understanding the regulatory landscape, companies can undertake the necessary pivotal trials, fast-track the approval of their innovations and get their product approved and out to those that need it the most-patients.
The UK’s Biotech Market: A Vital Global Player
The UK continues to be one of the world’s leading biotech hubs. With a solid track record in innovating, there is no denying the scale of the opportunities. However, accessing these opportunities is not always straightforward. The UK now operates under its own regulatory framework, separate from the EU’s system and navigating this new environment requires careful planning.
The UK’s Medicines and Healthcare products Regulatory Agency (MHRA) sets the regulatory framework for clinical trials, medical devices and drugs. Understanding how to navigate this system is essential for companies hoping to bring their products to market efficiently and without unnecessary delays.
The Importance of Clinical Trial Conduct in the UK
Too often, companies focus primarily on product development,
overlooking the critical importance of integrating regulatory considerations, especially around clinical trials, into their early-stage planning.
The UK’s regulatory framework, while robust, can be complex and distinct from other global systems, especially when it comes to clinical trial authorisations, safety reporting and ongoing oversight. The MHRA has specific requirements for clinical trial conduct that must be carefully navigated, from initial trial approvals through to monitoring, data management and safety monitoring.
Getting it right early in the process is crucial for avoiding costly delays or regulatory hurdles that can disrupt timelines. Having the right CRO in place, who understands the UK nuances, ensures clinical trials are conducted smoothly, with all necessary approvals in place, helping to speed up market access and reduce risk as companies bring their innovations to market.
Regulatory Challenges in the UK: Compliance and Quality
One of the most significant challenges facing biotechs is the misconception that the UK is easy to navigate. While the UK does offer a world-class infrastructure, the regulatory system is more complex than many anticipate. Some of the key hurdles we encounter include:
• Regulatory Approval Processes: The UK’s regulatory approval system is detailed and specific-distinct from the EU and US. Companies must adjust their application strategies and timelines, to comply with the latest regulations, which vary depending on the product category-whether it’s a drug, medical device, or combination product.
• Quality Management Systems (QMS): A robust QMS is a nonnegotiable when it comes to UK trial conduct.
• Pharmacovigilance Infrastructure: In the UK, pharmacovigilance is a vital part of the regulatory process. Companies must ensure their systems are in place to meet the UK’s stringent safety monitoring requirements.
These aren’t just boxes to tick-they are the foundation of success. If companies fail to anticipate and prepare for these requirements, they risk delays, increasing costs and in some cases, failing to meet the UK’s demands.
Lessons Learned: Early CRO Involvement
We have seen the value of early CRO engagement to overcoming the challenges that come with conducting trials and bringing products to the UK.
By bringing our regulatory and quality experts into the planning process early, companies can streamline their pathways. This experience shows that when companies get the right support from day one, they're better equipped to avoid common pitfalls and meet the necessary regulatory standards whether that's in the UK, the EU, or globally.
What Does the Future Hold for Biotechs in the UK?
Looking to the future, the pressure to meet accelerated approval timelines will only grow. Biotechs will need to balance the need for speed with the imperative of maintaining product safety and quality. As
regulatory environments continue to evolve-particularly in the UK-it will become even more important to stay ahead of the curve and ensure that all aspects of compliance are managed from the outset.
Conclusion
The UK biotech sector is growing rapidly and with that growth comes the need for a more nuanced understanding of regulatory requirements. As biotechs expand, regulatory hurdles will become more complex and those who engage with experts early on will be better positioned for success.
By integrating regulatory and trial design and conduct considerations into the development process from the outset, biotechs can avoid unnecessary delays and set themselves up for UK success.
Yvanne Enever
Yvanne Enever, Founder and CEO of PHARMExcel, leads a specialist UK CRO delivering Phase I–IV trials for academia, biopharma and medical device organisations. Formerly at UCL, she established clinical and R&D units. An international speaker and contributor to IAOCR, UK-CLIF, COG and the ICR Forum, Yvanne is a Businesswoman of the Year and co-author in journals including The Lancet.
Regulatory Perspectives on the FDA’s Use of Artificial Intelligence in Drug Development
As artificial intelligence (AI) gains prominence in drug development, regulatory agencies such as the US Food and Drug Administration (FDA) are creating and implementing frameworks to promote the responsible use of AI for medical products. The FDA defines AI as a machine-based system that can, for a given set of human-defined objectives, make predictions, recommendations, or decisions influencing real or virtual environments.1
A perspective article published in JAMA in January 2025 noted that the FDA’s first approval of a partially AI-enabled medical device occurred in 1995 for PAPNET, a software used to prevent misdiagnosis in women undergoing Papanicolaou tests for cervical cancer.2 The article indicated that, since the approval of PAPNET, the agency has authorised approximately 1,000 AI-enabled medical devices. The authors, including former FDA commissioner, Robert M. Califf, MD, stated that to “keep up with the pace of change,” in AI across biomedicine and healthcare, regulators will have to “advance flexible mechanisms.” While the agency has developed a total life cycle approach to support the deployment and innovation of AI-enabled products, industry and other external stakeholders will need to “ramp up,” their evaluation and quality management of AI “beyond the remit of the FDA.”
Efforts to Establish Policies for AI
At the 2025 annual Drug Information Association (DIA) meeting, Tala Fakhouri, PhD, MPH, Associate Director for Data Science and AI at the FDA’s Center for Drug Evaluation and Research (CDER), presented some of the agency’s efforts to establish policies on AI.
She highlighted that CDER has received 800 product submissions with AI components from 2016 to 2024. Since 2019, CDER started documenting the use of AI in regulatory submissions, created a working group, issued discussion papers, and convened several workshops, including those in collaboration with the DukeMargolis Institute for Health Policy in 2022 and the Clinical Trials Transformation Initiative (CTTI) in 2024.3,4
One of the discussion papers described the four main areas of focus regarding the development and use of AI for several of the FDA’s organisations, including CDER, the Center for Biologics Evaluation and Research (CBER), the Center for Devices and Radiological Health (CDRH), and the Office of Combination Products (OCP).5 These areas are to 1) foster collaboration to safeguard public health; 2) advance the development of regulatory approaches that support innovation; 3) promote the creation of harmonised standards, guidelines, best practices, and tools; and 4) support research related to the assessment and monitoring of AI performance.
As another relevant resource, in January 2025, the FDA also published the draft guidance for industry, Considerations for the Use of Artificial Intelligence to Support Regulatory Decision-Making for Drug and Biological Products, which provides recommendations to interested parties on the use of AI to produce information or data to support regulatory decision-making regarding safety, effectiveness, or quality for drugs.6 The guidance outlines a risk-based credibility assessment framework comprising a 7-step process, and it encourages sponsors to “engage early,” with the FDA to set expectations about the framework and help identify potential challenges.
Looking ahead, Fakhouri explained that the FDA will continue to refine its January 2025 AI guidance, which had received 1,450 comments from 98 entities by the time of her presentation. Moreover, the agency will focus on addressing stakeholder requests for issuing guidance on good machine learning practices, harmonising terminology, and engaging with all interested parties, including through a future CTTI workshop in 2025.
Integrating Generative AI for Internal Use
Within the FDA, there has also been a focus on the use of AI internally. On May 8, 2025, FDA Commissioner Martin A. Makary, MD, MPH, announced the completion of an AI-scientific review pilot and shared an “aggressive timeline,” for the agency to deploy a generative AI tool across all FDA centers by June 30, 2025.7 Named Elsa, the tool was launched on June 2, 2025.8 The FDA press release about Elsa explained that it was built within a high-security GovCloud environment and offers a secure platform for FDA staff to access internal documents while housing the information within the agency. Some of the tasks Elsa can perform include summarising adverse events, conducting faster label comparisons, and generating code to develop databases for nonclinical applications, the agency highlighted.
At DIA 2025, Fakhouri provided information on Elsa. She clarified that regulatory submissions would continue being evaluated by humans and that FDA reviewers are generally using Elsa to perform administrative tasks to increase their efficiency. Jeremy Walsh, the FDA’s newly appointed chief AI officer, also offered his perspective, explaining that Elsa is not being trained on data submitted to the agency. This approach ensures that only FDA staff handle this sensitive data. However, he stated that some external stakeholders have expressed interest in training Elsa with this data and that this topic would likely be explored in the future. The FDA panelists at the conference mentioned that the agency is interested in sharing findings and prompts with stakeholders and encouraged collaboration and transparency on the development of AI tools.
REFERENCES
1. Artificial Intelligence and Medical Products. Food and Drug Administration webpage. https://www.fda.gov/science-research/science-and-researchspecial-topics/artificial-intelligence-and-medical-products
2. Warraich HJ, Tazbaz T, Califf RM. FDA Perspective on the Regulation of Artificial Intelligence in Health Care and Biomedicine. JAMA. 2025; 333(3):241-247. https://pubmed.ncbi.nlm.nih.gov/39405330/
3. Understanding AI/ML in the Drug Development Lifecycle. Duke-Margolis Institute for Health Policy. https://healthpolicy.duke.edu/events/ understanding-aiml-drug-development-lifecycle
4. Artificial Intelligence (AI) in Drug & Biological Product Development Hybrid Public Workshop. Clinical Trials Transformation Initiative. https://ctticlinicaltrials.org/type/news/fda-ctti-convening-hybrid-public-workshopon-artificial-intelligence-in-drug-biological-product-development/
5. Artificial Intelligence & Medical Products: How CBER, CDER, CDRH, and OCP are Working Together. Food and Drug Administration. https://www.fda. gov/media/177030/download?attachment
6. Considerations for the Use of Artificial Intelligence to Support Regulatory Decision-Making for Drug and Biological Products. Food and Drug Administration webpage. https://www.fda.gov/regulatory-information/ search-fda-guidance-documents/considerations-use-artificial-intelligencesupport-regulatory-decision-making-drug-and-biological
7. FDA Announces Completion of First AI-Assisted Scientific Review Pilot and Aggressive Agency-Wide AI Rollout Timeline. Food and Drug Administration webpage. https://www.fda.gov/news-events/press-announcements/ fda-announces-completion-first-ai-assisted-scientific-review-pilot-andaggressive-agency-wide-ai
8. FDA Launches Agency-Wide AI Tool to Optimize Performance for the American People. Food and Drug Administration webpage. https://www. fda.gov/news-events/press-announcements/fda-launches-agency-wideai-tool-optimize-performance-american-people
Jennifer Nguyen
Jennifer Nguyen, PhD, is a Senior Content Analyst for the Cortellis suite of life science intelligence solutions at Clarivate. She previously worked as a medical writer, which involved writing and editing scientific journal articles and materials for science conferences. Her current role includes reporting on FDA advisory committee meetings, regulatory policies, and workshops.
Email: jennifer.nguyen@clarivate.com
The Clinical Development Market in APAC: Opportunities, Growth and Challenges
The Asia-Pacific (APAC) region has rapidly emerged as one of the most dynamic markets in global clinical development. Over the past decade, demand for innovative therapies, a large and diverse patient population and favourable government initiatives have transformed APAC into a preferred destination for conducting clinical trials. According to Grand View Research, the APAC clinical trials market was valued at USD 12.1 billion in 2024 and is projected to grow at a compound annual growth rate (CAGR) of approximately 8.4% from 2025 through to 2032.
For biopharmaceutical companies in the U.S. and Europe, expanding into APAC offers significant strategic advantages: faster patient recruitment, reduced operational costs, access to treatment-naive and large populations, with the potential to accelerate drug approvals. Yet, the region also presents challenges, such as complex regulatory frameworks, infrastructure disparities and cultural diversity that can affect trial execution.
This article provides a deep dive into the APAC clinical development landscape, highlights country-specific opportunities, explores drivers of growth and examines the challenges and concerns that sponsors must navigate.
The Evolving Clinical Trial Landscape in APAC
Rapid Market Expansion
The APAC region has become increasingly important in the global R&D ecosystem. As the burden of chronic and lifestyle-related diseases grows, demand for innovative therapies has spurred investments in clinical research infrastructure across the region. Countries like China, India, Japan, South Korea, Australia, Singapore, Thailand, Taiwan and Malaysia now account for a significant share of global clinical trials, with China and India, in particular, seeing double-digit growth in recent years.
APAC has transitioned from being a cost-driven outsourcing destination to becoming a global leader in clinical research innovation. The region hosts over 100,000 active clinical trials as of 2025. China and India dominate in trial volume, while countries like Singapore and Australia lead in regulatory speed and specialised early-phase studies. This list highlights the regional distribution:
Active Clinical Trials by Country (2025)
• China (36,000 active trials) leads due to a huge patient base and regulatory reforms.
• India (18,000) continues to attract large-scale phase III studies.
• Japan (15,000) remains dominant in high-quality trials, particularly oncology.
• South Korea (11,000) has invested heavily in biotech innovation.
• Australia (8,000 trials) is strong in early-phase and oncology studies.
• Singapore (6,000) focuses on precision medicine and rare diseases.
• Thailand (5,500) leverages its medical tourism ecosystem for patient recruitment.
• Taiwan (7,000) thrives in oncology and cell/gene therapies.
• Malaysia (4,000) emerges as a cost-effective destination.
Increased Regulatory Harmonisation
Historically, fragmented regulatory systems were a barrier to efficient trial operations in APAC. Today, initiatives such as the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) and region-specific reforms are streamlining approval timelines. For instance, China’s National Medical Products Administration (NMPA) has dramatically shortened trial approval timelines, while India’s regulatory transformation is encapsulated in the New Drugs and Clinical Trials Rules 2019, a decisive shift from the former Schedule Y. These rules embody a renewed commitment to participant protection, procedural transparency and regulatory agility which creates more simplified processes to attract more foreign-sponsored studies.
Technology Integration
Digital health technologies, including decentralised clinical trials (DCTs), real-world data (RWD) and electronic data capture (EDC), are rapidly transforming trial operations in APAC. Japan and South Korea are helping lead the way in leveraging artificial intelligence (AI) and big data analytics, enabling faster patient recruitment, more accurate monitoring and efficient data collection. The (APAC) region is becoming a global hub for AI-driven clinical trials, leveraging large datasets, diverse populations and government support for AI and digital transformation to accelerate drug development. AI applications in APAC clinical trials include optimising patient recruitment and selection, automating data analysis, improving protocol design and speeding up overall trial efficiency and cost-effectiveness. While facing some ethical and regulatory challenges, the region's strong IT infrastructure, government initiatives like China's ‘Healthy China 2030’ and increasing outsourcing make it a key player in the future of AI in global clinical research.
Drivers of Growth in APAC Clinical Development
Several key factors make APAC a highly attractive region for clinical research:
1. Large and Diverse Patient Populations
APAC is home to 4.5 billion people, nearly 60% of the world’s population. This provides an extensive pool of patients across diverse genetic backgrounds, disease profiles and socioeconomic conditions. For rare diseases and oncology, where patient recruitment is often challenging, APAC offers unparalleled opportunities.
2. Rising Disease Burden
The region faces increasing rates of cancer, cardiovascular disease, diabetes and neurodegenerative disorders. According to the World Health Organisation (WHO), non-communicable diseases account for nearly 74% of deaths in APAC. This surge in demand for effective therapies has created fertile ground for clinical research.
3. Cost-Effective Operations
Operational costs in APAC are generally lower than in North America or Europe. For example, the cost of running a Phase III oncology trial in India can be 40–60% lower compared to the U.S. Lower investigator fees, infrastructure expenses and patient compensation contribute to these savings, allowing sponsors to stretch R&D budgets further.
4. Expanding Clinical Research Infrastructure
Governments across APAC are investing heavily in healthcare infrastructure and research capabilities. High-quality clinical research organisations (CROs), globally recognised hospitals and accredited laboratories now support international standards, making APAC increasingly competitive with Western markets.
Country-Specific Highlights
Japan: Quality-Driven Research
Japan is known for its robust regulatory framework, advanced medical infrastructure and highly experienced investigators. The Pharmaceuticals and Medical Devices Agency (PMDA) has accelerated approval pathways, especially for breakthrough therapies, making Japan a critical hub for precision medicine and rare disease studies. Japan offers a high-quality environment for clinical trials due to its strong regulatory framework, including strict adherence to J-GCP, a well-established healthcare infrastructure and a commitment to patient safety and ethical standards.
Notably, Japan leads APAC in integrating real-world evidence (RWE) into clinical development and offers strong IP protections for innovative therapies. However, high operational costs and slower patient recruitment compared to China and India can limit its competitiveness. An experienced Japanese CRO partner can help in navigating the nuances of this market.
South Korea: Innovation and Technology Integration
South Korea has positioned itself as a leader in clinical trial innovation, driven by government funding and world-class healthcare infrastructure. Seoul, in particular, is a top-ranked city for clinical research globally.
Key Strengths:
• Rapid adoption of AI, big data and decentralised clinical trials.
• High participation rates among patients.
• Strong presence in biologics, cell therapies and oncology trials.
The challenge lies in balancing growing international demand with limited site capacity, which can strain timelines.
Australia: A Gateway to Global Approvals
Australia offers unique advantages, including rapid regulatory approvals, access to highly diverse patient populations and the ability to generate data accepted by the U.S. FDA and European Medicines Agency (EMA). Its Clinical Trial Notification (CTN) scheme allows approvals in as little as 4–6 weeks, making it particularly attractive for early-phase studies.
Government incentives, such as the Research & Development Tax Incentive, further reduce costs, making Australia a preferred destination for first-in-human and adaptive trial designs.
Singapore: Asia’s Precision Medicine Leader
Singapore has evolved into a strategic clinical research hub:
• Regulatory Excellence: The Health Sciences Authority (HSA) offers fast-track approvals in 8 weeks, among the region’s quickest.
• Therapeutic Niches: Oncology, rare diseases and cell and gene therapies.
• Research Infrastructure: Cutting-edge facilities at the Biopolis and partnerships with leading pharma companies.
• Cost Considerations: While costs are higher (85% of U.S. levels), sponsors benefit from superior quality and early-phase capabilities.
Taiwan: Bridging Innovation and Efficiency
Taiwan is increasingly viewed as a gateway for APAC clinical development, particularly for innovative therapies.
Key Strengths:
• Highly efficient and centralised healthcare systems.
• Strong track record in oncology, immunology and rare diseases.
• Highly educated clinical research workforce and advanced hospital networks.
Taiwan’s balance of speed, cost and quality makes it a hidden gem for sponsors seeking high-value trial environments.
China: The Regional Powerhouse
China has emerged as a clinical research leader, fueled by government reforms, significant investment and a growing biopharma ecosystem. The NMPA’s regulatory modernisation and China’s accession to ICH standards in 2017 reduced trial approval times from 12–18 months to as little as 60 days.
Key Trends in China:
• Strong growth in oncology and rare disease trials.
• Increased acceptance of foreign-sponsored studies.
• Accelerated approvals through programs like the Priority Review Pathway.
However, navigating China’s regulatory environment still requires local expertise and partnerships, including an experienced APACbased CRO, particularly given evolving data privacy laws.
India: A Cost-Competitive Hub
India combines a large patient pool, cost advantages and skilled investigators, making it one of the fastest-growing clinical trial markets globally. After a slowdown earlier in the decade due to
ethical concerns and regulatory scrutiny, reforms introduced in 2019 revitalised the industry.
Key Advantages Include:
• Access to treatment-naive patients across multiple therapeutic areas.
• Clinical trial costs up to 60% lower than Western counterparts.
• Government incentives to attract foreign sponsors.
Challenges remain around infrastructure variability and ensuring consistent adherence to Good Clinical Practice (GCP) standards, particularly across rural regions.
Thailand: A Rising Medical Research Destination
Thailand is gaining attention for its affordable trials and large patient pool:
• Medical Tourism Advantage: With over 3 million international patients annually, recruitment is streamlined for certain therapeutic areas.
• Therapeutic Strengths: Infectious diseases, oncology and regenerative medicine.
• Regulatory Framework: Approval timelines average 16 weeks.
• Cost Efficiency: Trials are 40% cheaper than in the U.S., making Thailand attractive for late-phase studies.
Malaysia: An Emerging Cost-Efficient Hub
Malaysia is rapidly positioning itself as a cost-effective alternative for sponsors targeting Southeast Asia.
Key Strengths:
• 55% lower trial costs than U.S. averages.
• Multilingual workforce and strong government backing for biopharma growth.
• High prevalence of diseases like diabetes and cardiovascular conditions, enabling rapid recruitment.
While smaller in scale, Malaysia’s strategic location, cost advantages and growing clinical infrastructure make it increasingly attractive for global trials.
Challenges and Concerns
While APAC presents compelling opportunities, sponsors must address several key challenges:
1. Regulatory Complexity
Despite progress, regulations still vary significantly across APAC countries. Sponsors must manage inconsistent timelines, language barriers and data-sharing rules. For example, China’s data localisation requirements can complicate global data integration.
2. Infrastructure Disparities
Although major cities boast world-class research facilities, rural areas often lack adequate resources. Ensuring uniform trial quality and compliance across diverse geographies remains a challenge.
3. Ethical and Cultural Considerations
Cultural attitudes toward clinical research vary widely. In some countries, patient scepticism and limited awareness about clinical trials can hinder recruitment efforts.
4. Counterfeit Drugs
In some APAC markets, the presence of counterfeit drugs poses a
direct threat to patient safety and drug quality. Collaboration between international regulatory agencies, such as the FDA and EMA, can help in knowledge-sharing, strengthening quality assessments and inspections globally.
5. Supply Chain Risks
Over-reliance on certain pharmaceutical suppliers and potential vulnerabilities in the supply chain can affect the quality and availability of ingredients and finished products. Organisations like ISPE and PDA are helping to improve quality management practices in pharmaceutical manufacturing, potentially leading to fewer defects and recalls.
6. Data Privacy and Compliance
Evolving data protection laws, such as China’s Personal Information Protection Law (PIPL), require careful planning around data collection, transfer and storage to remain compliant.
7. Intellectual Property and Quality Concerns Across Some Countries
Conducting clinical trials in China may present challenges for intellectual property (IP) protection, particularly for foreign
biopharmaceutical companies. Awareness creates opportunity for improvement.
While significant efforts, including the New Drugs and Clinical Trials Rules 2019, aim to address these issues by improving Good Clinical Practice (GCP) standards and ethics oversight, the ongoing quality of trials depends on continued regulatory consistency, robust infrastructure, better-trained personnel and a deeper understanding of ethical principles to ensure participant protection.
Overcoming Challenges
The focus on improving the quality of pharmaceutical clinical development in APAC is a keen area of focus for 2025 and beyond. However, obstacles such as standardising adherence to international regulations and improving local regulatory systems will remain key focus areas.
The trajectory of APAC's pharmaceutical market remains strong and addressing quality concerns will be paramount to ensuring patient safety and the growth potential of this key market.
The Future of Clinical Development in APAC
Looking ahead, APAC’s role in the global clinical development ecosystem is expected to grow significantly. AI, decentralised trial models and real-world evidence will drive efficiencies, while continued regulatory reforms and infrastructure investments will enhance competitiveness.
Partnerships between global sponsors, local CROs and healthcare institutions will be critical to navigating the region’s complexities. Biopharma companies that adopt a region-specific strategy, embrace technology and invest in patient engagement will be best positioned to capitalise on APAC’s growth potential.
Conclusion
The Asia-Pacific region offers an unparalleled opportunity for clinical development, combining vast patient diversity, rising disease prevalence, cost efficiency and increasing regulatory harmonisation. While challenges persist, from navigating complex regulations to ensuring consistent quality, APAC’s clinical trials market is poised for sustained, long-term growth.
For U.S. and European biopharmaceutical companies, success in APAC requires more than simply entering the market; it demands a deep understanding of local ecosystems, strategic partnerships and adaptive operational models. By leveraging the region’s strengths and proactively addressing its challenges, sponsors can accelerate drug development timelines and bring innovative therapies to patients faster.
REFERENCES
1. Grand View Research, Asia-Pacific Clinical Trials Market Report 2025.
2. GlobalData Clinical Trials Intelligence 2025
3. ClinicalTrials.gov 2025
4. World Health Organization (WHO), Global Health Observatory Data
Clareece West, President and Chief Commercial Officer, Linical, is a veteran in the global clinical research industry, having worked in leadership positions across health technology, two Fortune Top 10 companies and large CROs. She has over 20 years of executive leadership experience, including global clinical and commercial operations across numerous therapeutic areas, regulatory, data management, safety, change management, international sales, proposals and marketing, M&A, P&L and restructuring expertise. Clareece is passionate about integrating technology into clinical research, improving the execution of global clinical trials and enhancing patient outcomes.
Alison Cundari
Alison Cundari, Senior Director Marketing and Corporate Communications, Linical, is a seasoned marketing leader with over 15 years of experience in clinical research and the pharmaceutical industry. She specialises in driving strategic growth through integrated marketing, corporate communications and data-driven digital strategies, including SEO, social media and targeted advertising. Passionate about advancing patient-centric innovation, sustainability and the future of clinical research, Alison brings a unique perspective on emerging trends shaping the clinical development market.
Challenges in the Post-marketing Investigations for Medical Devices
As the European and overall worldwide regulation strives to become clearer, unambiguous, harmonised and as a result, more restrictive and demanding, this tendency still seems to leave behind the post-marketing studies for medical devices.
The European Union Medical Device Regulations 2017/745 entered into force in May 2021 and significantly improved the clarity about the expectations imposed on manufacturers in the post-marketing period.
The MDR’s increased requirements for clinical evaluation aim to ensure safer medical devices for consumers and users. However, this in parallel, leads manufacturers to new challenges related to the preparation of robust Clinical Evaluation Reports for their medical devices.
The possibility of some undesired consequences for the European market is a highly discussed topic, as for some manufacturers, the cost of generating the required clinical data will outweigh the potential return on investment. Consequently, the manufacturers may discontinue certain medical devices or remove them from the EU market, leading to a device shortage.
The general consensus among manufacturers is that the heightened requirements for clinical evaluation, particularly for high-risk medical devices, which had not been present to this extent before, are creating challenges.
The necessity to perform clinical investigations in the postmarketing period becomes evident in some cases, while in others, the manufacturers would rather avoid such and a resort, to alternative methods of data collection.
Still, everyday practice proves to provide numerous scenarios and topics that lack consideration in the regulation.
Challenges Related to the Data Collection Programme for CER Determining the scope and amount of data needed to generate sufficient clinical evidence, accepted by the respective Notified Body, is one of the most prominent challenges in the eyes of the manufacturers.
Per the MDR, ‘clinical evaluation,’ means a systematic and planned process to continuously generate, collect, analyse and assess the clinical data pertaining to a device in order to verify the safety and performance, including clinical benefits, of the device when used as intended by the manufacturer.
The clinical evaluation, its results and the clinical evidence derived from it shall be documented in a clinical evaluation report with only limited exceptions.
Determining the appropriate data sources can prove to be a challenging and time-consuming process. On the one hand, the manufacturers struggle with some uncertainty regarding the regulatory expectations. Some inconsistencies have been suggested in the amount of clinical data accepted by the different notified bodies. Still, there are no actual guidelines on what constitutes sufficient clinical evidence, hindering all stakeholders and possibly leading to exceeding expectations or wasting time in evaluating insufficient reports.
This is particularly true for manufacturers with medical devices that changed their class due to the MDR's new classification rules and even products that were previously considered a cosmetic product but are now under the MDR jurisdiction. Such manufacturers had to initiate processes that were not previously required for products that had been on the market for years. There is less uncertainty for the high-risk or invasive medical devices, as they are under stronger regulatory oversight and rigorous requirements.
Identification of the Most Appropriate Clinical Evaluation Pathway
On one end of the spectrum is opting for a safer method to collect high-quality data from a comprehensive PMCF investigation, which can ensure the acceptance of observations, but it demands significant resources, including time. In some cases, a market shortage may occur because a device is recalled while under proactive observation.
Choosing methods that depend on less relevant sources, like complaints or vigilance systems, increases the risk of not sufficiently justifying the device's safety and performance assessment. Overreliance on reactive data may lead to rejection by the Notified Bodies.
Reactive or Proactive PMS Data?
Reactive PMS data are passively collected information, sourced by external unsolicited sources such as complaints, vigilance reports, etc. In contrast, Proactive PMS data are actively, deliberately and systematically gathered. This may include PMCF, including studies, users or consumers surveys, structured literature review, etc. The MDR requires manufacturers to integrate both within their programme to confirm persistent safety and performance, with emphasis on proactive data.
Reactive PMS data alone is insufficient, and often it is hard to obtain. In Europe, there are still no publicly available consolidated data sources. Depending on the region, the doctors and the patient are, to various degrees, unaccustomed to using the vigilance systems. Unfortunately, this raises doubts that the lack of complaints genuinely reflects the real picture of the device's safety and performance.
The MDR requires manufacturers to actively and systematically gather, record and analyse relevant data (information). Thus, Proactive data collection is essential to confirm the benefit-to-risk,
in-real-world clinical performance, and safety throughout the medical device's lifecycle.
In summary, Proactive PMCF activities are mandatory for Class III medical devices. Class IIa and IIb devices typically require proactive PMCF activities, unless properly justified otherwise.
Considered from the perspective of the Notified Bodies, the Reactive PMS data is necessary and valuable, but can be regarded as the bare minimum, as this is generally expected for any product on the market.
The Proactive PMS data is considered capable of demonstrating the actual features of the clinical evaluation, controls, and risk minimisation. Therefore, the absence of such data can be regarded as non-conformance with the MDR.
Types of Post-marketing Clinical Follow-up
As specified in the MDR, the PMCF is a part of the clinical evaluation plan. It consists of a proactive, systematic process to confirm the device's safety and performance through its expected lifetime. The PMCF can take different forms, from surveys and registries to an entire PMCF investigation. The PMCF aims to ensure the continued acceptability of the benefit-risk ratio, identify the residual risk, uncertainties, rare adverse events, long-term outcomes, possible systematic misuse and potential off-label use.
The types of PMCF activities, besides the investigation, are noninvestigational but structured. The robustness of the generated data may vary significantly based on the quality of the data source and the applied methodology. The latter is being scrutinised by the Notified
Bodies when observing such data. Still, outside of a dedicated clinical investigation, the data may lack completeness and there can be bias issues.
Challenges In the Course of a PMCF Investigation
The PMCF investigations are prospective, interventional or noninterventional clinical investigations, conducted with CE-marketed devices, designed to address PMCF questions specifically. Depending on the level of intervention (deviating from the scope of the device’s labelling), they may fall under different local jurisdictions and aid different goals.
It is widely accepted that the proactive, dedicated clinical investigations, particularly if they are well-designed and executed, would allow the collection of data with the highest quality. The prospective design, frequently including a control group or well-defined endpoints, produces data with the highest robustness.
However, the most prominent disadvantages of the PMCF investigations are that they are costly and time-consuming. Aside from the significant resource consumption for the manufacturers, there are some other considerations to be accounted for.
Some high-risk medical devices, such as implants, cardiovascular, etc., are often intended for a small, highly specific patient population. However, sample size justifications follow strict rules, regardless of the struggles to recruit the investigated population within any particular deadlines or the investigation type (pre- or post-marketing). In contrast to the initial clinical investigation, which is typically conducted with narrower inclusion and exclusion criteria, a post-marketing clinical investigation should have no such criteria, outside the requirements of
the in-force Instructions for Use of the product. This may lead to the impression of easier enrolment, but in fact bears additional challenges and consequences. For instance, the compliance is lower, the diverse patient population may pose difficulties in data analysis, etc. Thus, patient recruitment to reach statistically meaningful results can be either time-consuming or expensive, but mostly both.
A not uncommon scenario is an initial clinical investigation, performed for the primary purpose of obtaining a CE mark, lacking some key features, in particular, long-term safety observations or a sufficient patient count to make assumptions about rare adverse events or device deficiencies. This is especially true in the case of initial clinical investigations conducted under MDD/AIMDD. Conducting a PMCF investigation might necessitate substantial follow-up long after the device's actual use has concluded. However, patient compliance is known to decline when they no longer see any direct benefit from this process.
Depending on local legislation requirements, medical devices used for post-marketing investigations can be supplied by the manufacturer, but in most cases, they are self-funded by the patients. This presents another challenge for recruitment from several angles. If the manufacturer supplies the medical devices, it could impose an extra financial burden. If funded by the patient, it could cause delays in recruitment, as some medical devices are expensive. The issue is even more challenging for devices used for extended periods, primarily when employed as a treatment regimen following a strict schedule or when treatment needs to reach a specific frequency to meet the ‘per the indications,’ criteria.
And finally, the newly MDR-imposed requirements to perform post-marketing investigations are still met with reluctance by some stakeholders and other approaches are prioritised.
Lack of Harmonisation for the Post-marketing Investigations
The clinical investigation is the subject of a written authorisation by the Member State(s) in which the clinical investigation is to be conducted, in accordance with the MDR. An ethics committee, set up in accordance with national law, has not issued a negative opinion in relation to the clinical investigation, which is valid for that entire Member State under its national law. These two processes follow the submission of the Clinical Investigation Application, as specified in Article 70 and in Chapter II, Annex XV of the MDR.
The same documents regarding the application for clinical investigation, excluding some items from the list, apply for the PMCF investigations under Article 74 of the MDR. The package is expected to be submitted as a notification to the Member State(s) concerned.
However, Article 74 does not consider all possible types and variations of the PMCF investigations, and the requirements of the local legislations are pronouncedly lacking in harmonisation.
There are cases where a disconnect exists between the understanding of sufficient data by the agencies approving the clinical investigations (RAs and ECs) and the entities issuing the CE marking (the Notified Body). The mere approval of a Clinical Investigation Application does not guarantee in any case that the data generated will be deemed sufficient, or that the investigation design will be deemed appropriate by the Notified Body.
In conclusion, serious challenges are being faced by medical device manufacturers in demonstrating compliance with the MDR. From the time of its first launch, the MDR placed particular weight on the high-risk devices, which led to quicker and more effective onboarding
of these manufacturers with the requirements, in comparison to the medium-risk device manufacturers.
For more and more cases, the manufacturers will have to go through an actual PMCF investigation to satisfy the clinical evidence expectations sufficiently.
Dr. Dilyana Stoeva
Dr. Dilyana Stoeva has been the Medical and Regulatory Affairs Manager at Ramus Medical since 2012, overseeing all aspects of CT planning and execution while ensuring compliance with national and international standards and industry best practices. With a strong background in medical writing, regulatory strategy, and project management, she has contributed to over 40 CTs across all trial phases and various therapeutic areas.
Dimitar Mihaylov
Dimitar Mihaylov, PhD, is the Business Development Manager at Ramus Medical, committed to identifying growth opportunities, building strategic partnerships and expanding market presence since the company's creation in 2010. With strong marketing experience, he drives business initiatives that enhance Ramus Medical's competitiveness and long-term success.
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Harmonising Global Approaches to Transformative Theranostics
Cancer prevalence is rising globally. Radiopharmaceuticals and Theranostics offer precise, targeted diagnostic and therapeutic solutions for safer, more tolerable oncology therapies. Implementing a successful radiopharmaceutical program in any institutional practice or trial setting requires meticulous planning across several domains and seamless integration with oncology workflows for timely and accurate patient care.
This article explores the landscape, regulatory considerations, infrastructural and operational requirements along with future directions for expanding these therapies into clinical settings.
Current Landscape
Radiopharmaceuticals and theranostics have a rich history and promising applications for targeted therapies in oncology. As such, the global radiopharmaceuticals market has a projected compound annual growth rate (CAGR) of 9.8%, estimated to reach $19bn by 2035.1 Large pharma and biotechs alike are pushing innovation around radiopharmaceutical agents, with the recent development of more efficient alpha-emitting isotopes paving the way for new therapies.
At the centre of this transformation is theranostics, an approach that uses the same molecular target for both imaging and treatment. This enables personalised, precision medicine while minimising harm to healthy tissues.
Iodine-131 MIBG NET Sympathetic Tumors Pheochromocytoma/ Neuroblastoma
Radium -223 Bone Bone Metastasis
Table 1: Currently Approved Theranostic Pairs
As the market grows and milestone approvals of therapies like Lutathera and Pluvicto prove clinical value, the focus shifts to how we can translate this innovation into scalable, accessible clinical practice. For all stakeholders involved, from pharmaceutical developers to academic institutions and healthcare providers, the path to implementation is complex.
Foundations for Radiopharmaceutical Progress
Successfully delivering a radiopharmaceutical therapy or trial requires robust infrastructure, highly trained personnel and strict regulatory compliance.
Key Institutional and Clinical Trial Requirements Include:
• Specialised infrastructure, such as PET/SPECT scanners, shielded injection rooms, radiopharmacy facilities and radioactive waste management systems
• Reliable isotope supply chains, including access to reactor and cyclotron-produced isotopes, as well as portable generators for on-site availability
• Rigorous quality control, including radionuclide purity verification, dose calibration and precise documentation
• Expert teams, composed of nuclear medicine physicians, radiopharmacists, physicists and radiation safety officers, all trained in proper handling and dosimetry
• Integrated workflows, aligning nuclear medicine with oncology teams through shared protocols and multidisciplinary tumour boards
Infrastructure and Isotope Supply
The infrastructure within supply chain and at clinical sites present the primary hurdles for radiopharmaceuticals and theranostics research and development. Most medical isotopes are produced in a handful of aging reactors concentrated in North America and Europe. Isotopes like Gallium-68 and Actinium-225 have short half-lives, requiring rapid, local production and reliable transportation infrastructure. Investments and innovative alternatives in production are decentralising the process and public-private partnerships are scaling access and stabilising supply chains.
Stable supply chain then leads to the second infrastructural level –site and institutional capacity. Sites need specific, appropriate equipment, quality control procedures, radioactive waste management strategies and thorough training in delivering and managing radiopharmaceutical therapies. Even for high-resource sites, the initial investment in building out the proper facilities, teams and procedures can be a significant obstacle.
Institutions must consider both short-term implementation costs and long-term sustainability models when adopting theranostic programs.
Workforce and Workflows for Radiopharmacy
Upskilling and aligning cross-specialty teams is essential for safe, efficient and effective deployment of radiopharmaceutical therapies. There is a shortage of professional trained in the specific roles required for radiopharmaceuticals, including nuclear medicine physicians, radiopharmacists, radiation safety officers
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Regulatory Affairs
and medical physicists. Cross-disciplinary training programs and theranostic-specific certification and CME modules, like those offered by SNMMI and EANM can strengthen our collective pool of expertise and harmonise approaches.2 Additionally, deeper integration with oncology and tumour boards will help close the gaps and improve patient selection and care timelines.
Radiation Education
Despite the safety and tolerability of modern radioligand therapies, the stigmas and fear attached to the term ‘radiation,’ can be challenging for patients and participants to overcome. However, radiopharmaceuticals differ from the external beam radiation therapy that is the focus of public concern. Radiopharmaceuticals primarily cause cell death through direct DNA damage (single- and double-strand breaks) and indirect effects such as immune stimulation and theranostic innovations are driving more precision treatments to minimise risk to healthy tissues.
Education campaigns and patient advocacy organisation involvement can help reduce public fear while integrating decision aids and transparent risk-benefit discussions into clinical workflow can help to support informed participant choices. Normalising radiopharmaceuticals as mainstream, safe and effective cancer treatments will be important for participants as well as clinicians, which can impact referrals and clinical trial participation.
Radiopharmaceutical Regulations
The rapidly evolving regulatory landscape for radiopharmaceuticals is complicated by the unique classification of the therapies – they are simultaneously classified as drugs, radioactive substances and medical devices.
Regulatory guidance is becoming more refined, with the FDA’s 2022 guideline for radiopharmaceuticals in rare diseases streamlines preclinical and trial design processes and the EMA’s 2024 draft guidance, which aims to harmonise expectations for early-phase trials, combination regimens and dosimetry validation. The IAEA and WHO, as well as multi-stakeholder working groups led by professional societies, are working toward globally harmonised, adaptive frameworks that will be essential to supporting radiopharmaceutical development.
Toward an Integrated Ecosystem
Radiopharmaceutical programs are capital, resource and research-
intensive. While breakthroughs are driving accelerated evolution in the field, the investigational agents are mostly accessible only to academic centres in high-income countries, thereby limiting the potential progress and data generation. The restriction also perpetuates global access inequities.
A globally distributed research ecosystem is essential to ensure the equitable development and validation of radiopharmaceutical therapies. CROs with expertise in radiopharmaceutical logistics can play an important role in creating and connecting global trial networks, both with personnel relationships and with technology-enabled decentralisation, monitoring and real-time dosimetry. Integrated digital tools can improve trial inclusiveness and representative population data, create time and cost-saving efficiencies and improve safety monitoring.
Achieving the potential of theranostics on a global scale will require concerted efforts from stakeholders, including policymakers, developers, CROs, academic medical centres and payers. Each party must align to build scalable and patient-centric programs that can realise the transformative potential of radiopharmaceuticals.
2. Certification and CME modules in theranostic techniques and safety protocols are offered by SNMMI and EANM
Dr. Divya S Mishra
Dr. Divya S Mishra is a Radiation Oncologist with over 19 years of experience in Clinical Practice, Medical Affairs, Regulatory support and Therapeutic Expertise of Industry-driven clinical trials of various Cancer Drugs, Radioenhancers and Radiopharmaceuticals across phase 1–4 settings. With a strong focus on driving strategic initiatives to enhance efficiencies across clinical research and healthcare settings, Dr. Divya is deeply passionate about the cause of making better and safer medicines available to cancer patients worldwide.
Supercharging Rare Disease Drug Development Through Human Connection
Drug development commonly encounters a bottleneck at the clinical trial stage. Patient recruitment is notoriously challenging, with many studies facing costly delays, but for rare disease trials, these challenges are often exacerbated. Without the right support, trials risk early termination, a potentially devastating result for those who already have few treatment options available. Many trial sponsors and sites look to new technology to overcome these barriers, but now, more than ever, we need human connection to help secure studies’ success and ensure innovative treatments reach those who need them.
For the life sciences sector, rare disease is somewhat of a paradox. To be classified as such, the general consensus among countries is that there must be extremely low prevalence within their territories. And yet collectively, hundreds of millions of people live with a rare disease worldwide, making it a decidedly common occurrence.
Despite the longstanding need for effective, approved treatments, relatively few have materialised. The reasons for this are complex, but with biopharmaceutical companies typically facing higher costs, a slower rate of progress and a higher risk of failure for rare disease drug development compared with other conditions, it is arguably not surprising. The often complex, genetic nature of rare conditions can make drug discovery challenging, but the clinical trial stage is often the most problematic. Studies generally struggle to enrol enough patients; it is generally accepted that about 80% of all trials fail to reach their recruitment target on time and this can be compounded for rare disease studies, where the patient pool is far smaller. Even once enroled, the many financial, physical, clinical and social hurdles faced by those living with these conditions can make it difficult for them to sustain their participation through to the endpoint. Without enough patients involved, the trial will terminate early. Without the necessary data to pass regulatory approval, patients will no longer be able to access a potentially life-changing treatment. Without a new treatment on the market, sponsors will be left with exorbitant costs and no opportunity for reimbursement.
Technological advancements in recent years have brought forward a focus on how to make the drug development process more efficient and cost-effective, including for clinical trials. Net Treatment Benefit (NTB), for example, is an interesting concept with the potential to accelerate studies using fewer patients. Meanwhile, conversations abound about how Artificial Intelligence (AI) models can help identify patients faster and improve diversity by analysing patient records and ease the burden on busy research sites by automating workflows and personalising communications. But it doesn’t matter how many participants you need for your study or how quickly you can identify them; the challenges associated
with patient recruitment and retention often remain the same. These include:
• The perceived burden that a study will have on a patient.
• Not understanding the purpose of clinical trials or what’s involved.
• Mistrust of pharmaceutical companies.
• Cultural barriers, including language barriers.
• A poor relationship between doctor and patient.
The key to success here is building patient-centricity into enrolment and retention strategies from the outset and using human connection to power the type of empathetic engagement that keeps patients feeling respected, heard and involved from start to finish.
Rare Disease Drug Development
About 10,000 rare diseases have been identified to date, of which most have a genetic origin, necessitating a need for cutting-edge treatments. However, the limited market size for rare disease drugs and the typically lower Return on Investment (ROI) they generate as a result, has previously disincentivised pharmaceutical drug development. This has contributed to a so-called ‘healthcare gap,’ where those living with a rare condition must first overcome lengthy diagnosis delays before facing a future with limited, if any, treatment options.
Thankfully, global institutions, including national governments, recognise the importance of addressing this healthcare inequality and there is widespread acknowledgement that meeting the clinical needs of people living with a rare disease is necessary if we, as a global community, are to achieve universal health coverage. This includes access to effective therapies. However, the pathway to bringing new treatments to market is rarely smooth. When it comes to clinical trials, patient recruitment is one of the biggest hurdles to overcome. Even for studies focusing on far more common indications, research sites often struggle to balance their busy workloads and dedicate the time and resources required to find, reach and follow up with potential participants. Any delay to a clinical trial, of which poor enrolment is a common cause, can result in significant costs for sponsors, with estimates ranging from 540,000 USD to potentially millions of dollars per day. Inadequate patient recruitment may even risk the future of the treatment in question; it is often cited as one of the most frequent reasons for early termination, including for rare disease studies.
Considerations for Patient Recruitment in Rare Disease Trials
Due to the low prevalence of each rare disease, it is inevitable that finding suitable people to take part in your study will be more labour-intensive and likely to take more time. AI systems have the potential to help here, analysing datasets and medical registries quickly to identify potential study participants, but there remains a need for site staff to follow up and assess each person’s suitability.
Ensuring patient diversity in trials, now rightly recognised as best practice, can also lengthen the recruitment process. In days past, studies were typically powered by middle-class white men, resulting in a paucity of data relating to a treatment’s efficacy in women, disabled people and people of colour. Regardless of the study’s indication, it is important to consider who the condition affects and ensure all groups are involved.
About three-quarters of all rare diseases affect children, so there is a need for paediatric studies. However, these are known for being more difficult to recruit to. It is imperative that children and their families and caregivers are given bespoke study materials that give them the information they need in a way they understand to help them make informed decisions.
Another consideration is the often significant medical and non-medical burden that people living with a rare disease and their families and caregivers have to bear, which could affect their ability to participate in a clinical trial. They may require more frequent healthcare-related appointments, assistive technology or wider care. It may be harder or more costly for them to travel. Balancing patients’ needs with the requirements of a clinical trial is imperative if patients are to enrol on a trial and stay involved.
Even once recruitment is complete, the job is still not finished. Patient retention is critical. If people don’t feel engaged or find participating too much of a burden, they are likely to drop out and be lost to follow-up. Roughly 30 per cent of study participants will drop out, costing sponsors an additional 19,500 USD or more to replace them. If too many people choose to stop participating, the study could fail as the results would no longer be reliable.
The Power of Empathy
The rise of AI and Machine Learning (ML) technology has exciting potential to streamline and accelerate the process of drug development, including clinical trials. But human connection remains a cornerstone of effective patient recruitment and retention.
We already know that patient-centric trial design will improve people’s overall study experience, alleviating some of the hurdles that might otherwise make it near impossible for them to participate. In turn, this can make recruitment and retention easier, giving patients faster access to a potential new treatment and saving sponsors time and money. But patient-centricity without empathy can only go so far; without it, patients eventually risk feeling devalued and dismissed rather than heard and respected.
Studies demonstrate time and again that empathy has a transformative effect on patient behaviour and clinical outcomes. Patient satisfaction and treatment adherence are generally higher, the doctor-patient relationship is deepened, and emotional wellbeing is often greater. This relationship between patient and clinician is especially important for clinical trials. Many prefer to be referred by their primary care doctor or community-based practitioner whom they trust, although the overall referral rate via this avenue remains low.
The same is true for research staff with whom patients have a good rapport. It is therefore crucial to approach any interaction through a lens of patient-centricity, but empathy is the secret ingredient to establishing a connection with patients and building a trusted relationship, both of which are key to continued participation.
Therapeutics
Transforming Patient Engagement
For effective and sustained patient engagement that enables enrolment and retention, the first step must always be to start with patient-centricity. If the patient perspective is not at the heart of any clinical trial, recruitment and retention will always be so much harder to achieve. Studies should take patients’ needs fully into account and consider how to make it as easy as possible for them to take part, particularly those that focus on rare diseases, where patients typically have more obstacles to navigate. Engage patients as partners in the study design process; reach out to Patient Advocacy Groups (PAGs), charities and support groups and seek direct patient feedback at the earliest opportunity to guarantee studies enable and empower patients to participate and stay involved. Demonstrating empathy through trial design in this way is an important first step. If done correctly, it should naturally seep into patient materials and other forms of communication.
Training is also an essential component. Many sponsors may not come into direct contact with patients, but it’s important if they are to understand the needs and challenges of those they are seeking to help. Likewise, empathy training for research staff is crucial to help them connect with patients more deeply. Empathy is essentially a skill; some people may find it harder to demonstrate than others, but it can be learned and developed with practice. Consider how this kind of training and education can help strengthen understanding and enhance staff empathy and emotional intelligence. For sites, combine this with training focusing specifically on study materials to level up patient communication. Ensuring staff fully understand what the trial entails, combined with an empathetic approach when speaking to potential participants, should boost staff confidence and make it easier for them to connect with patients on an emotional level.
Clinical trial patient recruitment strategies should absolutely embrace new technologies that can accelerate the process, minimise drop-out risks and reduce the burden on sites, but this should always be balanced with the need for human connection. Community engagement, especially when targeting people from underrepresented ethnic groups, is still an effective method, albeit more time-consuming. Don’t rely on healthcare settings to reach potential patients, visit communities where people live, work and socialise. Speak to community-based groups, healthcare professionals and even faith leaders. Target non-healthcare settings like nail and hair salons, cafes or gyms. Use active listening, not just for community engagement, but in all communication with patients throughout the trial, and be a supportive cheerleader for them.
When it comes to healthcare, patients want and need to feel valued, respected and heard. Some technologies, like chatbots, may be able to provide automated responses to study-related queries, but sometimes patients may just want to talk to someone. Be a listening ear; focus on what they are saying and respond to them with empathy. Show that you hear them. In a world of automation, be the difference for patients.
Of course, human connection can often take more time than research staff have available and there is a danger it can fall by the wayside. To alleviate this risk, consider outsourcing to a trusted vendor. Choose an organisation with experience in direct and sustained patient recruitment, retention and engagement to enable sites to concentrate on other areas of the trial and patient care.
In this increasingly digital world, empathetic engagement remains a key component of clinical trial patient recruitment and retention. Combining human connection with AI capabilities
will optimise patient recruitment and retention strategies, reduce drop-out and subsequently increase data reliability for the regulatory stage. This not only reduces costs for trial sponsors but will ultimately help get life-changing drugs to those patients who really need them more quickly.
REFERENCES
1. Fermaglich, L. J., & Miller, K. L. A comprehensive study of the rare diseases and conditions targeted by orphan drug designations and approvals over the forty years of the Orphan Drug Act. Orphanet Journal of Rare Diseases, 18(1) (2023). https://doi.org/10.1186/s13023-023-02790-7
2. https://rarediseases.org/rare-diseases/, visited 11 August 2025.
3. Rees, C. A., Pica, N., Monuteaux, M. C., & Bourgeois, F. T. Noncompletion and nonpublication of trials studying rare diseases: A cross-sectional analysis. PLoS Medicine, 16(11), e1002966 (2019). https://doi.org/10.1371/ journal.pmed.1002966
4. Alexander W. The uphill path to successful clinical trials: keeping patients enroled. P T. 38(4):225-227 (2013). https://www.ncbi.nlm.nih. gov/pmc/articles/PMC3684189/ https://www.clinicalleader.com/doc/ understanding-clinical-trial-patient-attrition-0001, visited 10 August 2025.
Kate Shaw is Co-Founder and CEO of Innovative Trials, an internationally renowned clinical trial patient recruitment and retention company. She has more than 20 years’ experience in patient recruitment support for clinical research and has achieved widespread recognition for her work. In 2024, Kate was awarded the ‘Woman in Pharma,’ award at the Pharma Industry Awards UK for her commitment to advancing science and inspiring more women into STEM.
Email: kate.shaw@innovativetrials.com
Kate Shaw
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Beyond Enrolment: How Community-Based Oncology Practices Drive Patient Retention in Early-Phase Trials
Recruitment remains a well-known hurdle in Phase 1 oncology clinical trials, but what happens after enrolment is equally vital: patient retention. Keeping patients on a trial through its duration presents an equally critical challenge that directly impacts study validity, operational efficiency and future patient willingness to participate in research.
For oncology trials, retention operates on two distinct but interconnected levels: maintaining patients on specific protocols and retaining them within research programs as they transition between treatments.
Retention challenges are especially pronounced in early-phase oncology trials, where visit schedules are intense, procedures are demanding and the emotional weight of participation is high. When patients drop out of trials prematurely, sponsors face delayed timelines and inflated costs. A study designed for 100 completed participants may require enroling 150 patients to account for dropouts, extending recruitment periods and resource allocation. More concerning, early departures due to poor experiences can sour patients on future trial participation, creating a ripple effect that extends beyond individual studies.
Despite these challenges, some sites consistently achieve high retention. Understanding how they do it can offer lessons for improving the design, conduct and patient experience of oncology trials across the board.
Understanding Why Patients Drop Out
Retention failures in oncology trials often stem from a mismatch between patient expectations and trial demands. In Phase 1 studies, patients are frequently required to attend weekly visits, some lasting six to ten hours. These long days often include blood draws, cardiac monitoring and in some cases, invasive procedures such as biopsies. Without clear communication upfront, participants may not anticipate the full burden until they arrive, leading some to withdraw early.
Side effects from investigational drugs present another challenge. If patients experience unexpected toxicity and aren’t adequately prepared for how it will be managed, they may opt to discontinue. Clear, anticipatory guidance around side effect management is critical.
The logistical barriers extend beyond the clinic walls. Many patients travel significant distances for specialised care – some driving three hours each way for weekly appointments, which can become a significant barrier if not proactively addressed. Work schedules, caregiving responsibilities and transportation costs create additional friction points that can derail participation.
The psychological dimension compounds these practical challenges. Patients entering Phase 1 trials often arrive after learning their current treatments have failed, creating anxiety that experimental therapy amplifies. Unlike standard oncology care with monthly visits, research protocols thrust patients into unfamiliar environments with new teams, procedures and uncertainties.
Retention, then, is not just a matter of patient willingness. It’s shaped by how well the trial integrates into the patient’s life or fails to.
What Works: Retention Strategies That Make a Difference
Community-based oncology practices have developed targeted strategies to address retention barriers within their sphere of control.
• Patient-Centric Preparation:
This approach begins before patients enter the clinic, with comprehensive preparation that sets the foundation for positive experiences. Research teams obtain each patient’s complete medical records, review previous treatments and side effects and identify potential trials in advance. Patients are more likely to stay engaged when they feel their situation is understood and that they’re not just another case file.
• Clear Communication:
Clear, honest communication is essential. Setting expectations about visit schedules, potential side effects, and time commitments – well before the first appointment – can prevent surprises that might otherwise cause a patient to drop out. When side effects occur, a clear plan for managing them helps patients feel supported rather than abandoned.
• Operational Flexibility:
Operational flexibility also plays a major role. Clinics that offer early morning or evening appointments give working patients and caregivers more viable options.
• Culture of Caring and Connection:
Even small actions make a difference. Prompt callbacks, respectful interactions and a culture of attentiveness across staff roles can build a strong patient-provider relationship. While weekly visits create logistical challenges, they also provide regular opportunities for support, reassurance and relationship building. Weekly team huddles or communication routines that keep staff aligned on each patient’s progress enable a more responsive care environment. Seeing the same staff consistently – adds familiarity and comfort, reducing anxiety in an already stressful process.
Designing Trials for Retention: Sponsor and Site Collaboration
Retention is not just a site-level concern – it begins with protocol design. Trials that impose high burdens without justification risk dropout, even when patients are motivated. Sponsors can improve retention by working closely with investigators to assess feasibility during protocol development. This includes re-evaluating the need for frequent visits, long stays, or multiple invasive procedures.
Proposed protocols are formally reviewed for feasibility before launch. If excessive burdens are identified – such as 18-hour clinic days or redundant biopsies – sponsors may be advised to revise the protocol. In some cases, protocols that seemed workable on paper are later amended after low enrolment or poor retention signal a mismatch with real-world patient capacity.
Sponsors increasingly recognise these risks and adopt realistic and patient-informed protocol designs. This protocol approach, along with
budgets for logistical support for patients, can make a measurable difference.
Beyond a Single Study: Retaining Patients Across Trials
In oncology, trial participation is rarely a one-time event. Many patients who enrol in early-phase trials eventually require another option once disease progression or resistance emerges. How patients feel about their first trial experience often determines whether they are willing to consider another.
Sites that build trust – through transparency, respect and coordinated care – are more likely to retain patients across multiple studies. Even when a therapy proves ineffective, a positive experience can motivate patients to stay engaged with clinical research.
Strong communication with referring oncologists also plays a key role. These physicians often have longstanding relationships with patients, and their continued involvement – through timely updates and collaborative care – can reinforce trust in the trial process. When oncologists remain informed and engaged, patients are more likely to view clinical trials as an integrated part of their treatment journey rather than a disruptive detour.
This continuity benefits both patients and sponsors. For patients, it offers sustained access to investigational therapies. For trial sites, it creates operational efficiency and a consistent, trial-ready population. And for sponsors, it means higher data quality and fewer delays.
Retention, then, is not only about completing one protocol – it’s about building an environment that supports patients over time.
Conclusion
Patient retention in oncology clinical trials is shaped by more than protocol compliance or logistical support – it reflects the overall patient experience. From trial design to site operations, from the first appointment to communication with referring physicians, every interaction can either strengthen or weaken a patient’s willingness to continue.
Dr. Justin A. Call
Justin A. Call, MD, is Director, Clinical Research at START – Mountain Region. Dr. Call received his undergraduate degree from the University of Utah and his medical degree from the University of Colorado Health Sciences Center in Denver, Colorado. Dr. Call completed his residency training in Internal Medicine and fellowship training in Hematology and Medical Oncology at the University of Colorado Health Sciences Center. He is board certified in Hematology and Medical Oncology. Dr. Call's clinical interests include drug development of new anticancer agents, with a special interest in gynecologic cancers and hematologic malignancies. He has been the principal investigator / co-investigator of more than 50 cancer clinical trials.
Redefining Site Relationships in Clinical Trials Insights from WCG 2025 CenterWatch Global Site Relationship Survey
At the heart of every clinical trial lies a complex network of relationships between sponsors, contract research organisations (CROs), trial sites, investigators, coordinators and patients. The quality of these relationships has a direct impact on every stage of a study, from protocol design and recruitment to data integrity and final outcomes. Cultivating a strong partnership between sites, sponsors and CROs ultimately benefits all parties. Identifying areas where site satisfaction is low provides sponsors and CROs with the necessary knowledge to drive meaningful improvements.
How Partnership, Feedback and Innovation are Shaping the Future of Sponsor-CRO-Site Collaboration
WCG’s CenterWatch Global Site Relationship Survey has been evaluating site satisfaction since 1997. Conducted every two years, the survey provides sites an opportunity to rank specific sponsors and CROs on a series of trial processes, including protocol design, study support, training, diversity and technology. In 2025, survey improvements included refining survey attributes, expanding language options and enhancing mobile accessibility. As a result, the survey procured over 12,000 responses from a diverse, global audience. Given that sites could select more than one sponsor or CRO to rate, this translated to over 19,000 sponsor ratings and almost 10,000 CRO ratings.
The analysis of the survey centered on a derived Customer Satisfaction (CSAT) Score. Participating sites were directed to rate sponsors and CROs using a 1–5 scale, with responses of four or five indicating satisfaction.
Respondents spanned diverse roles and geographies, with North America and Western Europe accounting for 23% and 29%
of responses, respectively. While Japan accounted for only 4% of responses, it was the region with the lowest satisfaction ratings, with a total CSAT of 36, nearly 30 points below the next lowest region. Cultural elements may partly explain this, as a rating of three is generally considered positive by Japanese respondents.
While various site roles were represented, investigators and study coordinators were 84% of respondents. The survey revealed the continued gap in satisfaction between study coordinators and investigators. Study coordinators, the site personnel at the frontline of site operations, reported lower satisfaction by almost 10 CSAT points.
Among the eight categories evaluated, Diversity and Technology received the lowest CSAT scores. As newly introduced areas in the survey, these categories reflect emerging challenges related to recent regulatory changes, technological advancements and efforts to recruit a more diverse patient population to enhance scientific rigor. Sponsors agree that study-by-study tailoring of diversity efforts is needed, with attention to cultural and epidemiological differences across geographies. Despite ongoing shifts in the political and regulatory landscapes, the global momentum toward inclusive trials is expected to persist.
When asked to identify the factors most critical to their satisfaction, respondents highlighted overall protocol design, quality of communication with study team/site staff and professionalism, knowledge and training of monitors/CRAs as the top three attributes.
Study coordinators placed particular emphasis on support for technology platforms and the inclusion of their feedback in protocol design. Meanwhile, investigators prioritised clear communication, patient enrolment viability, contract flexibility and monitor knowledge and professionalism.
Bridging Protocol Design and Operational Reality
An effective clinical trial is grounded in a rigorously designed protocol that integrates the perspectives of both sites and patients. Sponsors acknowledge that balancing patient and site-centric considerations is fundamental to achieving successful outcomes. Findings from this survey for the Protocol Design category indicate that sites perceive
the industry as not making significant progress in addressing the increasingly complex and demanding nature of high-burden protocols.
Protocol Design was one of two categories, the other being Study Monitoring Support, that demonstrated significant discrepancies between investigators and study coordinators. The former highlights the frontline capability to implement a protocol effectively, while the latter underscores the sponsor's responsibility to furnish sufficient support throughout the study duration.
Within the Protocol Design category, the attributes receiving the lowest ratings were protocol-patient friendliness and the solicitation and inclusion of site feedback in protocol development. Satisfaction levels for both attributes declined compared to previous years, indicating a negative trend in site perception. In fact, four of the top five declines in satisfaction were within the Protocol Design category.
A significant challenge identified by sponsors is the presence of organisational silos that impede progress. Sponsors have noted that protocol development frequently occurs with limited collaboration between clinical sciences and clinical operations. It is commonly observed that protocol authors may not always be fully aligned with the practical considerations of clinical execution. The result is protocols that may be scientifically robust but operationally burdensome and insufficiently attuned to the realities of patient care.
When sponsors do gather site feedback, they typically prioritise input from investigators, often overlooking valuable insights from study coordinators. Even when investigators are involved, some sponsors restrict feedback to a limited group of individuals, not covering a strong geographical base.
There is a clear industry trend toward large-scale initiatives that incorporate both sites and patients earlier in protocol development to obtain actionable feedback. This strategy not only improves the quality and practicality of protocols but also demonstrates recognition for the skills and experience of site personnel. Sponsors increasingly appreciate the value of input from diverse site perspectives, as these stakeholders are best positioned to identify potential challenges with enrolment and patient retention.
Clinical Trial Management
Several innovative approaches have demonstrated potential to drive meaningful transformation. Engaging patients in detailed trial simulations during the design phase has been viewed as particularly effective. Additionally, employing data-driven burden scores enables the quantification of protocol demands on both patients and site staff. Alongside regulatory guidelines that support decreasing patient and site burden, the integration of these metrics reflects a significant cultural shift toward enhanced accountability and collaborative practice.
Site perspectives around ongoing study support were captured as part of the Study Monitoring Support category. Both the structure and style of sponsor and CRO organisations profoundly affect site experiences related to monitoring support. Sponsors agree that in-house monitoring and high staff retention for monitors are correlated with positive site relationships, while outsourced models can introduce variability and opacity. Retention of monitors/CRAs had the lowest satisfaction rating within this category.
Technology in Clinical Trials: Balancing Innovation and Site Burden Technology received the lowest satisfaction ratings among all survey categories, with only 57.9% of sites awarding sponsors a high score (four or five) in this area. Even organisations that performed better acknowledged significant opportunities for improvement. These companies noted that, while their performance is comparatively strong, there is still considerable progress to be made in easing the burden technology poses to sites.
Site frustration in this context arises from the volume of platforms required to conduct a clinical trial, along with concerns regarding the adequacy of support and training provided for these systems. The complexity is compounded by divergent requirements from sponsors, CROs and sites, often leaving sites with the burden of integrating disparate systems. While each platform may be effective and valuable individually, their combined use has resulted in significant challenges for site staff, including the burden of managing multiple logins (even with single sign-on) across systems that are not interoperable. Site turnover has increased significantly, driven in part by the challenging new era of technology and the associated strain.
A significant factor contributing to the increase in portals and platforms is the incorporation of decentralised clinical trial (DCT) elements. While these components offer enhanced convenience and support high-quality data collection, they also introduce multiple systems, each of which may require separate logins and procedures. One leading organisation in this field has shared that they are intentionally embracing DCTs cautiously, favoring a gradual implementation over an immediate, large-scale rollout to avoid potential disruptions and user dissatisfaction.
Organisations that performed on the higher end of the spectrum highlight the advantages of appointing a single, dedicated resource to assist sites in transitioning to new systems. Pilot programs that deploy specialists to offer site support during pivotal events, such as
investigator meetings, have yielded positive results. In models where full-service CROs manage the work, such roles act as vital bridges between the sponsor and the site.
Other efforts to streamline technology through vendor curation and ongoing feedback sessions are underway, but industry-wide improvement has been slow. The consensus is clear: technological innovation must be grounded in the real-world needs of sites, with an unwavering focus on reducing administrative burden.
Contracting:
Navigating Payment and Accountability Challenges
Contracting and payment processes present additional challenges in managing site relationships. While sponsors may acknowledge that these processes are less critical than protocol design, they are frequently identified as significant contributors to delays in site activation, highlighting the importance of improving efficiency to reduce study timelines. Survey findings showed that the provision of fair payment amounts and overall flexibility in contract and budget
Clinical Trial Management
negotiations satisfaction has decreased about 5–6% from 2023 to 2025.
Companies noted that widely accepted Fair Market Value (FMV) vendors and benchmarking tools suggest organisations should be making comparable payments. However, there remains a wide gap in site perception of payment amounts across sponsors, suggesting that further analysis on the use of FMV tools and company strategies on payment caps is warranted.
Site-specific feedback also highlights frustration with some CROs failing to make timely payments, sometimes requiring months of back-and-forth before funds are released, even when the principal investigator intervenes. There is an industry-wide need for more accountability and advocacy mechanisms to protect site interests.
One proposal for improvement in this space is to simplify contracts and budgets. For example, simplifying budgets into higherlevel categories rather than individual procedures is a method implemented by top-performing organisations.
Training: The Foundation of Productive Site Partnerships
A recurring theme in conversations surrounding the survey results is the importance of optimising site training, not merely as a box-ticking exercise, but as a critical component in fostering productive longterm site relationships. Sponsors emphasised that effective training ensures that sites both choose to work with them again and are better equipped to reduce audit or inspection findings. This, in turn, protects the performance and reputation of both the site and the sponsor.
Feedback from sites indicates that training tends to be too long and repetitive. One example frequently discussed is that investigator meetings are often too long and fail to target the audience sufficiently. In response, some study teams are experimenting with more focused sessions, such as short, high-quality training on the mechanism of action (MOA) and drug profiles. These initiatives can make site personnel more engaged and effective.
It is widely accepted that sites require training that is customised, concise and relevant, with a preference for reciprocal recognition of training across studies and ideally, among different sponsors.
Site Feedback Loops: Building a Culture of Listening and Responsiveness
Maintaining robust site feedback loops is crucial for fostering a culture of listening and responsiveness between sponsors, CROs and research sites. Effective feedback mechanisms allow sponsors to address site-specific frustrations, while also enabling them to tailor support and resources more precisely to site needs. Embedding feedback into protocol design, technology use and training will strengthen site satisfaction and loyalty. By systematically integrating site input into performance analyses and operational decisions, organisations can identify root causes of challenges, adjust processes proactively and ultimately build more productive,
mutually beneficial partnerships. This continued dialogue is essential for optimising efficiency, upholding quality standards and ensuring the valuation of site perspectives in the rapidly evolving landscape of clinical research.
Charting a Collaborative Future for Site Partnerships
The insights captured in the 2025 CenterWatch Site Relationship survey paint a picture of a clinical trial industry in transition. Across protocol design, technology, contracting, diversity, training and study support, the imperative is clear: sponsors and CROs must move from transactional to partnership-oriented relationships with sites.
Furthermore, linking these results with performance metrics is essential for evaluating and developing site relationships. Sponsors seek to associate site satisfaction with variables such as speed and quality and to compare planned outcomes with actual results.
Achieving this transformation will require:
• Robust, multi-level feedback loops that genuinely influence protocol and operational decisions.
• Streamlined, interoperable technology that lightens rather than adds to the site burden.
• Resources are allocated to support sites with required platforms.
• Continual investment in targeted, high-quality site training.
• Transparent, timely and fair contracting and payment practices.
• Diversity initiatives that are ambitious yet pragmatic and locally relevant.
• Vendor partnerships based on measurable impact and site preference.
• Organisational structures that prioritise consistency and clarity in site interactions.
Ultimately, the future of clinical research depends on the ability of sponsors, CROs and sites to listen, adapt and collaborate. Through these principles, the industry can tap into the expertise and dedication of the individuals who make clinical trials possible to accelerate scientific discovery.
Melissa Hutchens is vice president of WCG Research & Benchmarking. She joined the company through KMR Group in 2001 and has more than 24 years of experience in R&D benchmarking and analytics for the biopharmaceutical industry. She has built extensive benchmarking frameworks that span research, development, and operational levels within.
Melissa Hutchens
Clinical Trial Management
AI in Clinical Trial Recruitment: Proceed with Cautious Optimism
Artificial Intelligence (AI) is rapidly reshaping the landscape of clinical research, offering transformative solutions to longstanding challenges in trial design, execution and data management. As of 2025, AI is no longer a futuristic concept; it is a practical tool driving efficiency, precision and innovation across the clinical trial ecosystem. But what does AI mean in the context of practical applications for day-to-day clinical development activities? And does its potential have any limits?
Patient recruitment remains one of the most persistent challenges in clinical research, with up to 80%1 of trials failing to meet enrolment timelines and nearly one-third of Phase III trials being terminated due to insufficient accrual.2 In this context, AI offers a compelling opportunity to reimagine how patients are identified, engaged and retained. Yet, as with any powerful tool, its use must be tempered with ethical foresight and operational realism. This editorial explores the promise, limitations and future direction of AI in clinical trial recruitment.
The Evolution of Recruitment Challenges
Historically, patient recruitment has been a consistent operational challenge in clinical trials. Traditional methods including physician referrals, site databases and advertising campaigns, often resulted in slow enrolment, high dropout rates and underrepresentation of diverse populations. Despite incremental improvements, recruitment delays continue to cost sponsors millions annually and jeopardise study timelines. These persistent challenges underscore the need for innovative, data-driven approaches to recruitment, where AI, in particular, is emerging as a transformative force in this space.
Practical Applications of AI in Clinical Development
The use of AI has already made significant strides in optimising activities that previously required extensive human time and effort. Tasks that once took weeks can now be completed in a fraction of the time. AI-powered machine learning (ML) models are being used to predict trial outcomes and identify risks such as protocol failure or patient dropout. These models analyse both structured and unstructured data from past trials, such as eligibility criteria and geographic distribution, to forecast potential issues before they arise.
Generative AI, with its own set of use cases, is being used to create initial drafts of protocols and lengthy documents, shifting the human contributor’s role from creator to editor. These advancements have emerged rapidly, especially when compared to the decades-long reliance on traditional processes that saw only minor changes, such as the transition from paper to digital formats.
AI’s Role in Recruitment: Promise and Limitations
Despite decades of effort, recruitment continues to be a major operational hurdle in clinical trials. AI technologies are now being applied to address this issue with greater speed and precision than ever before. Tools such as chatbots and predictive algorithms are improving patient matching by analysing electronic health records (EHRs), demographic data and even genomic information. For example, platforms like TrialGPT have demonstrated near-human accuracy in
identifying eligible participants, reducing screening time by over 40%. Beyond identification, AI also supports patient engagement through personalised reminders, educational content and real-time support, factors that contribute to improved retention and overall satisfaction.3,4
Manual review of patient charts is time-consuming and prone to error. AI’s ability to synthesise disparate data sources, including clinical, demographic and behavioral, into a unified view is a clear advantage. These capabilities are particularly valuable in reducing site burden, supporting feasibility assessments and increasing certainty of eligibility for external site referrals through middleware5 solutions that bridge patient record retrieval.
However, one area that remains unexplored is AI’s ability to predict human behavior beyond eligibility. While AI can determine who qualifies for a trial, it cannot yet reliably predict who will choose to enrol. The decision to participate is influenced by a complex mix of factors: site engagement, study design, time commitments, cultural attitudes and even external events like pandemics. This raises an interesting question: Can AI not only identify eligible patients but also predict which ones are most likely to consent? Answering this question is, at best, a tentative ‘maybe.’ Exploring its feasibility introduces deeper philosophical and ethical questions.
Ethical and Philosophical Considerations
• Is it possible for AI to use currently available data to make predictions, or are additional inputs, such as social determinants of health or consumer behavior required?
• What characteristics influence a patient’s willingness to participate and can these be objectively characterised?
• Should an individual’s online footprint be considered and if so, how do we safeguard privacy?
• What are the boundaries of patient trial matching and prediction done without consent versus requiring explicit authorisation?
Some of this data could theoretically be scraped from the internet and integrated with clinical datasets, but this raises concerns about appropriateness and consent. Should AI be allowed to mine consumer behavior or social media activity to predict trial participation? And if so, should these applications be limited to HIPAA-covered entities, or can commercial recruitment organisations with AI offerings also participate?
The deeper AI applications go into the lives of potential participants, the greater the responsibility to protect those individuals, even if the use cases seem benign, such as sending a trial invitation. The integration of consumer data with health information is a murky area that demands careful scrutiny.
AI Bias and Fairness in Recruitment
One of the most pressing concerns in AI-driven recruitment is the risk of algorithmic bias. If training data lacks diversity, AI models may inadvertently exclude underrepresented populations, reinforcing existing disparities in clinical research. For example, an AI tool trained primarily on data from urban academic centers may underperform in rural or minority communities. Ensuring fairness requires deliberate
Clinical Trial Management
efforts to audit models, diversify training data and include equity metrics in performance evaluations.
Human-in-the-Loop Models
Despite AI’s growing capabilities, human oversight remains essential. The ‘human-in-the-loop’ models, where AI suggestions are reviewed and validated by clinical staff, offer a balanced approach. This ensures that nuanced clinical judgement, ethical considerations and patient preferences are not lost in automation. These hybrid models are especially valuable in sensitive areas like recruitment, where trust and empathy play a critical role.
Regulatory Perspectives
Regulatory bodies are beginning to address the implications of AI in clinical research. The FDA’s recent draft framework6 for AI/ML-based software emphasises transparency, validation and patient safety, all principles that must extend to recruitment algorithms. Similarly, the European Medicines Agency (EMA)7 has signaled interest in developing guidelines for AI use in clinical trials, particularly around data integrity and ethical considerations.
These frameworks are still evolving, but they underscore the need for industry-wide standards. Without clear guardrails, the risk of misuse or overreach grows, potentially undermining public trust in clinical research.
Global Perspectives on AI in Recruitment
Globally, the adoption of AI in clinical trials varies widely. In the U.S., innovation is often driven by private sector investment, while the EU emphasises ethical frameworks and data protection under GDPR. In Asia, countries like China and South Korea are rapidly scaling AI infrastructure, with government-backed initiatives supporting AI in healthcare. These regional differences influence how AI is applied in recruitment, from data access to regulatory scrutiny.
The Patient Perspective
From the patient’s point of view, AI-driven recruitment may feel impersonal or even invasive. Transparency about how data is used and ensuring informed consent at every stage, is critical to maintaining trust. Patients must understand not only that they are eligible for a trial, but also how and why they were identified. This is especially important in communities with historical mistrust of medical research, where even well-intentioned outreach can be met with skepticism.
Unfortunately, the history of clinical research includes instances of unethical behavior that have left lasting scars, particularly among marginalised populations. As AI becomes more embedded in recruitment strategies, it must be wielded with sensitivity and respect for these historical contexts.
Real-World Examples
Several AI tools are already demonstrating the potential to improve recruitment outcomes. Deep 6 AI,8 for example, has partnered with academic medical centers to accelerate patient matching by mining EHRs in real time. In one pilot study, recruitment timelines were shortened by 30% and site staff reported improved confidence in feasibility assessments.
Another example is IBM Watson Health,9 which has explored AIdriven trial matching using natural language processing to interpret complex eligibility criteria. While technology shows promise, it also highlights the importance of human oversight, AI can suggest matches, but clinical judgment remains essential.
Interoperability and Data Integration Challenges
For AI to be effective in recruitment, it must access and interpret data from multiple sources, including EHRs, claims data, registries and more. However, interoperability remains a major challenge. Variability in data formats, coding standards and system architectures can limit AI’s ability to generate accurate insights. Industry-wide efforts to standardise data exchange, such as Fast Healthcare Interoperability Resources (FHIR), are critical to unlocking AI’s full potential.
Looking Ahead: A Call to Action
As AI continues to evolve, the clinical research industry must prioritise responsible innovation. Establishing cross-functional working groups, including technologists, ethicists, regulators and patient advocates, can help define best practices and ensure AI serves both science and society.
CROs, sponsors, technology companies, healthcare institutions, sites and patient representatives all have a role to play in shaping the future of AI in recruitment. Together, they must ensure that innovation does not come at the expense of ethics, transparency, or patient trust.
AI has the potential to transform the patient recruitment process, but its success will depend on how thoughtfully it is implemented. The industry must remain vigilant, collaborative, and committed to keeping patient experience at the center of every technological advancement.
Earl Seltzer, Executive Director of Therapeutic Strategy and Innovation at CTI, a global fullservice CRO, brings over 20 years of clinical research experience spanning investigator sites and CROs. He leads global feasibility and strategic trial planning, with a specialised focus on rare diseases, transplantation and infectious disease. Earl drives innovation in patient engagement and AI integration, while overseeing proposal development and data analytics to optimise trial delivery.
Reimagining Clinical Trial Management: AI as the Virtual Team Member
Currently, clinical trials face challenges such as complex protocols, extended timelines, substantial costs and increasing regulatory requirements. As these trials become increasingly complex, costly and subject to stricter regulations, sponsors are exploring innovative methods to enhance trial planning, execution and oversight. Historically, the management of clinical trials has relied heavily on labour-intensive procedures, including the use of spreadsheets, reports and periodic status meetings, as well as fragmented technological systems. With the rising complexity of clinical trials, the workload on clinical project teams correspondingly increases. Furthermore, the clinical research ecosystem is under increasing pressure to conduct trials more efficiently and cost-effectively.
The transition towards digital transformation presents an opportunity to reconsider methodologies for conducting trials through the integration of Artificial Intelligence (AI)-driven, automated and data-centric systems. Conventional manual procedures are increasingly insufficient in maintaining efficiency and cost-effectiveness. Artificial Intelligence (AI) is progressing beyond just being a tool for data analysis and forecasting, emerging as an active participant within the clinical project team. AI is no longer a distant concept; it is becoming a virtual team member capable of enhancing or even autonomously executing a broad spectrum of roles traditionally carried out by members of the clinical operations team. By employing machine learning, natural language processing (NLP) and real-time analytics, AI enhances essential functions such as patient recruitment, site selection, data monitoring, risk assessment and protocol adherence. It facilitates expedited decision-making, predictive risk management and increased operational efficiency. As the complexity and scale of clinical trials expand, AI offers an intelligent, scalable solution to streamline workflows, improve data quality and accelerate timelines, redefining the future landscape of the drug development process.
This article explores a framework for leveraging artificial intelligence to augment or fulfill critical roles in clinical trial management and to transform operations into a streamlined, intelligent and proactive process. It describes how artificial intelligence can function as a ‘virtual team member,’ either augmenting or autonomously executing essential functions traditionally assigned to human professionals, such as Feasibility Associates, Clinical Research Associates (CRA), Medical Monitors/Safety Monitors, Data Managers and Project Managers. Through this transformation, artificial intelligence enhances operational efficiency, reduces costs and improves data quality and compliance. Additionally, it is recommended that human oversight be maintained over these AIperformed functions to ensure overall effectiveness and integrity in clinical trial management. For the conduct of efficient and effective clinical trials, automation should not be the sole approach; instead,
a collaborative model employing both human expertise and machine capabilities is vital – working side by side as a digitally enabled, virtual project team.
Clinical Trial Feasibility: AI as a Feasibility Associate Feasibility is a crucial first step in clinical trial planning, as it assesses the suitability of sites, countries and patient populations to ensure effective patient recruitment and smooth operations. Traditionally, feasibility assessments are manual, lengthy and rely on limited historical data and subjective judgment. AI is revolutionising this process by offering data-driven, predictive insights that improve speed, accuracy and scalability. Let’s explore some key functions of a Feasibility Associate that AI can fully perform or enhance.
Protocol Feasibility Assessment: AI can draft, distribute and analyse site feasibility questionnaires utilising natural language processing (NLP). Based on the responses obtained and the weighted importance of each question, AI can effectively assist in analysing the responses to identify the most suitable sites for the study. It can detect inconsistencies or red flags within site responses. Additionally, it will diminish the need for manual review and subjective decision-making.
Country and Site Selection: These procedures can leverage various data sources, including historical clinical trial databases (such as ClinicalTrials.gov), Electronic Health Records (EHRs), site performance databases, publication data, disease prevalence data and investigator networks, to optimise the selection process. AI capabilities can be effectively employed to rank potential sites based on assigned weights to feasibility parameters, which are aligned with the specific relevance to the clinical study. These parameters include prior enrolment performance for similar indications, the investigators’ experience in managing patients within that indication, protocol complexity, as well as the durations of ethics committee and regulatory reviews. Additionally, consideration can be given to sites and countries located in geographic regions with high disease prevalence relevant to the clinical study indication.
Patient Population Analysis: AI capabilities are utilised promptly and effectively to evaluate the feasibility of obtaining the required, protocol-specific patient cohort. AI is employed to analyse protocol-specific inclusion and exclusion criteria against deidentified Electronic Health Record (EHR) datasets to identify potential feasibility gaps that may limit the necessary patient population. This analysis will facilitate recommendations for protocol modifications, if necessary, to ensure better alignment with real-world populations.
Enrolment Forecasting: By utilising patient population analysis and predictive models derived from historical trial data, AI can aid in estimating enrolment timelines. Additionally, it can effectively simulate various recruitment scenarios, such as adding more sites or countries, or modifying eligibility criteria.
Overall, compared to traditional manual feasibility activities, AI as a Feasibility Associate will provide significant benefits to clinical operations, such as greatly reducing feasibility timelines, increasing site or country selection accuracy, improving enrolment forecasting, speeding up study startup and enabling better-informed protocol decisions.
Clinical Trial Monitoring: AI as a Clinical Research Associate
The Clinical Research Associate (CRA) plays a vital role in the comprehensive management of clinical trials, encompassing startup activities, interim assessments and close-out procedures at the trial sites. The CRA's role is central and crucial in ensuring that clinical trials are conducted in accordance with the protocol, standard operating procedures (SOPs), Good Clinical Practice (GCP) and all applicable regulatory requirements. Traditionally, CRAs undertake labor-intensive site visits, data verification and monitoring tasks that are costly and sometimes reactive rather than proactive. Furthermore, while performing these tasks, CRAs may occasionally overlook data pertinent to patient safety and data quality. Artificial Intelligence (AI) is increasingly enhancing and partially automating many CRA responsibilities through centralised and risk-based monitoring models. By analysing large volumes of clinical data in real-time, AI can identify anomalies, monitor trends and generate alerts, thus facilitating more intelligent and targeted site monitoring. The following outlines key CRA responsibilities that AI can perform or augment.
Remote and
Centralised Site
Monitoring: AI tools can continuously analyse clinical data streams from electronic data capture (EDC) systems, lab systems and ePROs to identify patterns and site-specific anomalies. The dashboards and reports designed to monitor data quality and patient safety will assist in flagging sites with QTL (quality tolerance limits) and data quality issues, such as inconsistent reporting, protocol deviations, patient safety alerts, or delays in data reporting. This approach facilitates remote and prompt escalation. AI consistently monitors site-level and study-level KRIs, including enrolment rates,
SAE reporting timeliness and query resolution times. Predictive models identify trends before they escalate into deviations. As part of a riskbased monitoring strategy, AI does not replace CRAs but enhances their capacity to monitor trials intelligently and efficiently, in accordance with regulatory expectations. Here, we refer to both the efficiencies and effectiveness that AI can contribute to clinical monitoring.
Risk-Source Data Verification (SDV) Prioritisation: AI can prioritise which data points and sites necessitate comprehensive source data verification, thereby alleviating the workload of CRAs. The dynamic SDV algorithms analyse risk factors such as adverse event reporting trends, data inconsistencies and protocol deviations to identify the data and sites that require additional scrutiny to ensure data quality, integrity and patient safety.
Query and Issue Management: AI can autonomously generate data queries by identifying missing, implausible, or inconsistent data entries. Natural Language Generation (NLG) tools are capable of drafting query texts and suggesting remedial actions.
Protocol Deviation Detection: AI is capable of identifying deviations by comparing patient data against the predefined protocol windows and criteria. Temporal Analysis ensures that visit scheduling and dose administration adhere to the protocol. The AI dashboard facilitates the identification of off-schedule visits at the sites.
Document Compliance and TMF Review: AI tools utilising NLP are capable of examining uploaded documents to verify completeness, consistency and date discrepancies within the Trial Master File (TMF) or Informed Consent Forms (ICFs).
We propose that AI-powered clinical monitoring can redefine the management and oversight of clinical trials by Clinical Research Associates (CRAs), facilitating a transition from reactive to proactive site monitoring. This technology enables the processing of extensive datasets in real-time, uncovering insights that may elude human
monitors. An AI-enhanced CRA role will support continuous and predictive site supervision, in contrast to the periodic and reactive monitoring associated with traditional CRA functions. This innovative approach will prioritise targeted and risk-based Source Data Verification (SDV), replacing the traditional, manual and costly 100% SDV procedures. Data queries will be automatically detected and drafted and protocol deviations or violations will be identified nearly in real time. AI-powered CRA role will reduce costly on-site visits, thereby enhancing data quality and integrity through real-time alerts. It is important to note that AI is not intended to replace CRAs; rather, it aims to empower them to concentrate on value-added activities where human judgment is indispensable, such as investigator engagement, site visits, quality improvement and patient safety assurance.
Medical and Safety Monitoring: AI as a Medical & Safety Monitor
The Medical Monitor (MM) often also serves as a safety monitor, playing a crucial role in clinical trials by overseeing data safety, medical validity and scientific integrity throughout the study lifecycle. This includes reviewing adverse events (AEs), ensuring protocol adherence, identifying clinical risks and supporting investigators in medical decision-making. However, as trials grow more complex and data-driven, traditional manual review processes are no longer sufficient for timely and effective oversight.
Artificial Intelligence (AI) is transforming the role of the Medical Monitor through the facilitation of real-time, automated and predictive medical data analysis. With the integration of AI, Medical Monitors are able to transition from reactive data review to proactive management of clinical risks, thereby enhancing patient safety and the overall quality of clinical trials. The following core responsibilities of a Medical Monitor are either performed or significantly enhanced by AI.
Real-time Monitoring and Detection of Adverse Events and Safety Signals: These are enhanced through the use of AI, which can generate dynamic, real-time subject profiles by aggregating data from electronic data capture (EDC), electronic patientreported outcomes (ePRO), laboratory results, imaging and adverse events. This facilitates periodic reviews of adverse events (AEs), laboratory abnormalities and treatment outcomes on a patientby-patient basis, thereby enabling the early identification of patient risks and safety signals. The signal detection algorithm is capable of identifying unusual patterns or clusters of adverse events by comparing trial data with historical datasets and external pharmacovigilance databases. Additionally, AI can propose probable severity, expectedness and causality scores based on patient data and protocol-defined risk thresholds.
Medical Data Review and Anomaly Detection: AI algorithms can identify unexpected clinical trends and outliers across patient populations. It can flag values that deviate from patient baseline or population norms. AI-based models can assist in clustering detection of unexpected adverse events at specific sites, facilitate early identification of dose-limiting toxicities, or detect laboratory abnormalities inconsistent with the disease or treatment.
Medical Review of Protocol Deviations: As MMs evaluate the medical significance of protocol deviations, AI-powered medical monitoring assists in deviation classification by categorising deviations based on severity and impact using pre-trained models. It also assesses whether a deviation may affect patient safety, efficacy outcomes, or trial integrity and it prioritises events that require immediate medical attention.
Safety Narrative Generation: AI creates structured safety narratives using structured data and clinician notes. AI assists in consistency checks to ensure all AE narratives align with data in EDC, ePRO and SAE forms.
Medical Query Management and Site Support: The medical query bot answers site-related questions about protocol procedures, patient eligibilities, study drugs and common safety concerns.
AI is transforming the role of the Medical Monitor from a passive reviewer of medical and safety data to an active, data-driven risk manager. With capabilities ranging from automated profile creation and safety signal detection to NLP-powered medical narrative review, AI enables Medical Monitors to identify clinical issues earlier, focus on high-risk patients and make faster, more informed decisions. By integrating AI into medical monitoring workflows, sponsors and CROs can enhance patient safety, improve trial outcomes, and meet increasing regulatory and scientific demands more efficiently and confidently. However, we also see the need for human medical monitor oversight in the process to address queries related to the contextual interpretation of complex cases, decision-making in unexpected clinical scenarios, patient selection waivers, ethical judgment, patient advocacy and of course, communication with investigators, DSMBs and regulators.
Clinical Project Management: AI as a Project Manager
The Clinical Project Manager (PM) plays a vital role in executing clinical trials, ensuring studies are completed on time, with quality, within budget and in compliance with regulatory and scientific standards. The project manager collaborates with cross-functional teams, tracks milestones, manages budgets and timelines, mitigates risks and ensures quality outcomes. As modern clinical trials become more complex, traditional project management approaches often become reactive, fragmented and labor-intensive. AI has the potential to enhance the Project Manager's role by providing predictive analytics, workflow automation, real-time tracking and intelligent decision support, thus shifting clinical trial operations from reactive to proactive.
Project Planning and Timeline Optimisation: AI-driven planning tools analyse historical data from previous trials to forecast realistic timelines for study initiation, enrolment, monitoring and closeout. AI has the capability to simulate various project scenarios based on country, indication, protocol complexity and operational variables.
Resource and Budget Forecasting: AI utilises historical data and current project inputs to accurately predict resource requirements and financial needs. The machine learning models are capable of refining predictions in response to variations in enrolment rates, protocol modifications, the addition of countries or sites and site performance.
Risk Prediction and Mitigation: AI identifies early warning indicators through the analysis of data spanning multiple domains, including enrolment delays, query resolution lags and protocol deviations. The use of predictive analytics facilitates timely interventions to avert subsequent complications.
Milestone and KPI Tracking: AI continually monitors progress against key performance indicators (KPIs), pertaining to project management metrics such as site initiation rates and timelines, patient enrolment versus planned targets, query resolution times and adherence to monitoring visits. AI-powered dashboards can prioritise project management risks, identify deviations and recommend corrective measures.
Team Coordination and Communication: AI-powered project management platforms can automate scheduling meetings, assigning tasks, tracking deliverables and summarising status reports. NLP can extract action items from meeting transcripts or emails and turn them into tasks.
Regulatory and Documentation Compliance: AI can monitor Trial Master File (TMF) documents for completeness, version control and regulatory submission readiness. Intelligent checklists ensure that country-specific regulatory requirements are tracked and met.
Real-Time Portfolio and Study Dashboards: AI consolidates data from CTMS, EDC, IRT, finance and eTMF systems to provide a comprehensive, real-time view of projects. AI can suggest prioritisation strategies across a portfolio of studies based on risk, strategic importance, or resource limitations.
AI is revolutionising clinical project management by giving PMs tools to handle trials more efficiently, accurately and proactively. From planning and budgeting to execution and oversight, AI helps predict issues before they arise, allocate resources effectively and maintain quality and compliance. AI functions as an intelligent co-pilot – improving human decision-making with insights derived from thousands of variables in real time. As trials grow more complex and urgent, AI-enabled PMs will set the standard for delivering faster, safer and more efficient clinical research.
Data Management: AI as a Data Manager
Clinical Data Managers play an essential role in maintaining the integrity, accuracy and preparedness of clinical trial data for analysis and submission. With the growing volume and complexity of data generated from EDC systems, ePROs, wearable devices and realworld data sources, traditional data management methods face new challenges. AI provides powerful solutions to transform data management into a proactive, intelligent and highly automated function. When integrated into the clinical trial ecosystem, AI as a Virtual Data Manager can streamline data cleaning, speed up query resolution, discover hidden data patterns and ensure high data quality with less human intervention.
Smart Edit Check Design and Validation: AI algorithms analyse past trials to suggest relevant edit checks based on protocol, indication and data structure. NLP models interpret protocol criteria and translate them into logical rules, reducing time spent on manual programming. AI tests edit checks against simulated data for performance and redundancy, decreasing creation time significantly while enhancing rule relevance.
Real-Time Anomaly Detection and Data Cleaning: The machine learning models continuously monitor incoming EDC data to detect outliers and implausible values, protocol deviations and patternbased inconsistencies. AI proactively flags issues, thereby facilitating real-time resolution rather than relying solely on periodic reviews. For instance, if a subject’s BMI (Body Mass Index) is recorded as decreasing drastically over a span of two days, the AI promptly flags this anomaly and suggests contextual information from previous entries or similar past irregularities.
Automated Query Management: AI agents automatically generate queries founded on validation rules and anomaly detection. These queries are prioritised considering data impact and patient safety risk factors. NLP models support site personnel by proposing query responses or clarifications in straightforward language. This approach aims to diminish the workload of data managers, expedite data cleaning processes and enhance support for site staff.
Advanced Data Reconciliation: AI facilitates the intelligent crossverification of Electronic Data Capture (EDC) data with other systems such as electronic Patient-Reported Outcomes (ePRO), laboratories and Interactive Response Technology (IRT). Mismatches are duly flagged, accompanied by potential explanations. For instance, AI can identify that a discrepancy in laboratory value dates is attributable to a time zone difference and can automatically correct such discrepancies when permitted by policy. Additionally, AI possesses the capability to automatically resolve minor discrepancies by employing confidence thresholds.
Medical Coding Automation: Using trained AI/NLP models, medical terms are automatically coded to MedDRA or WHO-DD with high accuracy. Human coders review only uncertain or ambiguous entries. AI continuously learns from previous coding decisions to enhance performance over time. This process speeds up coding turnaround and boosts consistency across coders and sites.
Data Lock Readiness and Forecasting: AI continuously assesses the database's readiness for interim or final lock by analysing the number of open queries, missing data rates and query response turnaround times. It provides alerts and timelines to keep stakeholders informed about progress and potential bottlenecks. Therefore, AI facilitates predictive planning and helps prevent last-minute delays during database lock.
Coordination with Other AI Roles: The data manager handles data generated from the study conduct, which is the ultimate output used to assess the safety and efficacy of the treatment. Therefore, a process can be established where the AI data manager coordinates with other AI roles within the clinical trial management team to communicate data-related risks, quality and safety issues in a timely manner. For example, working with the AI CRA to share alerts on site-specific data quality issues to prioritise monitoring efforts. Similarly, collaborating with the AI Medical Monitor to flag data anomalies that may indicate safety signals, or with the AI project manager to provide ongoing data health metrics that influence timeline projections and resource planning.
AI is transforming the role of the Clinical Data Manager by automating routine tasks, boosting data quality, and providing predictive insights. When applied thoughtfully, AI functions as a virtual co-pilot that improves data oversight and speeds up the process of reaching clean, locked databases, thereby reducing trial timelines and increasing efficiency. The decrease in manual work for repetitive tasks allows teams to focus more on strategic data review. In the future of clinical trials, AI-enhanced data management will be vital for maintaining data integrity in an increasingly digital, decentralised and rapid research environment.
Conclusion
As the clinical trial landscape evolves, embracing AI across feasibility, monitoring, medical oversight, data management and project management is not just innovation but a necessity. AI is not just a tool; it is becoming a co-pilot in clinical research. By reimagining AI as a virtual project team, sponsors and CROs can execute trials faster, more adaptable and more resilient. The goal is not to replace human intelligence but to amplify it with continuous, real-time, data-driven decision support. It enhances their capabilities by managing repetitive tasks, uncovering patterns and providing real-time insights. This hybrid operating model allows clinical teams to focus on strategic decisions, patient safety and regulatory compliance.
One of the key advantages of using AI in clinical trial management is establishing coordination among AI-powered roles to ensure that
knowledge transfer regarding key risks and benefits occurs promptly, enabling necessary proactive actions. Often, these insights or knowledge transfers from one role to another are missed in traditional human-based clinical trial management. For example, suppose during the feasibility process it is known that a site has fewer EC meetings or the schedule for upcoming EC meetings. In that case, this information should be promptly shared with the CRA so that site start-up activities can be planned accordingly to avoid delays in site initiation. Similarly, timely communication of data quality or safety issues identified by the AI data manager to relevant roles like AI CRA, AI Medical Monitor, or AI Project Manager will help reduce or eliminate issues, improve data quality, enhance patient safety, ensure timely database lock and support overall trial conduct. This innovative approach will facilitate effective management of clinical trials by ensuring proactive measures for risk mitigation or management.
While exploring the framework for implementing AI across clinical trial roles, responsibilities such as data privacy and security arise, requiring us to ensure that AI tools comply with HIPAA, GDPR, and GxP guidelines. The algorithms must be validated to meet regulatory standards (e.g., FDA, EMA, MHRA). Human oversight of these key functions performed by AI is essential, as AI will augment rather than replace human clinical judgment. Additionally, an effective change management process is necessary, where sponsors and CROs must train teams to trust and effectively utilise AI insights.
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Ashok Ghone
Ashok Ghone, PhD, MBA, is the Founder and CEO of MedInventas, with nearly 25 years of experience in the pharmaceutical, medical device and CRO industries. He brings deep expertise in global clinical research, with hands-on experience in clinical operations, project management, trial execution and process development. Ashok has successfully led cross-functional teams on local, regional and global projects across early and late-phase clinical studies in multiple therapeutic areas. A recognised thought leader, he has played a key role in designing and implementing processes, systems and training programs for riskbased and centralised monitoring. At MedInventas, he now offers domain expertise and AI-powered solutions for clinical operations, clinical trial management and medical writing.
Email: ashok.ghone@medinventas.com
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Harnessing Transformative Data Visualisation for Clinical Research: From Insights to Action
A Patient-centered Imperative
In the complicated realm of clinical research, data abounds – yet, in its raw form, this data remains scattered, isolated and often difficult to use. The true power of clinical research lies not in the sheer volume of data amassed, but in the clarity and actionable insight that can be extracted from it. The act of transforming raw numbers into meaningful information is akin to assembling an immense puzzle, where each piece represents patient data, outcomes, disease patterns and operational metrics. Only when these pieces are connected does a coherent picture emerge – one that can guide decision-making and drive innovation. This is critical as we keep in mind more than the day-to-day, but the bigger picture of the patients we serve – be those strangers, friends, neighbors, or ourselves to ensure we ultimately improve patient outcomes. This article explores the pivotal role of data visualisation in clinical research, advocating for a strategic, people-centric approach that translates insights into decisive action.
The Puzzle of Clinical Data
The analogy of clinical research as a puzzle is more than metaphor; it is a defining challenge across the industry. Every clinical trial generates thousands of data points – demographics, lab results, safety signals, efficacy outcomes, operational timelines. When these data points remain unintegrated, the potential for insight remains dormant. Data visualisation is the act of fitting these pieces together, revealing patterns, trends and stories that would remain invisible in the raw, numeric form. Without visualisation, clinical data is fragmented and its true value – its ability to inform and transform – is left unrealised.
Translating Data into Information
At the center of this transformation stand statisticians, programmers, analysts and data scientists – the architects who craft information from complexity. Their essential task is not simply technical; it requires empathy and foresight. Who will use this information? What do they need to know to make timely, effective decisions? A successful visualisation does not merely display data; it anticipates the questions and contexts of its audience – be they are researchers, clinicians, policymakers, or regulators. When executed correctly, visualisation empowers these stakeholders to accelerate decision-making, improving both the speed and the impact of clinical trials, but only if it is simple and intuitive to use.
Underlying every dataset, every visualisation and every analysis is a fundamental human reality: the patient. In clinical research, the patient is both the subject and ultimately, the beneficiary of our efforts. To embrace data visualisation is to accept the responsibility: we owe it to patients and to their families and communities, to drive fast, accurate and informed decisions. Every innovation in visualisation is a step towards more responsive care, improved health and enhanced quality of life. Clinical research is not an abstract enterprise; it touches all of us – directly or indirectly – and demands that we innovate not only for efficiency, but for the well-being of society.
Evolution and Revolution
Innovation in clinical research can be evolutionary – incremental improvements that accumulate over time – or revolutionary, marked by rapid, transformative change. Once a new standard is established, there is often no going back: just as society abandoned stone wheels for more advanced tire technology, so too does clinical research embrace new tools and methods that offer undeniable advantages. No matter your background or where you start, meaningful innovation and significant impact are always possible. History and industry show that big ideas can come from anywhere, proving that true progress is driven by vision, not by size or tradition. The lesson is clear: impact is not determined by the size of the organisation, the tenure of an individual, or the weight of legacy, but by the willingness to innovate, adapt and challenge the status quo.
Adaptation and User-centricity
History is filled with examples of major companies failing because they did not adapt. BlackBerry, once the undisputed leader in mobile communications, was overtaken by Apple – a company that understood the evolving needs of users and continuously innovated to meet them. Blockbuster Video succumbed to the onslaught of Netflix and streaming services, because it failed to adapt to technological shifts and changing consumer expectations. The lesson for clinical research is unmistakable: technical prowess alone is insufficient. Success belongs to those who innovate with the end user in mind, simplifying complexity and delivering solutions that are truly adopted and used.
Technological Evolution
The evolution of data management and statistical programming in clinical research is emblematic of the broader transformation
underway. Printing out code for manual review, poring over paper case report forms (CRFs) and maintaining mountains of paper documentation were once standard practice. Today, advanced validation, electronic data capture (EDC) systems and real-time analytics have supplanted these inefficient methods. The adoption of EDC and real-time data access allows researchers to spot trends, identify safety signals and respond more quickly than ever before. But such advances only realise their potential when designed with the user in mind – when visualisation and access are tailored to the needs of clinicians, safety teams and decision-makers.
Simplicity, Real-time Access and End-user Focus
To maximise the impact of data visualisation in clinical research, several guiding principles must be observed:
• Simplicity: The most effective visualisation is the one that is easily understood and actionable by its intended audience. Overly complex displays risk obscuring the message.
• Real-time Access: In a fast-moving field, delays in information can mean missed opportunities or increased risks. Real-time data access and visualisation empower stakeholders to respond promptly.
• End-user Orientation: The ultimate test of a visualisation tool is its utility to those who must act on its insights – clinicians, data managers, safety teams, reviewers and sponsors. Their needs should guide every stage of design and implementation.
• Customisation and Flexibility: No two studies or sponsors are alike. A robust visualisation platform must accommodate diverse data sources, evolving standards and unique stakeholder requirements.
• Integration with Decision-making Processes: Visualisation is not an end in itself; it must be embedded within the broader context of decision-making, enabling timely and confident action.
Curiosity, Boldness and Resilience
The future of clinical research belongs to the curious, the bold and the resilient. It is not the size of the company or the depth of experience that determines impact, but the willingness to innovate, adapt and put people at the heart of every solution. Data visualisation is a powerful lever for transformation, rendering the complex simple, the invisible visible and the inert actionable. By embracing the best of technology and the wisdom of user-centric design, we can bridge the gap between insights and action – delivering not only improved research outcomes, but tangible benefits for patients and society.
Let us challenge ourselves to be curious, be bold, be resilient. Innovate not for innovation’s sake, but for the lives that depend on our insights – and let every visualisation be a catalyst for positive change in clinical research.
Craig McIlloney
Craig McIlloney, Senior Vice President, Catalyst Flex, brings 25 years of experience in drug development. He oversees the global execution of functional services across multiple therapeutic areas and operations and expansion across data management, biostatistics, statistical programming, medical writing, quality, analytics and systems. He earned a B.S. (Hons) degree in statistics from the University of Glasgow, and an M.S. in applied statistics from Napier University, Edinburgh. He is a chartered statistician with the Royal Statistical Society and was previously a director of the Statisticians in the Pharmaceutical Industry.
Beyond Manufacturing: Strategic Clinical Supply Management for Global Trial Success
Clinical trials are the critical stages in which scientific innovation is tested and validated in patients, collecting data that will transform experimental therapies into approved treatments. While therapeutic efficacy remains the ultimate driver, the practical execution of packaging, labelling and distribution determine whether an investigational therapy reaches trial participants on time, in stable condition and in full regulatory compliance. Selecting the right partner to execute these activities is not simply a procurement exercise. It is a strategic decision that directly influences patient safety, cost control and trial continuity.
The critical clinical trials needed to establish safety and efficacy as well as providing registration data, are typically large, global and complex, in design. This complexity heightens operational risk from supply chain disruptions to regulatory misalignment. The ability to anticipate and manage these risks is now a differentiator between trials that run smoothly and those that stall.
Early Engagement: Designing for the Full Trial Lifecycle
Early engagement is one of the most reliable predictors of operational success. When sponsors bring in a CDMO able to complete appropriate planning before the first patient is dosed, they gain the
ability to create a coherent, phase-appropriate supply chain strategy that can flex as the study advances.
Proper early preparation allows packaging formats, dosing strategies and labelling requirements to be designed in direct alignment with the therapy’s specific formulation whether an oral solid dosage, sterile injectable, prefilled syringe, or autoinjector. Early engagement provides time to adjust plans in response to changes in the clinical design. Many sponsors underestimate the impact some changes may have on trial demands and failure to adjust can have a significant negative impact. Maintaining detailed forecasts throughout the planning phase will ensure sufficient supplies are available for uninterrupted trial management.
Early planning also allows regulatory compliance to be addressed with foresight. This includes U.S. FDA guidelines, European Medicines Agency (EMA) requirements, country-specific labelling laws and packaging language rules. The earlier these are incorporated into design, the less rework is needed later, reducing both cost and time to market.
As Ed Groleau, explains, ‘Sponsors who involve us at the design stage benefit from a strategy that can grow with them. We look not only at the first shipment but also at the eventual global footprint, so nothing is built in isolation.’
Packaging Strategy: Safeguarding Product and Supporting Patients
The primary role of clinical trial packaging is to protect product integrity which helps prevent degradation, avoid contamination and maintain stability under the appropriate environmental conditions. Yet in today’s trials, packaging also supports patient adherence, dosing accuracy and cost efficiency.
In early-phase studies, smaller patient numbers allow for greater flexibility. Bottles or basic vials may suffice, offering a costeffective way to deliver products while data are being gathered on dosage, stability and patient tolerability. These formats allow quick adjustments if dosing regimens change. In contrast, later phases require packaging solutions that can be standardised across larger production runs, such as blister packs for oral solids or prefilled syringes for injectables, with an eye on potential commercialisation.
Regulatory compliance is a constant throughout. Labels must present information clearly, conform to local and international guidelines and often be translated into multiple languages. For multicountry trials, even subtle differences such as the order in which dosing instructions appear, can affect approval timelines. This makes early collaboration between supply managers, regulatory affairs teams and packaging designers essential.
Patient-centricity must be embedded in packaging strategy. Complex opening mechanisms, confusing dose presentations, or poorly legible labels can undermine adherence. For blinded studies, packaging must prevent unintentional unblinding while remaining user-friendly.
Distribution and Logistics: Connecting Manufacturing to the Patient
Once packaging is complete, the focus shifts to distribution; an area where precision, compliance and foresight are vital. The journey from manufacturing site to patient often spans continents, climates and customs authorities, each with its own potential points of failure.
Temperature control is one of the most critical factors. Whether the requirement is controlled room temperature, refrigerated, or frozen, conditions must be maintained throughout transit. Relying on unvalidated shipping methods, such as ad-hoc gel pack arrangements, exposes the trial to product loss and compliance risk.
International shipments introduce additional complexity. Sponsors must know the import regulations of each destination country in advance, including required documentation, duties and value thresholds. The intended use of the product, whether for research only or clinical administration, influences customs classification and clearance requirements. The designated importer of record must be confirmed before shipment; without this, goods may be held indefinitely at the border.
Logistics & Supply Chain
Timing is also critical. Many countries require a ‘green light,’ process, involving pre-approval of paperwork and, in some cases, import permits. Depending on the country, these steps can take a few days to several weeks. Building these timelines into operational planning prevents delays in site activation and patient dosing. Selecting a CDMO with the knowledge and experience to provide guidance through these requirements is critical for ensuring flawless execution of the trial.
For high-value or irreplaceable products, such as cell and gene therapies, CDMOs should incorporate technology like GPS-enabled tracking with geofencing, real-time environmental monitoring and redundant contingency planning. Even for less sensitive products, these tools add a layer of assurance and visibility that supports both compliance and proactive issue resolution.
Scaling Up: Meeting the Demands of Later Phases
The logistical leap from Phase I to Phases II and III is profound. In Phase I, small patient populations and fewer sites allow for nimble, adaptive packaging and distribution strategies. Later phases, with larger enrolment and global reach, require a shift toward industrialised processes.
Regulatory diversity becomes a central challenge. It is a wellknown fact that labelling must conform to varying national standards, however, other aspects such as the requirements to complete Qualified Person (QP) release may be unknown or overlooked. Failure to account for everything required to progress from bulk drug to kit delivered to sites can cause detrimental delays. Having an experienced supply chain manager involved in the planning and execution of the trial can avoid these pitfalls.
Synchronising manufacturing, packaging and distribution with real-time enrolment data becomes essential to prevent both stock shortages and costly overproduction. Components of the process, from primary packaging to secondary labelling, can be adjusted or expanded without redesigning the entire system. This flexibility is particularly valuable when enrolment trends diverge from projections or when studies expand into new geographies mid-trial.
The Human Factor: Expertise and Cultural Fit
Technology and infrastructure are critical, but it is people who ultimately determine whether a supply chain strategy succeeds. The most effective CDMOs embed themselves into the sponsor’s team, providing not only operational execution but also strategic counsel.
By harnessing the experience of supply chain professionals bringing multidisciplinary knowledge including quality assurance, formulation science, regulatory affairs and global logistics, CDMOs can cultivate a team that operates as an extension to their client’s business. They anticipate bottlenecks, whether regulatory, logistical, or production related and intervene before these issues affect patient dosing. Communication must be constant and transparent, with regular planning calls, data-driven status updates and rapid decisionmaking when conditions change.
Cultural alignment matters. When a CDMO shares the sponsor’s commitment to patient safety, trial integrity and long-term success, the relationship evolves beyond a transactional contract into a true operational alliance.
Technology as a Supply Chain Enabler
In a global trial environment, technology is a powerful enabler of visibility, control and compliance. Integrated digital platforms allow real-time monitoring of shipment conditions, automatic updates to
Logistics & Supply Chain
expiry dates and instant inventory status across depots and clinical sites. Forecasting tools align manufacturing output with actual enrolment patterns, reducing both shortages and waste.
While no system can replace experienced judgment, technology amplifies operational capability. CDMOs that can integrate data from their global logistics network, packaging operations and clinical supply managers and convert it into a digital, comprehensive, ondemand format, enable sponsors to make informed, timely decisions. These capabilities not only support compliance but also streamline the preparation of regulatory submissions.
Risk Preparedness: Planning for the Unplanned Disruptions can still happen in long-running, multinational trials. Weather events can close airports, geopolitical instability can disrupt transport routes and manufacturing issues can delay batch release. The most resilient programs are those that prepare for these possibilities in advance.
Resilience begins with diversification. Secondary suppliers and depots are qualified in key regions to provide redundancy. Safety stock is maintained in proportion to manufacturing lead times. Alternative logistics routes are mapped for high-priority shipments and contingency protocols for temperature excursions, customs delays, or shipment loss are documented and rehearsed.
Brian Keesee, President, Clinical Trial Services at PCI Pharma Services states, ‘Every clinical program will encounter unexpected turns. The difference between a minor adjustment and a major disruption comes down to the quality of the planning you do before the first shipment leaves the depot.’
Partnership as a Competitive Advantage
In the high-stakes world of clinical research, operational excellence in packaging, labelling and distribution is as essential to trial
success as the therapeutic science itself. Sponsors who view their CDMO as a strategic partner, not just a service provider, are better equipped to navigate complexity, control costs and protect patient safety.
Edward Groleau, Sr. Director Clinical Supply Chain, has over 30 years of experience in pharmaceutical drug development on both the pharma and vendor sides. The first half of his career was spent in various laboratories from analytical method development, solid state characterisation and polymorph screening, to stress degradation and chemical characterisation. He left the labs and moved into clinical supplies in 2003 providing all aspects of CSM support to maintain clinical programs. He joined PCI in 2018 and became Sr. Director of PCI’s Supply Management And Readiness Team (SMART).
We have seen the value of early CRO engagement to overcoming the challenges that come with conducting trials and bringing products to the UK. By bringing our regulatory and quality experts into the planning process early, companies can streamline their pathways. This experience shows that when companies get the right support from day one, they're better equipped to avoid common pitfalls and meet the necessary regulatory standards whether that's in the UK, the EU, or globally.
Edward Groleau
Brian Keesee
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Clinical Trials: A Logistical Nightmare?
For clinical trial managers, the list of planning variables can seem endless. Cohort selection and patient recruitment, regulatory engagement and compliance, data management and security; each aspect presents unique challenges that could result in trial failure if not well managed. Logistics is another potential headache, with trials requiring global transport of medicines, hazardous materials, patient cells and samples.
Clinical trials are one of the most demanding areas within life science logistics, requiring efficient delivery of novel, sensitive medicines all over the world. These trials often involve numerous cross-border shipments with associated customs requirements. Whatever the shipment type, it is crucial to protect the integrity and quality of the medicine or sample, to ensure that the clinical trial is safe and that data generated from the trial is accurate.
So, is clinical trial logistics as nightmarish as it sounds or could it actually present an opportunity for the industry?
Novel Treatments = Novel Challenges
In the development of novel treatments, the more innovative the treatment, often the higher the potential impact for patients globally. As we’ve seen with the rise of biologic-based treatments, from monoclonal antibodies to cell and gene therapies, patients can experience lifechanging results when successful. However, these treatments present their own unique challenges throughout development, manufacturing and delivery. Often, the most innovative ideas are the most challenging to develop, as completely new techniques are required.
The same is true in logistics. Unlike traditional small molecule drugs that can have long shelf lives and broad viable temperature ranges, medicines based on biologics require precise control of their temperature, storage and delivery to ensure they remain effective and safe. It also places strict limits on delivery times and any delays could result in whole batches being lost, risking the success of the trial and the well-being of the patients.
For autologous cell therapies, these challenges are amplified as the patient’s own cells are extracted, shipped to wherever they are processed and then returned to the patient as a treatment. Time is of the essence and there is a lot of pressure to get it right!
Compliance at its Core
Transportation regulations for pharmaceuticals and life science substances are incredibly strict and with good reason. Any deviation in the state or quality of the product can impact patient safety, so ensuring the integrity of the products is maintained throughout the supply chain is critical. Regulations vary globally and any noncompliance can lead to recalls, fines, and in the worst-case scenario, severe risks to patients. Furthermore, regulations are constantly changing, so being aware of the transport regulations that apply to your product is crucial.
In order to comply with international customs requirements and regulations, each shipment must demonstrate that it maintains
temperature stability and passes drop tests. There are strict performance criteria for packaging and it must be qualified in line with industry standard protocols, such as the International Safe Transit Association 7D (ISTA7D) temperature test for transport packaging.
For air-based transportation, International Air Transport Association (IATA) requirements apply. These IATA requirements specify the classification, packaging, labelling, documentation and handling compliance requirements for goods, especially for hazardous materials. There are similar requirements for road, rail and sea transportation, all based on the relevant UN modal regulations.
For cell and gene therapies, chain of custody requirements mandate that each shipment is clearly monitored throughout its journey to prevent any tampering or potential damage. Documentation and traceability requirements add another level of complexity to an already challenging process. Staying up to date with all standards is therefore extremely important and demonstrating compliance is key for regulatory approval.
International Customs Regulations and Avoiding Delays
Customs requirements vary internationally, so clear and accurate labelling is vital. With fragile products, any delays at customs could result in temperature moving outside of the viable range. For example, a delay to a cryogenic shipment may result in warming without refreshment of the dry ice or liquid nitrogen. This risk is further amplified in decentralised trials or studies involving remote participation as materials must travel further and for longer, often also requiring them to be handled more frequently.
As a truly global industry, changes to trade agreements and associated taxes and tariffs can have a major impact on international logistics, both in cost of development and in possible delays. Navigating these complex financial and legal obligations is crucial for maintaining compliance and ensuring smooth operations.
Collaboration is a Game Changer
So far this may all sound like an endless list of potential catastrophes,
Logistics & Supply Chain
Case Study: Bringing Innovation to Clinical Trial Supply Chains
Increasingly complex demands for international clinical trials are leading drug developers to collaborate with specialist logistics providers to manage their supply chains. The logistics specialist manages all the study samples, including providing validated packaging and transporting the temperature-controlled samples, liaising with the collection/delivery sites, as well as designing and implementing contingency plans throughout.
Challenges
With over 300 participants spread across five collection clinics in the EU and Norway and a varied range of samples, including DNA and plasma, a global pharmaceutical company required secure, seamless and compliant delivery throughout its clinical trial.
This clinical trial included EU and non-EU countries, plus a wide range of samples at each collection site. The multi-site study included remote locations, requiring a worldwide network to ensure the seamless flow of shipments and information, whilst utilising the most efficient transport lanes.
Solution
Contingency plans were created for each phase of transportation, including sourcing replacement packaging and designing secondary flight plans in case of any airline delays.
‘As part of our preparation for this clinical trial, we created Standard Operating Procedures tailored to the trial’s requirements and advised each office of the paperwork and packaging requirements. By ensuring all the preparation was complete, collection and delivery was made in the shortest possible time as factors such as customs clearance were processed and prepared prior to the arrival of the samples at the airports.’ – Dennis Schreiber.
Experienced drivers arrived with validated packaging and placed the samples in the boxes, often directly in front of the customer, thereby ensuring correct handover of valuable materials. Often, the drivers were collecting up to eight sets of samples at the same collection site, many having different temperature requirements, including dry ice and controlled ambient.
Whenever required, local experts were immediately available to help expedite the import process, all while maintaining the highest levels of compliance standards in the industry.
but there is hope! Collaborating with experts who are familiar with the challenges of clinical trial logistics could help to avoid delays and ensure compliance. Should an unavoidable delay occur, proactive management may allow for any risks to be mitigated, whether that is recharging dry ice or finding alternative routes.
Logistics experts, packaging teams and cold chain providers must work together to simplify the process and create solutions that maintain the desired temperature for extended periods and reduce the potential for hazards, mitigating risk against unexpected transit delays.
Impact of New Technologies
New technologies are facilitating clinical trial logistics and their adoption is helping to drive efficiency. Real-time shipment tracking and temperature monitoring are enabled by Internet of Things (IoT) technology, which in turn facilitates regulatory compliance. The data obtained through these technologies can then be used to develop models that will help to plan future trials and ensure enhanced efficiency and performance.
As an industry, we share a purpose to ensure that patients receive critical medications, vaccines and biologics safely, reliably and on time. Every innovation developed in cold chain packaging and logistics is driven by this ambition. When cold chain solutions are more reliable and durable, life-saving treatments arrive in optimal condition. Smarter tracking, advanced insulation and reusable packaging don’t just enhance supply chains; they facilitate essential research and development, enable the delivery of safe and effective clinical trials and ultimately impact patient care, making treatments more available and dependable worldwide.
Bailey Coppage
Bailey Coppage, US Customer Solutions Manager, Biocair, has worked in the logistics industry for five years and has been with Biocair for over three years. Since joining Biocair, Bailey has worked extensively within the cell and gene therapy department, onboarding CGT clients, creating standard operating procedures, developing work instructions and building other resources to ensure CGT shipments are properly handled and efficient logistics solutions are delivered across the life science industry.
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