Holistic Clinical Data Transformation: Setting the Stage for AI-Driven Productivity
Presenters:
Elisa Cascade, MBA, Chief Product Officer, Advarra
Karen Correa, PhD, VP, Head of Global Clinical Operations, Takeda
Raj Indupuri, CEO, eClinical Solutions
Dr. Nimita Limaye, PhD, Research VP, Life Sciences R&D Strategy and Technology, IDC Health Insights
Jeffrey A. Meckler, CEO, Indaptus Therapeutics
Moderator: Barnaby Pickering, Managing Editor, Custom Content, Citeline
KEY TAKEAWAYS
Increasing trial and data complexity is forcing companies to rethink their approach to clinical research.
Sponsors, sites, and third-party vendors can foster efficiency by collaborating without compromising competitiveness.
Advanced technologies can increase productivity and shorten cycle times, but must be carefully evaluated before adoption.
Investing in AI technologies that quantifiably improve the patient experience is a path to getting long-term ROI.
in partnership with
OVERVIEW
Clinical trial cycle times have seen little improvement over the last 30 years, despite huge advancements in technology. At the same time, these new technologies have increased the amount of clinical data that can be collected. While this data promises to yield richer insights and benefit patients, the sheer volume of data produced makes it challenging to realize its full value.
To address these challenges, adopting an interoperable clinical data infrastructure that drives collaboration between sponsors, trial sites, and third-party solution providers is mission critical. Having this foundation in place can transform how data is collected and utilized, ultimately improving productivity and accelerating cycle times. AI and ML technologies hold great potential to shape meaningful clinical data transformation, however, if there isn’t a modern data infrastructure in place, productivity gains promised with these emerging technologies will remain elusive.
CONTEXT
In an event held at the Pendry, San Diego, the panelists discussed the continually evolving clinical trial landscape and how through strategic alignment of people, process, and technology, pharmaceutical organizations can lay the foundations for holistic, AI-driven clinical data transformation that boosts productivity and delivers meaningful return on investment (ROI).
KEY TAKEAWAYS
Increasing trial and data complexity is forcing companies to rethink their approach to clinical research.
The previous decades have seen huge advances in the understanding of disease pathways, drug targets and treatment mechanisms, increasing the complexity of every element of clinical research—from trial design through to supporting technologies, data sources, structures and collection modalities.
“The complexity of clinical trials is not just increasing but exploding, compared to where we were even five years ago. With increased data chaos, everything downstream is being impacted and that adds to cycle times.”
– Raj Indupuri, eClinical Solutions
Trials have become more complex in large part because the therapies being developed today, such as cell and gene therapies, are much more sophisticated, Jeffrey Meckler, CEO, Indaptus Therapeutics, noted.
“The trials being done now are not the simple trials that we were doing for blood pressure drugs 30 years ago. Now trials require a lot more components, data, and interaction with the patients and the investigators.”
– Jeffrey Meckler, Indaptus Therapeutics
One of the main challenges of dealing with a lot more data is efficiently connecting the ecosystem of sponsors and sites with better data-flows and end-user experiences. For example, enabling single sign-on for all systems within an organization—from HR to EMR systems, as well as sponsor/site systems—can facilitate a more seamless flow of data and, with that, greater efficiency.
“Sponsors and CROs really need to think about conducting trials from the sites’ perspective and making things more straightforward by connecting site and sponsor technologies.”
– Elisa Cascade, Advarra
In this context, the adoption of new data-harnessing technologies and processing capabilities is core to improving trial efficiency. However, Dr. Nimita Limaye, PhD, Research VP, IDC Health Insights, described the need to overcome the pharma industry’s historic reluctance to adopt new technologies.
“Incremental
improvements in efficiency gained by fine tuning processes won’t be enough. The only thing that’s going to really drive change is leveraging data, technology, and analytics.”
– Dr. Nimita Limaye, PhD, IDC Health Insights
Sponsors, sites, and third-party vendors can foster efficiency by collaborating without compromising competitiveness.
This need for trial sponsors to compete on intellectual property and not on processes spurred a discussion around how stakeholders can collaborate on some aspects of drug development while remaining competitive with respect to others.
“The competitive space should be around does your drug work better and is it safer—not around how we do processes or recruit patients.”
– Karen Correa, Takeda
“Having data standards [among technology vendors] has been a linchpin in enabling integration between different site and sponsor technologies. Once a common standard has been established, technology can be connected to open the flow of users, documents, and data across systems, resulting in decreased duplication of effort, time savings, and improved compliance. A great example is SAML for single sign-on which will reduce the number of unique systems that sites log into for a single study (currently 22 for a sample oncology study).”
– Elisa Cascade, Advarra
Designing clinical data technology solutions with built-in interoperability enables pharma and biotech companies to avoid spending time on workarounds and internal integrations. Dr. Limaye noted that “There is a shift happening in the industry right now. Technology companies are building integrated data repositories where all the data is sitting in one place, so that pharma companies can get the patient 360 view and slice it and dice the data in the ways that they want to.”
Advanced technologies can increase productivity and shorten cycle times, but must be carefully evaluated before adoption.
The potential for AI and machine learning (ML) technologies to transform clinical trial processes so that they are more efficient, thus resulting in shorter cycle times, is immense.
“If you look at the entire value chain from design to analysis and submission, there are so many areas in terms of how you can embed AI and automate,” Raj Indupuri, CEO, eClinical Solutions, said. Citing the data science team at eClinical, he said apprehension about AI replacing people is largely unfounded, and that instead, innovation could be significantly amplified with AI capabilities. “I cannot hire 20 or 30 more engineers,” he explained. “But if I had virtual [AI] software agents, productivity would be scaled exponentially to accelerate our roadmap and outcomes for our customers.”
It is important, however, that the adoption of AI and ML technologies be done in a responsible, human, and patient-centric way. One key concern is that, should focus be fully applied to these technologies, human skills could be lost. Yet, the reality is that many AI-driven processes will require human-in-the-loop supervision, and so, for the foreseeable future, having highly skilled subject matter experts will become more critical than ever.
User experience must not be neglected, also. With advanced technologies, many trial participants and site staff will require training or upskilling, so it is essential that technology adoption and implementation are preceded by user group testing. Karen Correa, VP, Head of Global Clinical Operations, Takeda, said the industry often suffers from “tunnel vision” when it comes to assessing AI adoption through the prism of end users.
“How many of you have had a site call you with the patient sitting in front of them while having problems with whatever the device is? The clin-ops team can’t answer the question and you try to get someone from the company to answer the question and you know what—no one knows what that feels like because we did not think about the user experience piece of it.”
– Karen Correa, Takeda
A third element of responsibly adopting AI/ML-powered clinical data technologies is ensuring that they are capable of contextualizing and correctly interpreting the data they ingest. “It’s not just about capturing data and running algorithms on it, but about contextualizing those data points because that’s what’s going to yield meaningful insights,” Dr. Limaye said.
“There is an opportunity here to think [about adopting advanced technologies] from an outcomes perspective, for all stakeholders across clinical development, and this mindset will transform how we manage clinical trials.”
– Raj Indupuri, eClinical Solutions
Examples of applications that could improve cycle times and boost productivity include capabilities that:
Support the design of study protocols with fewer amendments or deviations later.
Provide a centralized location for data across all sources—eliminating data silos and disparate systems and processes to manage.
Have automation capabilities for data mapping, classification, and workflows.
Offer a future-proof clinical data infrastructure supporting the use of modern techniques like Artificial Intelligence and Machine Learning
Optimize patient enrollment plans by using predictive models that simulate the outcomes of alternative enrollment criteria.
“When
we think about patient centricity and the people we interact with at the sites, including clin-ops staff, it’s about how we evolve those components [where AI] can really make a difference.”
– Jeffrey Meckler, Indaptus Therapeutics
Investing in AI technologies that quantifiably improve the patient experience is a path to getting long-term ROI.
As pharma companies intensify their investments in AI, they face the uncertainty of obtaining ROI on those investments. And whereas measuring the ROI of the broad introduction of new technologies is feasible—for example, 110 drugs approved per year after the introduction of such technologies versus 100 prior to that—tracking that metric for a single site trial is much harder.
In the most complex trials for novel therapies, proxy metrics may be the way to go here.
“What I believe is going to be the ROI measure of the future is how [a new technology helps improve] the end user and patient experience.”
– Dr. Nimita Limaye, PhD, IDC Health Insights
A related metric to quantifying the patient experience is the ability of AI technologies to predict patients’ interest and willingness to participate in clinical trials.
Last but not least, given the finite amount of money companies have to invest in R&D and their interest in doing more R&D for more drugs, AI-supported trials that improve efficiency and move processes along faster can free up resources to achieve that goal, Correa said.
CONCLUSION
While there is significant hype about the promise of AI and ML to address cycle time and productivity challenges, establishing an interoperable data and analytics infrastructure is foundational for unlocking the potential of these emerging technologies. At the heart, solid foundations accelerate value, enable the innovation-led growth required to keep pace with scientific breakthroughs, and—most importantly—improve patient outcomes.
“I’m very optimistic
about the next 2 or 3 years, and the pace of change. The core technology is there, the intent is there . . . and to be cost effective and efficient, the old way of doing things will not cut it. I’m looking forward to the way the industry is going to be modernized—the opportunity is immense.”
– Raj Indupuri, eClinical Solutions
BIOGRAPHIES
Elisa Cascade, MBA Chief Product Officer, Advarra
Elisa Cascade, Chief Product Officer, is responsible for driving Advarra’s technology product vision and management. She brings more than 30 years of experience in the clinical research industry with a focus on using technology to transform clinical research for all stakeholders.
Prior to joining Advarra, Cascade held the position of Chief Product Officer for Science 37 where she was responsible for setting the company’s product vision and roadmap and leading product management, business analysis, design, and strategic customer support. Previously, she held several key leadership positions including Executive Vice President and Product Line Executive for eCOA at Clario, Chief Product Officer at DrugDev, an IQVIA Company, and Vice President of the Digital Patient Unit at Quintiles (now IQVIA).
Cascade currently serves as the Chair for the Association for Clinical Research Professionals Board of Trustees.
Cascade earned a Bachelor of Science degree in Economics from the University of Michigan and a Master of Business Administration degree from The Wharton School of the University of Pennsylvania.
Karen Correa, PhD
Vice President, Head
of Global Clinical Operations, Takeda
Dr. Karen Correa is the Vice President, Head of Global Clinical Operations at Takeda, where she is responsible for the advancement of the portfolio and execution of global clinical trials. Her 30+ years of clinical research experience cover a large range of settings and venues including, benchwork, clinical site, CRO, as well as both large and small pharma organizations and has spanned across multiple therapeutic areas.
She also leads the “Diversity in Clinical Trials” initiative at Takeda and is known as an SME on this topic for the past 25 years. Correa serves as a board member of East Carolina University Alumni Board and CAMcare Health Corporation, a Federally Qualified Healthcare Center in South Jersey.
Raj Indupuri Chief Executive Officer, eClinical Solutions
A technologist with over 25 years of industry experience, Raj Indupuri is responsible for establishing the eClinical Solutions vision and future-looking technology strategy. He is deeply passionate about fostering innovation to revolutionize the Life Sciences industry with ground-breaking technologies that will modernize clinical trials and bring treatments to patients faster. As an industry veteran who has been part of the evolution of Life Sciences and clinical data management for over two decades, Indupuri has an astute business vision to realize the digital future and enable progress and potential with data and analytics at the core of the company’s innovative products and solutions. Indupuri is responsible for the overall direction and management of the company and is a Mechanical Engineer with an MBA from Boston University who firmly believes data is the new fuel that will drive human progress.
Dr. Nimita Limaye, PhD
Research Vice President, IDC Health Insights
Dr. Nimita Limaye is a Research VP with IDC Health Insights and provides research-based advisory and consulting services, as well as market analysis on key topics related to R&D Strategy and Technology in the life sciences industry. She addresses aspects such as the role of digital transformation in discovery research, e-clinical ecosystems, the role of NLP, AI, ML, DL, RPA, in transforming drug development, precision medicine, pharma R&D execution and strategic outsourcing models.
Jeffrey A. Meckler
Chief Executive Officer, Indaptus Therapeutics
Jeffrey Meckler currently serves as our Chief Executive Officer, bringing more than 30 years of financial and healthcare leadership experience to the company. Most recently, Meckler was the CEO of Intec Pharma, and prior to that, CEO of Cocrystal Pharma, transforming it from a research company into a clinical and development company. Earlier in his career, Meckler was managing director of the Andra Group, a life sciences consulting firm, and acted as a director and interim CEO of Cypress Bioscience after its acquisition by Royalty Pharma.
Meckler started his career at Pfizer, where he held a series of positions in manufacturing systems, market research, business development, strategic planning and corporate finance, which included playing a significant role in acquisitions and divestitures. He has also served as a director of QLT, Inc., Cocrystal Pharma, ClearFarma USA, Kyalin Bioscience, and Alveolus, and currently serves as director of Travere Therapeutics, where he also previously served as Chairman.
Meckler is the past President and continues to serve on the Board of Children of Bellevue, a non-profit organization focused on advocating and developing pediatric programs at Bellevue Hospital Center. He holds a B.S. in industrial management, an M.S. in industrial administration from the Tepper School of Business at Carnegie Mellon University, and a J.D. from Fordham University’s School of Law.
Barnaby Pickering
Managing Editor, Custom Content, Citeline (Moderator)
Having graduated from University College London with a master’s degree in biomedical engineering in 2020, Barnaby Pickering is passionate about cutting-edge life sciences technologies.
In his three years of writing for Citeline, Pickering has covered diverse topics including robotic surgery, organs on chips, and novel drug classes.