The Time is Right to Disrupt Clinical Cancer Trials and Accelerate Innovation
Contributed Commentary by Gaelan Ritter and Viraj Narayanan
August 18, 2021 | Life science stakeholders are continually looking for more efficient, cost-effective ways to bring breakthrough therapies to patients, including those with cancer. Yet the fundamental design and execution of clinical trials has remained largely the same for years.
As we prepare for a new decade, marked at its start by the astonishingly speedy development of a vaccine for COVID-19, clinical trial sponsors have the opportunity to disrupt the traditional drug development process like never before.
The growing maturity and value of real-world data (RWD), including EMR data, claims, and patient-generated information, holds incredible potential for sponsors, clinicians, patients, and data companies to see dramatically better outcomes.
It’s time to turn that potential into reality. We have the tools we need. Now, we must work together to drive positive changes throughout the entire lifecycle of scientific research and rise to the challenges of a data-driven future.
Here are some of the key steps we must take as an industry to get to the next level of innovation and successful outcomes.
Focusing On Diversity And Inclusion To Create Truly Representative Trials
Currently, the majority of clinical trials for cancer therapies are simply not representative of the patient populations who may benefit from the therapy in question.
Our established enrollment processes are largely to blame, because clinical research builds on previous research. When a sponsor is starting a trial and considering which sites to employ, they look at the history of each potential site in trials with the same phase and similar indications. But if the physicians at that site have a patient population is 95% Caucasian, then the patients they enroll in a trial will likely be largely Caucasian. There isn’t any negative intent, of course, but the system is perpetuating unwelcome bias.
Incorporating real-world data into enrollment and recruiting can help us move beyond this strategy. By leveraging EMR data and other data sources to identify patients of diverse backgrounds and appropriate clinical histories, we can proactively reach out to populations and additional sites that may otherwise be overlooked.
Exploring Predictive Analytics to Improve the Clinical Trial Experience
Clinical trials can restore hope to millions of patients, including those who have exhausted other avenues of treatment for their cancers. But participating in a trial can also spark anxiety and uncertainty. We don’t want anyone to feel like a guinea pig when enrolling in a trial, yet there is too much experimenting and not enough prediction before the trial starts.
We owe patients the best possible chance at a positive outcome. We need better data to make sure we are meeting that obligation.
Predictive algorithms can help us quickly and efficiently enroll patients who may benefit from the trial. As RWD becomes more integrated into the enrollment process, predictive analytics can help us perform biologic modeling of potential outcomes before we even start.
This, in turn, will allow sponsors to offer more targeted information about possible side effects or outcomes based on the specific clinical features of each individual. That’s a lot more comforting than handing participants a long laundry list of potential safety risks with little indication of the likelihood of experiencing a problem.
With predictive modeling, we can more safely enroll patients with a variety of existing conditions and factors that mirror what patients look like in the real world. Predictive analytics rooted in RWD can make it as easy as possible to participate in trials, encouraging higher rates of enrollment and expanding our ability to innovate and iterate.
Fast-tracking The Adoption Of Real-world Insights From Drug Design To Surveillance
RWD can be extremely valuable across the entire course of cancer drug development. We need to bring data to researchers and clinicians in a way that provides digestible, actionable recommendations instead of huge, unfiltered datasets.
If we can offer meaningful engagement with RWD along every step of the pathway, we can ensure that stakeholders have a more detailed, accurate understanding of what they are designing, what the outcomes should be, and why those specific outcomes are the most advantageous for the science they are trying to accomplish.
As researchers move through the trial, they need to refer to this data and make comparisons to understand how the asset is going to exist outside of the very controlled microcosm of the trial setting.
When an agent gets deployed in the real world, the tails of the bell curve suddenly get a lot bigger. In the after-market stage, there are huge numbers of people in those tails, and we must ensure that therapies are safe and effective for those individuals, too.
We need to go beyond traditional data sources to monitor the safety and efficacy of agents as they interact with all the varied, unpredictable factors that influence outcomes in real life. Real-world data has to become an integral, fundamental part of the way we perform all our activities, which it hasn’t been so far.
Embracing Leadership And Fostering Collaboration Between Stakeholders
Sponsors, providers, and data companies need to partner closely with one another so we can pilot and test some of these capabilities and develop a track record of success.
We can do this by publishing our results in respected outlets, participating in panels at conferences and other events, and being proactive and transparent with regulators. If pioneering companies take an active leadership role in education and integration of RWD and other innovations, we can bridge the gaps between stakeholders and better understand how to help one another succeed.
The more we collaborate and communicate in forums that include sponsors, clinicians, patients, caregivers, and data experts, the more we can all benefit from the work we are performing.
Real-world data is the lynchpin that will help us disrupt the status quo and accelerate innovation in cancer research. With robust, comprehensive, and representative datasets feeding the next generation of clinical trials, we can achieve better outcomes for patients than ever before.
Viraj Narayanan, Vice President of Life Sciences, leads COTA’s life sciences business. Viraj and his team are responsible for developing, managing and growing life sciences partnerships that leverage COTA’s real world evidence and analytic solutions. He developed the first set of life science partnerships that will leverage COTA’s Real World Evidence for regulatory filings, accelerating the drug development timeline. Prior to COTA, Viraj spent nearly a decade in healthcare strategic consulting and 5 years in the oncology space including with Sylvester Cancer Center at the University of Miami, Pfizer, Sanofi, and GSK. He was previously a Principal at Heidrick & Struggles Consulting and Decision Strategies International. Viraj started his career in the infectious disease R&D department at Centocor, a biotechnology company part of J&J. Viraj earned a BS in Decision Science from Carnegie Mellon and an MBA from the Wharton School at the University of Pennsylvania. Viraj is passionate about the potential impact of healthcare technology and has co-authored articles on Healthcare Nudge Strategies in Inc Magazine as well as on Clinical Trial Innovation with Real World Evidence in Stat News. He can be reached at firstname.lastname@example.org.
As the head of Analytics Innovation and Digital Health, Gaelan Ritter and his team are responsible for leading cutting edge real-world data alliances and most importantly creating and developing innovations across R&D. He co-leads the BMS digital initiative for global drug development, which is enabling a spectrum of digital solutions, including several types of decentralized trial capabilities. Gaelan is an industry leader in the development and infusion of digital innovation solutions to enable optimization of pharma drug development. In past roles Gaelan has led and developed strategic partnerships with large academic medical centers and networks. He has also supported trial design and start-up for the BMS oncology and immunology programs. This experience led him to develop industry leading trial design software and processes that create digital protocols and feed downstream systems and processes. He is passionate about not only the ideation and creation, but the development and business change that creates lasting advancement in the industry. Gaelan holds an MBA from Temple University along with masters’ degrees in human physiology and biophysics from Georgetown. Outside work, Gaelan lives in southeastern Pennsylvania with his wife, enjoys traveling around the globe, cooking, and restoring their historic home. He can be reached at Gaelan.email@example.com.