Three reasons why substituting real world data for certain randomized clinical trials is inevitable

The 21st Century Cures Act and planned Prescription Drug User Fee Act (PDUFA) VI are changing the regulatory environment and accelerating the rate at which evidence generated from real world data (RWD) is incorporated into regulatory decision-making.

The Network for Excellence in Health Innovation describes real world evidence as “a potentially transformative force” in the healthcare industry, “derived from medical practices among heterogeneous sets of patients in real-life practice settings, such as insurance claims data and clinical data from electronic health records.” What does this mean for the healthcare field, and in particular for the growing need for evidence in critical healthcare decision making?

With the ability to leverage technology to generate real world evidence, healthcare organizations are poised to better address complex but critical questions such as what treatments both deliver the best outcomes for patients and the best value for the healthcare system? While these questions may have previously been addressed with a randomized clinical trial (RCT) – or, more likely, been left unanswered due to the time and cost involved – rapid-cycle, real-world evidence generation can deliver the underpinnings for decision-making in approximately one tenth of the time and a small fraction of the cost. This essential evidence informs development of critical therapies, outcomes research, patient care, research on healthcare systems and quality improvement initiatives.

In one recent example, a platform that generates real world evidence through rapid-cycle analytics technology demonstrated how RWD can accelerate the “time to evidence” as compared to an RCT, with no compromise in quality. The rapid-cycle, analytics-enabled, multi-database RWD analysis was completed before an RCT analyzing the same question and yielded analogous results. The RWD analysis was completed in six months versus the four-year, seven-month duration of the RCT. In addition, the RWD analysis included 9,218 patients from a wide variety of clinical settings while the RCT enrolled 1,538 patients. By using a platform that combines best-of-breed science with leading-edge computing technology, a combined sponsor and academic team created powerful evidence to support the use of an important treatment.

The healthcare industry’s continued reliance on randomized controlled trials has become a hot topic, especially in an era when the vast flow of big data, combined with the right science, can provide high-quality evidence in observational study designs to support decision-making. From experience with biopharmaceutical and medical device companies and healthcare providers, three key benefits of RWD analysis continue to be top of mind for customers developing therapeutic insights to make smart choices in patient care:

RWD Analysis Can be a Substitute for or Supplement to RCTs
Big data has irreversibly changed medical research. There is an increasing body of literature in selected settings demonstrating RCTs can be supplemented by or substituted with observational studies. In addition, RWD costs less and has shorter "time to answer", along with the option to extend studies into ongoing monitoring systems to further demonstrate value and safety.

RWD Studies Allow for Larger Study Sizes and Broader Patient Representation
Real-world data enables rapid analyses that equal or surpass the quality of randomized clinical trials. RWD studies, for example, can draw upon large patient populations that are far more representative of all treated patients, rather than a narrow subgroup. RWD studies can also follow patients for longer periods of time, and focus on key clinical outcomes rather than surrogate endpoints.

By assessing large, representative populations over long periods of time, RWD studies allow streamlined identification of high- or low-risk patient subgroups, and can capture longer-term outcomes to inform a given product’s long-term benefit-risk profile.

RWD Studies Ensure Transparency Required by Healthcare Decision Makers
At present, the healthcare industry needs to develop guidelines to help increase payer and provider confidence in study design and methodologies to avoid potential costly mistakes in research. For any analysis to be accepted by outside decision makers, the methodology must be clear, the results must be complete, and the reporting must be transparent and must follow accepted standards. Platforms that generate real world evidence help ensure that researchers can quickly produce clinically actionable and highly accurate insights with the highest level of transparency. Ultimately, transparency is the underpinning of high-quality, widely-accepted research.

What does the future hold for RWD studies and decision-making? Understanding the value RWD brings to the healthcare landscape – such as improving clinical trials, better targeting, planning, and the ability to avoid certain trials – will ultimately enable payers and providers to make smart choices in patient care. As payers and providers complete more examples of high-profile RWD studies that could substitute for RCTs, the FDA will continue to recognize the benefits of RWD studies, providing guidance for future rulemaking. With the promise of highly accurate results, lower costs and shorter duration for studies, substituting even a small percentage of RCTs with RWD studies will be a game-changer for payers and providers.

Jeremy Rassen, ScD. Co-Founder, President and Chief Scientific Officer, Aetion:
Jeremy Rassen is an epidemiologist and computer scientist with 20 years of experience in the science and technology of big data. He was an Assistant Professor of Medicine at Harvard Medical School, where he developed cutting-edge methods for developing quality evidence using real-world data. Prior to that, Jeremy spent a decade in Silicon Valley. Jeremy was the fifth employee at E.piphany, Inc., where he was involved in the creation, sale and deployment of data-intensive applications for marketing and customer relationship management. Jeremy received his bachelor’s degree from Harvard College and his master's and doctorate degrees in Epidemiology from the Harvard School of Public Health.

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