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Real-World Evidence Opportunities for Emerging Biotech

The use of real-world evidence has greatly expanded in recent years but is still underutilized by emerging biotechs.
The use of real-world evidence has greatly expanded in recent years but is still underutilized by emerging biotechs.

Real-world data (RWD) are data relating to patient health status and/or the delivery of healthcare routinely collected from a variety of sources. Traditional RWD sources include electronic health records (EHR), claims data, and disease and product registries. Real World Evidence (RWE) is the clinical evidence about the usage and potential benefits or risks of a medical product derived from analysis of RWD.

The Role of RWD/RWE

Traditionally, RWE has played a role in the peri-launch environment to describe patient populations and to support patient safety and real-world effectiveness, as well as in economic modeling and pricing. However, RWE is being increasingly used for new product approvals, line extensions, and, to a lesser extent, label expansions. RWE trials have steadily increased from 25 in 2013 to ~200 in 2021.

The Rise of RWD/RWE

Interest in RWD/RWE has been on the upswing since 2016 when the 21st Century Cures Act set the stage for the use of RWE to support the approval of new indications and help satisfy post-approval study requirements. The FDA has since released several draft and final guidance documents regarding the use of RWD/RWE. In the two years following the release of the Framework for FDA’s RWE Program in 2018, the FDA approved 85% of NDA and BLA submissions that were backed by RWE.

In addition to growing regulatory acceptance, other drivers have contributed to increasing interest in RWD/RWE. In 2018, it was estimated that 30% of the world’s data volume was being generated by the healthcare industry, projected to reach 36% by 2025. The healthcare sector is estimated to generate more than 19 terabytes of clinical data each year. Additional data sources include wearables, social media, and patient-reported outcomes, among others.

We can now tokenize patient data and link data sources to ensure de-identification, enrich studies, and follow patients longitudinally. Such capabilities have given rise to new types of partnerships, including integrated patient registries and federated data models. Concomitantly, data analytics capabilities, including artificial intelligence and machine learning applications, are evolving.

Increasing demand from external stakeholders (patients, providers, regulators, payers/HTAs), a desire by sponsors to demonstrate value from sources beyond randomized clinical trials (RCTs), and growing interest in outcomes-based reimbursement agreements have also contributed to increasing interest in RWD/RWE.

RWE opportunities for emerging biotech companies:

  • Reduce study costs: Emerging biotechs nearly doubled the number of sponsored clinical trials in 2021 versus 2016, accounting for 42% of products filed with the FDA in 2021. Researchers have estimated that the use of RWE could reduce trial costs between 5% to 50% to expedite safety monitoring and simplify data collection.
  • Therapeutic area opportunities: In a retrospective analysis of RWE inclusion to support efficacy in regulatory submissions, oncology was identified as the main therapeutic area, followed by hematology and neurology. With >1500 products in development from 2011–2021, oncology represents the largest therapeutic area of emerging biotech pipelines. In 2021, there were 778 emerging biopharma companies with late-stage oncology pipeline activity. Neurology is the second largest therapeutic area.
  • Rare disease opportunities: Natural history studies represent an opportunity to better understand rare diseases. Additionally, regulatory submissions that include RWE generally support rare disease, serious conditions, or unmet medical needs where it is not possible or ethical to conduct an RCT. Emerging biotechs have demonstrated more interest in innovative approaches (e.g., basket trials, dose escalation/expansion studies) than their larger pharma counterparts. The inclusion of RWD/RWE is an organic next step for these companies.
  • Decentralized trials (DCTs): Before the COVID-19 pandemic, the industry saw a marked increase in DCT models, often used when anticipating challenges to patient enrollment, e.g., in geographically restricted site-based studies in rare disease. However, emerging biotech companies participated in a smaller share of DCTs than their larger counterparts, opting for more traditional trials. The pandemic brought greater acceptance and use of DCTs, including technologies to support DCT design and innovative patient recruitment. However, as of 2021, emerging biotech companies continued to under-utilize DCTs, missing opportunities to improve recruitment, foster patient population diversity, and accelerate trials.
  • Other opportunities: RWD can also be used to accelerate time to market, inform payer negotiations, inform strategies for label expansion, and understand safety and effectiveness in real-world settings, supporting greater product differentiation.

Integrated evidence generation planning

An integrated strategy can save time and reduce costs at an enterprise level. Internally, cross-functional identification and prioritization of evidence gaps in the context of scientific, market, regulatory, and payer landscapes is crucial in developing an integrated evidence generation strategy to fill evidence needs driven by external stakeholders, including patients, providers, regulators, and payers.

About the Author

Judy Lytle, Ph.D., MBEE, PMP, is the Executive Director of Real-World Evidence Study Solutions at UBC. She utilizes her extensive expertise to help biopharma develop evidence generation strategies, powered by rigorous science, that are designed to demonstrate value.

References

  1. Real World Evidence. https://www.fda.gov/science-research/science-and-research-special-topics/real-world-evidence. Retrieved April 6, 2023.
  2. Dang. 2023. Real-World Evidence: A Primer. Pharmaceutical Medicine. 37:25-36. https://link.springer.com/article/10.1007/s40290-022-00456-6.
  3. Coughlin, D. Roberts, K. O’Neill, P. Brooks. 2018. Looking to tomorrow’s healthcare today: a participatory health perspective. Internal Med J. 48(1):92-96. DOI: 10.1111/imj.13661.
  4. Wolff. 2022. What is Data Volume and How to Face Discovery Challenges in Healthcare. https://www.jdsupra.com/legalnews/what-is-data-volume-and-how-to-face-1804605/. Retrieved April 6, 2023.
  5. Rise in Real World Evidence Trials for 2021. https://www.clinicaltrialsarena.com/comment/real-world-evidence-trials/ . Retrieved April 6, 2023.
  6. Mofid, W.R. Bolislis, T. Kuhler. 2022. Real-World Data in the Postapproval Setting as Applied by the EMA and the US FDA. Clin Ther. 44(2):306-322. DOI: 10.1016/j.clinthera.2021.12.010
  7. Aitken. 2022. Emerging Biopharma’s Contribution to Innovation. https://www.iqvia.com/-/media/iqvia/pdfs/institute-reports/emerging-biopharma-contribution-to-innovation/iqvia-institute-emerging-biopharmas-contribution-to-innovation-forweb.pdf. Retrieved April 6, 2023.
  8. Marciniak interview with J. Graff, VP Comparative-Effectiveness Research at the National Pharmaceutical Council, Washington D.C. What the Rise of Real-World Evidence Means for the Pharmaceutical Industry: A Closer Look. ISPOR. 2020. https://www.ispor.org/publications/journals/value-outcomes-spotlight/vos-archives/issue/view/unlocking-the-promise-of-real-world-evidence/what-the-rise-of-real-world-evidence-means-for-the-pharmaceutical-industry-a-closer-look. Retrieved April 6, 2023.
  9. Mahendraratnam, K. Mercon, M. Gill, L. Benzing, M.B. McClellan. 2021. Brief Report: Understanding Use of Real-World Data and Real-World Evidence to Support Regulatory Decisions on Medical Product Effectiveness. Clin Pharm & Ther. 111:150-154. https://doi.org/10.1002/cpt.2272

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