Five Key Strategies to De-Risk R&D with Real-World Data

By Sujay Jadhav, CEO, Verana Health
LinkedIn: Sujay Jadhav
LinkedIn: Verana Health

In the complex, high-risk business of pharmaceutical research and development, sponsors face a challenge of picking target products with high therapeutic potential and acceptable safety profile. Then they must efficiently manage costs and timelines.

With drug development success rates remaining below 15 percent, and many compounds never reaching the commercial stage despite years of expensive effort, the industry is continually seeking new tools and approaches to improve decision-making and resource allocation.

One of the most promising recent advances in R&D efficiency is the application of real-world data (RWD). The healthcare information collected routinely in everyday clinical practice, RWD offers an invaluable window into how medical treatments and technologies perform in the broader population.

Pharmaceutical companies are integrating real-world insights throughout the R&D continuum, bolstering the relevance, precision, and efficiency of their efforts.

Recent research by Tufts Center for the Study of Drug Development (CSDD) revealed that pharma, biotech, and contract research organizations (CRO) leaders anticipate an increase in their return on investment in RWD in the coming years.

“The use of real-world data is becoming increasingly important to drug development, patient safety, and commercialization activity,” said Ken Getz, executive director of Tufts CSDD and research professor at Tufts University School of Medicine.

And with the FDA committed to realizing the full potential of fit-for-purpose RWD to generate RWE to advance the development of medical products across their lifecycle, the future prospects of RWD are bright.

Here are five key RWD strategies that industry leaders cite as effective in reducing risk and advancing the development of novel therapies.

1. Identify High-Potential Pathways

To improve odds of success, researchers are using RWD to identify areas of unmet need, better understand diseases, and uncover therapeutic opportunities.

By correlating EHR records with disease progression, genetic profiles, and treatment outcomes, researchers can uncover novel biological pathways and confirm genetically validated targets in real-life patient populations.

They can also spot treatment gaps and unexpected outcomes in routine clinical practice. These insights may point toward new indications or line extensions for existing products.

This approach enables companies to focus investment where it’s most likely to achieve measurable impact and directs resources toward programs with the highest potential.

2. Strengthen the Case for Strategic Investment

A compelling package of clinical data alone is not always sufficient to warrant further investment in today’s pharmaceutical environment. Increasingly, stakeholders, including internal portfolio leaders, payers, and providers, require a credible value proposition.

This is where RWD can provide invaluable context, showing how a therapy performs in real-world settings and how it contributes to improved patient outcomes and cost-effectiveness.

Pharma companies are using RWD to build stronger business cases for investment decisions and to support favorable market access and reimbursement.

3. Optimize Clinical Trials and Avoid Amendments

The average clinical trial requires around six or seven amendments at a cost of up to a half a million dollars each. These amendments often stem from mid-stream adjustments in protocol inclusion and exclusion criteria.

By using RWD to understand patient populations and potential study sites prior to launching a clinical trial, organizations can minimize costly amendments, saving millions of dollars and significant time.

Curated electronic health record (EHR) data can be used to evaluate trial-eligibility criteria, identify potential study participants, and streamline recruitment. Researchers can pinpoint patients based on disease variations, previous treatment failures, comorbid conditions (the presence of multiple illnesses), or even specific lab values and test results.

RWD has become an essential tool for helping researchers optimize study criteria, facilitate site selection and accelerate effective enrollment, critical factors for avoiding costly study amendments.

4. Streamline Development through External Control Arms

With regulatory agencies recognizing the utility of real-world evidence, researchers are increasingly incorporating RWD into clinical trial designs through external control arms (ECAs).

ECAs use historical real-world patient cohorts as comparators for investigational therapies. In situations where randomized controls are impractical or ethically challenging, including rare or life-threatening conditions such as oncology, ECAs allow for rigorous evaluations without jeopardizing a patient control group.

ECAs can supplement efficacy and safety data with broader real-world demographics, reduce recruitment challenges, lower patient burden, and accelerate clinical timelines.

5. Conduct Post-Market Surveillance

RWD is essential for risk management after product launch. By monitoring RWD sources, pharmaceutical companies can track effectiveness, identify long-term or rare adverse events, understand patterns of use, and ensure appropriate benefit-risk balance.

RWD allows for ready monitoring of safety and effectiveness across diverse populations. These insights allow sponsors to detect issues early, respond quickly to potential concerns, and maintain trust with regulators, providers, and patients.

Additionally, the careful monitoring of post-market RWD enables teams to make informed decisions on product development and commercialization strategies.

Growing Benefits of Real-World Evidence

The application of RWD throughout the R&D lifecycle is showing promising results advancing pharmaceutical innovation. By grounding decisions in real-world evidence, companies can reduce scientific and operational risk while increasing the efficiency and effectiveness of programs. This responsive, data-informed approach ultimately helps deliver high-value therapies to patients, while supporting the success of life science organizations in a challenging R&D market.