Overcoming risks in Phase 3 trials to accelerate time to market

Knowing that novel therapies often don't meet their timelines and revenue expectations, we want to investigate the business-critical decisions that take place at every stage of the drug development process. To explore informed decision-making, I sat down with colleagues Sinan B. Sarac (MD, MSc, PhD), senior vice president within our Regulatory Consulting Group; Sangeeta Budhia, vice president and global head of Pricing and Market Access Consulting; and Amy Pace, vice president, Biostatistics. 

The following is a high-level overview of the third podcast in our five-part series, focusing on overcoming risks in Phase 3 to accelerate time to market. Since available data reveals that drugs and therapies for cancer indications show the lowest probability for success, we turned our discussion to oncology first. 

While there’s been a significant uptick in successful trial outcomes for cancer treatments in recent years, we continue to see efficacy and safety issues emerging in Phase 3 despite encouraging results in Phase 2. It’s disappointing to witness a promising product that obviously has clinical utility being rejected by regulators, despite a positive signal in a later phase, because the trial failed to demonstrate statistical relevance. Sometimes this occurs because of the study size; rare and serious adverse events are commonly not apparent in smaller studies. Yet if the company had included just 20% more patients in each arm, for example, the study might have generated significant results. 
 

The advantages of flexible trial designs 

An adaptive design might have been able to overcome those challenges. In fact, failure in Phase 3 can often be attributed to the rigidity of traditional randomized clinical trials (RCTs). Rushing into the trial design without exploring alternatives typically saves neither time nor cost. A better approach is to allow for flexibility and continuous updating as data is generated, with a multidisciplinary team making well-informed decisions at each stage of the development process. 

In Phase 3 studies, for example, at Parexel we often implement sequential designs where an interim analysis is incorporated with rules for stopping early for efficacy or futility. This early feedback can save time, sample size, and money. There are also basket designs and other types of platform trials that offer a parallel structure. Other emerging innovative designs include the use of an external control arm, a hybrid approach with some internal controls supplemented with matched external controls, and use of artificial intelligence (AI) to create digital twins. 
Certainly, the protocol for an adaptive design will take more time to write and fine tune. It’s essential to sit down with regulators and get their endorsement. But it's time well spent and can be highly effective and efficient in the end. 

The payers’ perspective 

And what about payers? In our experience, payers are increasingly looking holistically across the evidence package to understand efficacy as demonstrated within the context of the trial design, and to see how that can be translated and mapped to clinical practice. For example, one adaptive trial design was recently coming to market with a single-arm study. Although payers still require comparative efficacy – to judge the new drug compared to treatments available in clinical practice, sponsors should think about how are they going to generate that comparative efficacy with single-arm study – and how to demonstrate the benefit that new treatment brings. Another consideration, slightly different from the regulatory perspective, is substantiating long-term efficacy over the patients’ lifetime. That’s beyond the two- to three-year trial designs that sponsors are currently bringing to market. 

The value proposition for the target product profile 

This brings us to the wider discussion about the importance of demonstrating value in clinical trials relative to existing options – another frequent cause of failure. So, in addition to working on a trial design, biostatistics can deliver quantitative risk metrics. This risk can be averted by determining how the treatment fits into the current treatment algorithm, and the value proposition as you consider the target product profile (TPP). Quantitative approaches can be used to calculate the probability of meeting pre-specified decision criteria tied to the TPP at the planning stage of a trial. For example, the sample size can be optimized not only based on statistical power, but also on the probability that, say, the lower limit of the confidence interval will exceed the TPP target value. You can incorporate commercial market and value perspectives at the study design phase, which can increase the probability of success on multiple parameters. 

Further, an integrated evidence plan can help mitigate risk. Your value story can show you where evidence gaps might exist. Think about evidence generation beyond the clinical development program, such as a real-world evidence strategy and your patient engagement plan. A key objective is to ensure that payers have the same perspective about the unmet need and value that you do. 

The importance of avoiding risks by planning ahead 

De-risking your study, then, can best be accomplished by advance planning. Think carefully about the objectives of the study and the data each of the stakeholders will expect to see, and about how to build the value story. Consider using quantitative metrics to assess and communicate risks at the development transition stages. Engage with regulators early and build a clear regulatory strategy document, then update it continuously. Build flexibility into your trial designs with adaptive approaches – which can lead to faster time to market, as well as cost savings related to early termination of indications or products that are not demonstrating potential. 

Adaptive designs are a key component of the future of clinical trial development, as we see their effectiveness in reducing delays in approval and marketing of innovative products so needed for patients. And while we focused on adaptive trial design for cancer treatments in our podcast, these recommendations hold true for any drug development program. 

Please listen to our series of podcasts, De-Risking Drug Development, for more insights about how to take this approach throughout the development lifecycle.

About Parexel’s Consulting businesses 

Parexel’s Consulting businesses help you to facilitate business-critical decision-making at every stage to maximize the probability of commercial success. Our expertise encompasses medical affairs, growth strategies, strategic compliance, regulatory strategy and operations, market access, and medical communications. Our approach considers and addresses the needs of all stakeholders, including patients, physicians, regulators, payers, and other healthcare providers. We do this by designing, operating, and implementing strategies informed by expert knowledge, experience, and clinical trial expertise. We collaborate with you to help speed life-changing medicines to patients who need them. We’re always available for a conversation.

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