In this video interview, Sunny Kumar, MD, partner at Informed Ventures, discusses how FDA guidance and investor expectations are shaping resilient trial designs that use adaptive methods, virtual controls, and decentralization to lower costs and accelerate patient access.
In a recent video interview with Applied Clinical Trials, Sunny Kumar, MD, partner, Informed Ventures, discussed the slow adoption of DCT models despite their benefits in retention and diversity. Key barriers include high upfront costs (millions per trial) and the current down cycle in pharma investment. To address the digital divide, Kumar emphasized providing devices to patients rather than relying on their own, especially in under-resourced areas. Operational and cultural challenges, such as regulatory compliance and risk-aversion, contribute to a six-year lag in adopting clinical trial innovations. Generative AI is seen as a promising tool to reduce costs. Kumar also highlighted the need for tech platforms that fit seamlessly into the pharma ecosystem.
ACT: How are FDA guidance updates and investor expectations changing what “resilient” trial design looks like—and what does that mean for clinical teams executing trials on the ground?
Kumar: Yeah, it's great question. As I think everyone is aware, there's a lot of change happening in the senior levels of the regulatory environment, with the FDA pushing this kind of resilient or adaptive style design, all with the goal of trying to get more drugs to patients faster and cheaper than ever before. While you might disagree with the methods, that specific goal is generally aligned with what most people, pharma, patients, doctors, all want. Now, how do we actually do that? I think that's very much up in the air. Decentralized trials are absolutely one component of that, because it's better retention. It's easier for patients to reduce the cost of the trials. Having an adaptive trial design so that we can see, okay, if this drug is very effective, then we can either accelerate the trial and end it sooner, or if the drug is not doing particularly well, then we can end the trial and not necessarily have to spend the money taking the trial all the way to completion. Could we potentially do in silico trials or have a virtual control arm so that we can recruit fewer patients into that part of the trial. I think these are all signals that we're looking at potentially bringing into clinical trials—all again—with the goal of getting more drugs to patients faster and cheaper than ever before. That's something that we're all generally in this industry, very supportive of. However, I think it's very early when it comes to actually implementing any of the things that I've mentioned from a regulatory perspective, and we still have to see how that plays out.
