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: From your experience with health tech startups, what common blind spots do you see when it comes to building tech that’s truly usable and scalable for clinical trial sites and operations teams?
Kumar: Great question. This is not a universal challenge, but a very common challenge is that there’s a difference between those who build technology and those who use that technology in pharma. I think the most common issue that I see is that the entrepreneurs are very, very good at understanding technology and figuring out how to build a product, but it sometimes takes a couple of iterations to understand how does that technology really fit within the pharma ecosystem? How does it really solve the problem that a pharma sponsor, that a clinical trial lead actually has and that’s the problem that needs to be solved in order for you to get adoption. The most common example of this that I see is that you’ll have a great technology that’s a specific point solution, whereas a pharma sponsor or CRO needs a platform. They can’t buy 10, 12, 15, 20, different point solutions and try and integrate them all in the back end, even though that’s generally how technology is built, especially with a small amount of initial venture funding, you need to build a platform, or at least have an idea of how that technology scales into a platform in order to really get adoption.