Why Decentralized Trials Face Slow Adoption Despite Strong Data

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: Despite strong data on retention and diversity, why do you think most sponsors and CROs are still slow to adopt decentralized clinical trial models at scale?

Kumar: Great question. I think we've seen two large barriers that have prevented wide scale adoption. And I use that specific term wide scale adoption because if you actually look at the data, most sponsors have actually adopted these decentralized trials. The adoption rate at the sponsor level is now 80-90%, virtually 100%, but the actual trials themselves are not fully decentralized, or have not adopted some sort of decentralized software. And there are a couple of reasons for that. The biggest is that in order to truly adopt this software across every single functional areal you have to put in place not just the software itself—which can cost a couple of million dollars per trial—but the infrastructure to support that, and that involves a significant additional investment that can often be tens of millions of dollars. As you're well aware, pharma as a whole, biotech as a whole, has been going through a bit of a down cycle from an investment perspective, where many of these companies have been downsizing, laying off staff, and trying to find ways to reduce expenditure. And despite—as you pointed out—the savings that these companies can see, the improvements in diversity, the improvements in retention, the upfront costs required to put in place decentralization, whether that be ePRO, eCOA, eConsent, some of these other solutions, has limited the adoption that we're seeing upfront. I do think that this will be resolved over time, as more and more of these sponsors see the value of these solutions, and do put in place those investments, but it takes time.

Second, and this is also a very pressing challenge here, is that we have to make sure that we're solving the core issue, the core challenge that these pharmaceutical sponsors have, which is, ‘How can I reduce the overall cost of my clinical trial, and how can I get more drugs to market faster?’ As you pointed out, retention is a critical component, diversity is a critical component, but do they boil down to that bottom line of saying, ‘Hey, does this reduce the cost of my overall clinical trial spend, and does this increase the success of my clinical trial?’ I think we've have some data to support that, but it's still relatively early, and as the data improves across those dimensions, we'll see more adoption of this technology as well.