Oct 9, 2025
Kourosh Davarpanah, Co-Founder and CEO of Inato, is using an AI-enabled platform to transform participation in clinical trials. The existing clinical trial system is not seen as representative of the general population, and FDA directives have addressed this lack of diversity. The Inato platform features a marketplace approach that connects trial sponsors with a broader range of hospital sites, as well as an AI tool to assist doctors in identifying patients who are eligible for trials.
Kourosh explains, "Our focus at Inato is to expand the number of patients who are able to participate in clinical research. If you think about how things have been done for the past decades, most of the patients who have the opportunity to participate are coming from the larger academic hospitals. And what this means is that typically, 5% of the sites, meaning 5% of the hospitals running research, run about 70% of all the trials globally. So this has an impact not only on the number of patients that can actually participate in trials, but it also has an impact on the type of patients. So, typically, those are going to be white patients, richer patients. And so it has a big impact also on equity and on the diversity--and ethnic diversity especially--of patients participating."
"We have two pieces of the platform. The first piece is that we're helping connect the hospitals running the trials with trials that are being run by the sponsors. So the way this works is similar to marketplaces like Airbnb, where you have the sponsor that can share any number of upcoming trials. We enable the sites to discover all the trials on the platform and showcase, based on their profiles, how many trials they have done in the past, what is the makeup of the team and doctors, etc. We're able to allow them to get selected in trials that they otherwise wouldn't be able to get selected for. So this is the first piece of it, really connecting the sites and the trials. And increasingly with AI, we've started supporting sites in actually identifying patients at scale. And this has really been a massive tech shift, where the latest generations of LLMs are able to accurately identify patients eligible for any trial with over 95% accuracy."
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