AI powered clinical trials search

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AI powered clinical trials search

I built this app over the past couple of days using phenoUI, the app development toolkit for healthcare that my co-founder and I built. I was motivated to build this app for a few reasons: a) to serve as a demo of how our tools can be used to rapidly build bespoke healthcare AI apps, b) evaluate different models to determine how they perform with healthcare AI use cases, and c) explore a more user friendly experience for clinical trial searching based on my personal experience. Having built my career in healthcare and working in biopharma for a number of years, I am the person in my family & friends circle that people turn to when they need help finding clinical trials. The current process of searching for clinical trials is challenging for both patients and providers alike and while the Clinical Trials gov website has made significant strides in the past few years (including a modernized API!) it's still overwhelming and difficult to navigate. What can you do in the app?: Enter a search query (e.g. “45 year old female her2 pos”) which is then processed using Gemini API + Clinical Trials.gov API to analyze relevant clinical trials and assess how good a fit the trials are given the input search query. The top 10 search results are provided along with a measure of the trial fit (determined by the AI), a rationale for why the trial is a good fit (provided by the AI), and links to the official clinical trials government website for the given trial How: I used our phenoUI tools (e.g. phenoUI figma plugin, phenoUI flutter runtime, phenoUI gateway) to build and customize the frontend and easily connect the app to the custom backend service I built. To build the AI clinical trial backend, I evaluated Gemini Flash 1.5, Gemini Pro 1.5, Claude 3 Opus, and Claude 3.5 Sonnet. Anecdotally I observed similar performance in terms of latency and accuracy across all four services so opted to go with the option with the highest quota and lowest cost (e.g. Gemini Flash 1.5). The search query is processed using Gemini to extract key search parameters to then perform the search using the Clinical Trials.gov API. The top 10 search results are returned from the Clinical Trials.gov API and these results are then sent along with the original search query to Gemini a second time to assess which trials are a good fit for the characteristics described and the AI is asked to explain its rationale for why it recommended different trials. Youtube demo with more detail: https://www.youtube.com/watch?v=GffgxMEA4TM What’s next?: I built this app primarily as a proof-of-concept to demonstrate how healthcare AI applications can be built using our phenoUI tools. I do think this search interface could be helpful for providers and patients to improve the experience of searching for clinical trials but would love to hear any feedback, suggestions, or questions! This app is currently for demonstration purposes only but if there’s sufficient interest we would be excited to build it out further either on our own or with a healthcare company partner!