{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"START","title":"START: Melissa Bime, CEO & Founder, Infiuss Health: \"AI-Powered clinical rehearsal. Run the trial before you run the trial.\"","html":"","width":"100%","height":180,"duration":756,"description":"\n‍A clinical trial at Stanford enrolled a patient living in Africa.\nHe was never physically there.\nHe had been diagnosed with a rare genetic disorder, and Stanford was running a trial for it. The research team gathered his genetic information and medical records. They monitored him remotely and enrolled him.\nThe patient was Melissa Bime’s father.\nShe was working at Stanford as a clinical trial nurse at the time. She had trained as a nurse in Cameroon and moved to the US, where she worked through the COVID vaccine trials.\nShe says that was the spark. Why not build digital versions of patients and get them into clinical trials.\nThat’s Infiuss Health.\nIt builds medical digital twins from real-world and historical data. Trial teams rehearse a protocol across thousands of virtual patients before a single one enrolls.\nThe twins flag who is likely to drop out mid-study. Who has a comorbidity that affects how the drug performs. Whether two hours of travel to a research site is feasible over two years.\nInfiuss reports up to a 30% reduction in sample size and design cycles 10x faster.\nDuring the recent Ebola outbreak, Infiuss helped companies running vaccine trials recruit patients with a specific genetic trait.\nMelissa’s long-term view is approval with a hundred patients instead of thousands.\nHer focus is small and mid-sized life science companies. Most have one or two drug candidates the entire company hinges on. Infiuss is built to give them more tries.\n\"AI-Powered clinical rehearsal. Run the trial before you run the trial.\"\n🎙️Melissa Bime, Founder, Infiuss Health on Fondo START  \n‍\n01:29 From nursing school in Cameroon to healthcare entrepreneurship\n02:29 The diagnosis that changed everything\n04:22 Building computational versions of real patients\n05:27 Why clinical R&D costs billions and fails nine times out of ten\n06:23 What digital patient twins can predict today\n07:35 Cutting roughly six to eight months from the process\n08:05 Approval with a hundred patients instead...","thumbnail_url":"https://img.transistorcdn.com/q-E1hh7K6IS4AfZiNy2p4MYVGcUOO8lQP92h8QbOEOA/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS80NzVj/MDEzNjkxNjU1N2Uy/NDFhMDQ3M2ZhNWI3/NWY0MS5wbmc.webp","thumbnail_width":300,"thumbnail_height":300}