{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/aa4a24dd6c5e4be88d683d0ea8a0971c\" frameborder=\"0\" width=\"3840\" height=\"2880\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":2880,"width":3840,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":2880,"thumbnail_width":3840,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/aa4a24dd6c5e4be88d683d0ea8a0971c-00001.gif","duration":1506.838667,"title":"Manjari Narayan -- ATHENA: Using Causal AI to 10x Clinical Trial Success","description":"Manjari is addressing the more than 90% failure rate of new therapies that enter clinical trial evaluation. What if instead, every 1 in 2 drugs that entered clinical trials succeeded? Early drug development requires effective proxy signals, such as animal models and biomarkers, to evaluate whether a drug modifies the right biological mechanism, cures disease in the relevant tissue, or displays the right safety profile. Yet, the ability of these proxy signals to emulate unbiased human response to drugs is rarely even quantified, let alone systematically improved. ATHENA aims to increase clinical trial success rates by quantitatively evaluating these proxies, combining them into improved predictive models using causal AI.\n\nRead the full proposal (https://drive.google.com/file/d/1yPb_IuBP3rMbI0zUMQEUgpY9GwF7dE51/view?usp=sharing).\n\nDr. Manjari Narayan is a quantitative scientist who has worked in neuroscience, psychiatry, pediatrics and protein design, across academia (Stanford, Rice) and industry (Dyno Therapeutics). She uses statistical learning and causal inference to understand and intervene on complex systems found in biology and medicine. She holds a PhD in Electrical Engineering from Rice University; her work received the ENAR distinguished paper award in Biostatistics. You can find her on Twitter as @Neurostats.\n\nEmail: manjari@manjarinarayan.com"}