Every Cure’s End-to-End AI-Enabled Drug Repurposing Platform: Integrating Human-in-the-Loop Expertise to Accelerate Impact

<p xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" class="first" dir="auto" id="d15942904e254">Every Cure is pioneering an AI-driven platform to systematically identify, evaluate, and advance drug repurposing opportunities across all known diseases and approved drugs. Inspired by co-founder David Fajgenbaum's discovery of repurposed drugs for rare inflammatory diseases, including his own, Every Cure leverages an integrated pipeline combining biomedical knowledge graphs, predictive machine learning models, and real-world evidence to rank over 66 million drug-disease pairs and uncover the most promising repurposing opportunities, an approach we call 'computational pharmacophenomics.' <p xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" dir="auto" id="d15942904e256">Central to our innovation is a "human-in-the-loop" medical review system that iteratively refines model outputs. We leverage domain expertise to assess biological plausibility, strategic fit, and clinical viability—transforming top algorithmic predictions into real-world, patient-relevant interventions. Crucially, human feedback is captured to measure, retrain, and improve the predictive engine, fostering a continuously learning system. We validate results using LLM-based evidence synthesis, real-world evidence, and in vitro /in vivo experiments and clinical trials. Our platform has already identified high-potential candidates like lidocaine for solid tumors and leucovorin for FRA+ autism, which are now undergoing validation to bring the best options to patients. <p xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" dir="auto" id="d15942904e258">We share technical insights on predictive approaches for repurposing, our scalable medical review and data collection methods, and how we translate this to patient impact. We contend that combining computational scalability with expert-guided judgment and training data, along with accountability across the entire repurposing process, is vital to translate theoretical repurposing potential into actionable clinical benefits.All authors listed after Charlie Hempstead contributed equally under the guidance of Dr Fajgenbaum and are listedalphabetically.

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Publication Details

Published
2025-06-30
DOI
https://doi.org/10.58647/rexpo.25000098.v1
Primary Topic
Ginger and Zingiberaceae research
Type
article
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article

Every Cure’s End-to-End AI-Enabled Drug Repurposing Platform: Integrating Human-in-the-Loop Expertise to Accelerate Impact

Ginger and Zingiberaceae research
article

Every Cure’s End-to-End AI-Enabled Drug Repurposing Platform: Integrating Human-in-the-Loop Expertise to Accelerate Impact

article en

Abstract

<p xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" class="first" dir="auto" id="d15942904e254">Every Cure is pioneering an AI-driven platform to systematically identify, evaluate, and advance drug repurposing opportunities across all known diseases and approved drugs. Inspired by co-founder David Fajgenbaum's discovery of repurposed drugs for rare inflammatory diseases, including his own, Every Cure leverages an integrated pipeline combining biomedical knowledge graphs, predictive machine learning models, and real-world evidence to rank over 66 million drug-disease pairs and uncover the most promising repurposing opportunities, an approach we call 'computational pharmacophenomics.' <p xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" dir="auto" id="d15942904e256">Central to our innovation is a "human-in-the-loop" medical review system that iteratively refines model outputs. We leverage domain expertise to assess biological plausibility, strategic fit, and clinical viability—transforming top algorithmic predictions into real-world, patient-relevant interventions. Crucially, human feedback is captured to measure, retrain, and improve the predictive engine, fostering a continuously learning system. We validate results using LLM-based evidence synthesis, real-world evidence, and in vitro /in vivo experiments and clinical trials. Our platform has already identified high-potential candidates like lidocaine for solid tumors and leucovorin for FRA+ autism, which are now undergoing validation to bring the best options to patients. <p xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" dir="auto" id="d15942904e258">We share technical insights on predictive approaches for repurposing, our scalable medical review and data collection methods, and how we translate this to patient impact. We contend that combining computational scalability with expert-guided judgment and training data, along with accountability across the entire repurposing process, is vital to translate theoretical repurposing potential into actionable clinical benefits.All authors listed after Charlie Hempstead contributed equally under the guidance of Dr Fajgenbaum and are listedalphabetically.

CURE International UK (GB)
Openalex Percentile: Top 40%
Ginger and Zingiberaceae research
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