A framework designed for discovery
Overview
HIT-AI integrates AI-driven drug-disease prediction, high-throughput experimental screening, and real-world clinical validation to systematically identify and advance repurposed FDA-approved drugs for autoimmune diseases. The work combines computational knowledge graph analysis with cellular, animal, and clinical validation pipelines across multiple autoimmune conditions.
Experimental / Computational Methods
Knowledge graph construction and machine learning modeling to generate predictive scores for 640,000 drug-disease combinations across 4,000 FDA-approved drugs and 160+ autoimmune diseases; high-throughput cellular screening targeting key autoimmune pathways (TLR, TREX1-cGAS-STING, JAK-STAT, NF-κB, TCR, BCR, BAFF); multi-omic data integration from Colton network members; animal model validation of promising candidates; and retrospective clinical studies using EHR data from 10M+ Americans.
Data Sources / Models Used
Biomedical knowledge graphs integrating drug, disease, and pathway data; multi-omic datasets from Colton network investigators; high-throughput cellular screening datasets targeting key autoimmune signaling pathways; EHR data from 10M+ Americans for retrospective clinical validation; and existing clinical trial infrastructure at UPenn and other Colton Centers.
Analytical / Translational Focus
Identification and clinical validation of repurposed drug candidates for 160+ autoimmune diseases, with a goal of delivering at least three validated treatments to patients within three years through laboratory validation, observational research, and clinical trials. Commercialization strategies include licensing, spinout companies, internal development at Penn, and collaboration with Every Cure, with IP anticipated from novel dosing, formulation, and combination therapy discoveries.
Powering the science
Jonathan Miner, MD, PhD, Colton Consortium Member
Associate Professor, Department of Medicine (Rheumatology), Perelman School of Medicine, University of Pennsylvania
Sara Cherry, PhD, Colton Consortium Member
John W. Eckman Professor of Medical Science, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania
David Fajgenbaum, MD, MBA, MSc, FCPP, Colton Consortium Member
Associate Professor, Department of Medicine (Translational Medicine and Human Genetics), Perelman School of Medicine, University of Pennsylvania