AI-Assisted Drug Re-Purposing for Human Liver Fibrosis.

Liver fibrosis has few treatment options due to the poor quality of the available animal and in vitro models. To address this, a hypothesis generating multi-agent AI system (AI co-scientist) is used to assist in re-purposing drugs for treatment of liver fibrosis and direct their experimental characterization. The anti-fibrotic efficacy and toxicity of 25 drugs are serially assessed in multi-lineage human hepatic organoids grown in microwells (i.e., microHOs). Remarkably, three previously characterized anti-fibrotic drugs and two AI co-scientist-recommended drugs that targeted epigenomic modifiers exhibited significant anti-fibrotic activity and they promoted liver regeneration. Analysis of these five anti-fibrotic drugs revealed that they all can reduce the generation of activated myofibroblasts and that each drug have unique effects on mesenchymal cells that generated their anti-fibrotic effects. Since all five of the anti-fibrotic drugs reduced TGFβ-induced chromatin structural changes, epigenomic changes play an important role in the pathogenesis of liver fibrosis. One AI co-scientist recommended drug is an FDA-approved anti-cancer treatment (Vorinostat) that reduced TGFβ-induced chromatin structural changes by 91% and promoted liver parenchymal cell regeneration in microHOs. Hence, the integrated use of AI co-scientist and this microHO platform identified a potential new generation of liver fibrosis treatments that also promote liver regeneration.