AI‐Assisted Drug Re‐Purposing for Human Liver Fibrosis

A multi‐agent AI (AI co‐scientist) is used to repurpose drugs for liver fibrosis treatment and to guide their experimental characterization. The anti‐fibrotic efficacy and toxicity of these drugs is assessed in multi‐lineage human hepatic organoids grown in microwells (microHOs). This approach identified new liver fibrosis treatments that also promote liver regeneration, offering hope for improved therapeutic options. Abstract 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. A multi-agent AI (AI co-scientist) is used to repurpose drugs for liver fibrosis treatment and to guide their experimental characterization. The anti-fibrotic efficacy and toxicity of these drugs is assessed in multi-lineage human hepatic organoids grown in microwells (microHOs). This approach identified new liver fibrosis treatments that also promote liver regeneration, offering hope for improved therapeutic options. Abstract 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. Advanced Science, Volume 12, Issue 44, November 27, 2025.