<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>31(8)</volume><submitter>Xu Z</submitter><pubmed_abstract>Despite substantial progress in artificial intelligence (AI) for generative chemistry, few novel AI-discovered or AI-designed drugs have reached human clinical trials. Here we present the results of the first phase 2a multicenter, double-blind, randomized, placebo-controlled trial testing the safety and efficacy of rentosertib (formerly ISM001-055), a first-in-class AI-generated small-molecule inhibitor of TNIK, a first-in-class target in idiopathic pulmonary fibrosis (IPF) discovered using generative AI. IPF is an age-related progressive lung condition with no current therapies available that reverse the degenerative course of disease. Patients were randomized to 12 weeks of treatment with 30 mg rentosertib once daily (QD, n = 18), 30 mg rentosertib twice daily (BID, n = 18), 60 mg rentos</pubmed_abstract><journal>Nature medicine</journal><pagination>2602-2610</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12353801</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>A generative AI-discovered TNIK inhibitor for idiopathic pulmonary fibrosis: a randomized phase 2a trial.</pubmed_title><pmcid>PMC12353801</pmcid><pubmed_authors>Liu H</pubmed_authors><pubmed_authors>Fang H</pubmed_authors><pubmed_authors>Xiang P</pubmed_authors><pubmed_authors>Rao S</pubmed_authors><pubmed_authors>Cao J</pubmed_authors><pubmed_authors>Lv Y</pubmed_authors><pubmed_authors>Liu S</pubmed_authors><pubmed_authors>Meng Y</pubmed_authors><pubmed_authors>Ren F</pubmed_authors><pubmed_authors>Wang P</pubmed_authors><pubmed_authors>Zhao L</pubmed_authors><pubmed_authors>Ding Y</pubmed_authors><pubmed_authors>Cui H</pubmed_authors><pubmed_authors>Chen S</pubmed_authors><pubmed_authors>Zhavoronkov A</pubmed_authors><pubmed_authors>Zhao H</pubmed_authors><pubmed_authors>Li H</pubmed_authors><pubmed_authors>Xiao Z</pubmed_authors><pubmed_authors>Satler C</pubmed_authors><pubmed_authors>Tan C</pubmed_authors><pubmed_authors>Luo F</pubmed_authors><pubmed_authors>Korzinkin M</pubmed_authors><pubmed_authors>Gennert D</pubmed_authors><pubmed_authors>Pan P</pubmed_authors><pubmed_authors>Ma D</pubmed_authors><pubmed_authors>Dai J</pubmed_authors><pubmed_authors>Xu Z</pubmed_authors></additional><is_claimable>false</is_claimable><name>A generative AI-discovered TNIK inhibitor for idiopathic pulmonary fibrosis: a randomized phase 2a trial.</name><description>Despite substantial progress in artificial intelligence (AI) for generative chemistry, few novel AI-discovered or AI-designed drugs have reached human clinical trials. Here we present the results of the first phase 2a multicenter, double-blind, randomized, placebo-controlled trial testing the safety and efficacy of rentosertib (formerly ISM001-055), a first-in-class AI-generated small-molecule inhibitor of TNIK, a first-in-class target in idiopathic pulmonary fibrosis (IPF) discovered using generative AI. IPF is an age-related progressive lung condition with no current therapies available that reverse the degenerative course of disease. Patients were randomized to 12 weeks of treatment with 30 mg rentosertib once daily (QD, n = 18), 30 mg rentosertib twice daily (BID, n = 18), 60 mg rentos</description><dates><release>2025-01-01T00:00:00Z</release><publication>2025 Aug</publication><modification>2026-07-15T06:30:51.267Z</modification><creation>2026-06-30T03:23:41.839Z</creation></dates><accession>S-EPMC12353801</accession><cross_references><pubmed>40461817</pubmed><doi>10.1038/s41591-025-03743-2</doi></cross_references></HashMap>