A generative AI-discovered TNIK inhibitor for idiopathic pulmonary fibrosis: a randomized phase 2a trial

作者：Zuojun Xu, Feng Ren, Ping Wang, Jie Cao, Chunting Tan, Dedong Ma, Li Zhao, Jinghong Dai, Yipeng Ding, Haohui Fang, Huiping Li, Hong Liu, Fengming Luo, Ying Meng, Pinhua Pan, Pingchao Xiang, Zuke Xiao, Sujata Rao, Carol Satler, Sang Liu, Yuan Lv, Heng Zhao, Shan Chen, Hui Cui, Mikhail Korzinkin, David Gennert, Alex Zhavoronkov · 发表于：Nature Medicine · 年份：2025 · DOI：10.1038/s41591-025-03743-2 · 被引用次数：138 · 研究领域：Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis、Sarcoidosis and Beryllium Toxicity Research

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 rentosertib QD (n = 18) or placebo (n = 17). The primary endpoint was the percentage of patients who have at least one treatment-emergent adverse event, which was similar across all treatment arms (72.2% in patients receiving 30 mg rentosertib QD (n = 13/18), 83.3% for 30 mg rentosertib BID (n = 15/18), 83.3% for 60 mg rentosertib QD (n = 15/18) and 70.6% for placebo (n = 12/17)). Treatment-related serious adverse event rates were low and comparable across treatment groups, with the most common events leading to treatment discontinuation related to liver toxicity or diarrhea. Secondary endpoints included pharmacokinetic dynamics (Cmax, Ctrough, tmax, AUC0–t/τ/∞ and t1/2), changes in lung function ...