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

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 (C<sub>max</sub>, C<sub>trough</sub>, t<sub>max</sub>, AUC<sub>0-t/τ/∞</sub> and t<sub>1/2</sub>), changes in lung function as measured by forced vital capacity, diffusion capacity of the lung for carbon monoxide, forced expiry in 1 s and change in the Leicester Cough Questionnaire score, change in 6-min walk distance and the number and hospitalization duration of acute exacerbations of IPF. We observed increased forced vital capacity at the highest dosage with a mean change of +98.4 ml (95% confidence interval 10.9 to 185.9) for patients in the 60 mg rentosertib QD group, compared with -20.3 ml (95% confidence interval -116.1 to 75.6) for the placebo group. These results suggest that targeting TNIK with rentosertib is safe and well tolerated and warrants further investigation in larger-scale clinical trials of longer duration. ClinicalTrials.gov registration number: NCT05938920 .

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Journal
Nature Medicine
Published
2025-06-03
DOI
https://doi.org/10.1038/s41591-025-03743-2
Citations
64
Primary Topic
Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
Type
article
Field-Weighted Citation Impact
97.17
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article

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

Li Zhao, Pinhua Pan, Fengming Luo, Dedong Ma et al.
64 citations
Nature Medicine
Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
97.17
article

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

Li Zhao, Pinhua Pan, Fengming Luo, Dedong Ma, David Gennert, Ying Meng, Alex Zhavoronkov, Sang Liu, Haohui Fang, Zuke Xiao, Mikhail Korzinkin, Ping Wang, Shan Chen, Hong Liu, Huiping Li, Jie Cao, Jinghong Dai, Yuan Lv, Yipeng Ding, Feng Ren, Sujata Rao, Chunting Tan, Carol Satler, Hui Cui, Pingchao Xiang, Heng Zhao, Zuojun Xu
article en
64 citations

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 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 (C<sub>max</sub>, C<sub>trough</sub>, t<sub>max</sub>, AUC<sub>0-t/τ/∞</sub> and t<sub>1/2</sub>), changes in lung function as measured by forced vital capacity, diffusion capacity of the lung for carbon monoxide, forced expiry in 1 s and change in the Leicester Cough Questionnaire score, change in 6-min walk distance and the number and hospitalization duration of acute exacerbations of IPF. We observed increased forced vital capacity at the highest dosage with a mean change of +98.4 ml (95% confidence interval 10.9 to 185.9) for patients in the 60 mg rentosertib QD group, compared with -20.3 ml (95% confidence interval -116.1 to 75.6) for the placebo group. These results suggest that targeting TNIK with rentosertib is safe and well tolerated and warrants further investigation in larger-scale clinical trials of longer duration. ClinicalTrials.gov registration number: NCT05938920 .

Nature MedicineVol. 31(8)
Tongji University (CN), Central South University (CN), Capital Medical University (CN), Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Sichuan University (CN), Peking Union Medical College Hospital (CN), Tianjin Medical University General Hospital (CN), West China Hospital of Sichuan University (CN), Nanfang Hospital (CN), Jiangxi Provincial People's Hospital (CN), Nanjing Drum Tower Hospital (CN), Insilicos (United States) (US), Shanghai Pulmonary Hospital (CN), Hainan General Hospital (CN), Anhui Provincial Hospital (CN), Peking University Shougang Hospital (CN), Beijing Friendship Hospital (CN), INSEAD (AE), First Affiliated Hospital of Zhengzhou University (CN), Xiangya Hospital Central South University (CN), Insilico Biotechnology (Germany) (DE), Qilu Hospital of Shandong University (CN), Southern Medical University (CN), China Medical University (CN)
Openalex Percentile: Top 0%
Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
97.17
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