Insilico Medicine Advances AI-Discovered IPF Drug Rentosertib into Phase III Clinical Trial

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Insilico Medicine Advances AI-Discovered IPF Drug Rentosertib into Phase III Clinical Trial

Insilico Medicine has initiated the Phase III clinical trial of Rentosertib, an investigational oral therapy for idiopathic pulmonary fibrosis (IPF), marking a significant milestone for artificial intelligence (AI)-driven drug discovery as the company advances one of its lead candidates into late-stage clinical development.

Rentosertib, formerly known as ISM001-055/INS018_055, is a potentially first-in-class oral small-molecule inhibitor targeting TNIK (TRAF2 and NCK-interacting kinase) for the treatment of IPF, a progressive and irreversible lung disease with limited treatment options. The drug was discovered and designed using Insilico Medicine's generative AI-powered Pharma.AI platform, which combines the company's AI-driven biology engine, PandaOmics, for target identification and Chemistry42 for molecular design and optimisation.

The Phase III trial will be a randomised, double-blind, placebo-controlled, parallel-group study involving 320 patients with idiopathic pulmonary fibrosis. Participants will receive once-daily Rentosertib or placebo over a 52-week treatment period to evaluate the drug's efficacy and safety.

The study will be led by Professor Zuojun Xu of Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, with Academician Nanshan Zhong and Professor Chang Chen serving as co-leading principal investigators.

The late-stage trial follows encouraging Phase IIa results, which demonstrated a dose-dependent efficacy trend. The findings were published in Nature Medicine and presented at the American Thoracic Society (ATS) 2025 International Conference. Earlier, the program's AI-enabled discovery and development pathway was detailed in Nature Biotechnology.

Idiopathic pulmonary fibrosis is a chronic, progressive disease characterised by scarring of lung tissue that gradually impairs breathing and lung function. The condition primarily affects older adults, with median survival typically ranging from two to four years after diagnosis. While currently approved antifibrotic therapies can slow disease progression, they do not reverse the underlying lung damage, underscoring the need for more effective treatments.

According to the company, TNIK was identified as a promising therapeutic target using PandaOmics, which analysed multi-omics datasets, biological networks, disease pathways, scientific literature, patents and aging-related biological data. The AI platform ranked TNIK as a high-priority fibrosis target with the potential to address disease mechanisms distinct from those targeted by currently available therapies.

"Rentosertib was not discovered by starting from a conventional target and simply screening more compounds. It emerged from a biology-first, aging-informed AI workflow that linked TNIK to fibrosis and inflammatory pathways before generative chemistry was used to design a clinical-stage drug candidate," said Feng Ren, Co-Chief Executive Officer and Chief Scientific Officer of Insilico Medicine.

The initiation of the Phase III study represents one of the most advanced examples of AI-enabled drug discovery reaching late-stage clinical development, with both the therapeutic target and molecular structure generated using artificial intelligence technologies.

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Feng Ren Insilico Medicine PandaOmics Professor Zuojun Xu Rentosertib TNIK

More news about: global pharma | Published by Abha | July - 08 - 2026

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