Insilico Medicine advances AI-discovered drug for pulmonary fibrosis to Phase III trials
Insilico Medicine has initiated Phase III clinical trials for rentosertib, an AI-discovered oral medication designed to treat idiopathic pulmonary fibrosis.
1. Advancing AI-Driven Treatment
Insilico Medicine has moved its AI-identified drug, rentosertib, into Phase III clinical trials for the treatment of idiopathic pulmonary fibrosis (IPF). IPF is a severe condition characterized by lung tissue scarring that typically results in a median survival rate of two to four years post-diagnosis. Rentosertib, an oral medication, functions by inhibiting the TRAF2- and NCK-interacting kinase (TNIK) to address the underlying mechanisms of the disease. In a randomized Phase IIa trial involving 71 patients, those receiving a 60 mg daily dose showed a mean forced vital capacity gain of +98.4 mL, compared to a 20.3 mL loss in the placebo group. The U.S. Food and Drug Administration granted the drug Orphan Drug Designation in February 2023.
2. Computational Discovery Pipeline
The development of rentosertib utilized Insilico Medicine’s proprietary Pharma.AI platform. The process began with the PandaOmics engine, which analyzed biological datasets, clinical outcomes, and academic literature to identify TNIK as a primary target for IPF. This approach bypassed traditional receptor tyrosine kinase pathways, instead focusing on signaling channels related to fibrosis and inflammation. Following target identification, the Chemistry42 engine employed Generative Tensorial Reinforcement Learning to design molecules that fit the target protein pocket. This methodology allowed the team to nominate a preclinical candidate within 18 months, significantly faster than conventional high-throughput screening processes.
3. Clinical Validation and Future Outlook
The progression of rentosertib is supported by a series of peer-reviewed publications, including findings in Nature Biotechnology, the Journal of Medicinal Chemistry, and Nature Medicine. These studies document the full lifecycle of the drug, from algorithmic target prioritization and generative molecular design to Phase I pharmacokinetics and Phase IIa efficacy data. By integrating proteomic aging-clock frameworks into its clinical trials, Insilico Medicine aims to provide empirical evidence of the drug's biological impact.