A small-molecule TNIK inhibitor targets fibrosis in preclinical and clinical models
Feng Ren1,2, Alex Aliper2,3, Jian Chen4
1Insilico Medicine Shanghai Ltd., Shanghai, China.
Abstract:
Idiopathic pulmonary fibrosis (IPF) is an aggressive interstitial lung disease with a high mortality rate. Putative drug targets in IPF have failed to translate into effective therapies at the clinical level. We identify TRAF2- and NCK-interacting kinase (TNIK) as an anti-fibrotic target using a predictive artificial intelligence (AI) approach. Using AI-driven methodology, we generated INS018_055, a small-molecule TNIK inhibitor, which exhibits desirable drug-like properties and anti-fibrotic activity across different organs in vivo through oral, inhaled or topical administration. INS018_055 possesses anti-inflammatory effects in addition to its anti-fibrotic profile, validated in multiple in vivo studies. Its safety and tolerability as well as pharmacokinetics were validated in a randomized, double-blinded, placebo-controlled phase I clinical trial (NCT05154240) involving 78 healthy participants. A separate phase I trial in China, CTR20221542, also demonstrated comparable safety and pharmacokinetic profiles. This work was completed in roughly 18 months from target discovery to preclinical candidate nomination and demonstrates the capabilities of our generative AI-driven drug-discovery pipeline.
Insights
Artificial intelligence identified TNIK as a novel anti-fibrotic target for idiopathic pulmonary fibrosis (IPF). A new drug, INS018_055, shows promise in preclinical and early clinical studies for treating fibrotic diseases.
Area of Science:
- Drug discovery
- Artificial intelligence in medicine
- Pulmonary fibrosis research
Background:
- Idiopathic pulmonary fibrosis (IPF) is a severe lung disease with limited treatment options.
- Previous drug targets for IPF have not yielded effective clinical therapies.
- There is a critical need for novel therapeutic strategies for IPF.
Purpose of the Study:
- To identify novel anti-fibrotic targets for IPF using artificial intelligence (AI).
- To develop and evaluate a small-molecule inhibitor of TNIK (TRAF2- and NCK-interacting kinase) as a potential IPF therapy.
- To assess the anti-fibrotic and anti-inflammatory properties of the novel compound INS018_055.
Main Methods:
- Utilized a predictive AI approach to identify TRAF2- and NCK-interacting kinase (TNIK) as an anti-fibrotic target.
- Generated INS018_055, a small-molecule TNIK inhibitor, through AI-driven methodology.
- Evaluated INS018_055's efficacy, drug-like properties, and safety in preclinical in vivo models and Phase I clinical trials (NCT05154240, CTR20221542).
Main Results:
- INS018_055 demonstrated significant anti-fibrotic activity across multiple organs in vivo via various administration routes.
- The compound exhibited notable anti-inflammatory effects in addition to its anti-fibrotic profile.
- Phase I clinical trials confirmed the safety, tolerability, and favorable pharmacokinetic profile of INS018_055 in healthy participants.
Conclusions:
- TNIK inhibition represents a promising therapeutic strategy for treating fibrotic diseases, including IPF.
- INS018_055 is a potent small-molecule TNIK inhibitor with demonstrated anti-fibrotic and anti-inflammatory properties.
- The rapid discovery and development of INS018_055 highlight the efficacy of AI-driven drug discovery pipelines.
