INS018_055 is the first-in-class drug candidate for idiopathic pulmonary fibrosis disease discovered and designed with the empowerment of generative AI. An article published by Insilico Medicine researchers comprehensively describes the development of the TNIK inhibitor INS018_055 from AI algorithm to clinical trials, and discloses for the first time the data and performance of the drug candidate in preclinical experiments and clinical trials.
The research highlights the significant benefits of an AI-driven approach to drug discovery and underscores the enormous potential of generative AI technologies to drive change in the industry.
Idiopathic pulmonary fibrosis (IPF) is a scarring disease characterized by a progressive and irreversible decline in lung function that affects millions of people worldwide. Despite the enormous burden of fibrotic disease on the global health system, current treatment options are very limited due to its relatively insidious onset and progression.
TNIK plays a key role in fibrosis-driven signaling pathways, including WNT, TGF-β, Hippo, JNK and NF-κB signaling pathways. Despite its association with fibrotic pathways, TNIK has not been studied as a therapeutic target in the treatment of IPF.
As the first step in the development of a new drug, the researchers used the AI-driven discovery engine PandaOmics to identify potential therapeutic targets in fibrotic diseases. The PandaOmics platform nominates potential targets through a process of deep feature synthesis, causality inference, and novel pathway reconstruction. Through this approach, the research team successfully identified TNIK as the most promising target for anti-fibrotic therapy.
The research team utilized Chemistry42, an AI-driven drug design platform, to generate innovative molecular structures with desired properties according to a structure-based drug design strategy, aiming to obtain safe, specific, and efficient TNIK inhibitors. After several iterations of screening, the candidate molecule INS018_055 was finally obtained.
INS018_055 demonstrated significant efficacy against IPF in both in vivo and in vitro assays, and showed promising results in pharmacokinetic (PK) and safety studies in several cell lines and multiple species. In addition, INS018_055 had potential therapeutic benefit against renal fibrosis and dermal fibrosis.
The research team conducted two clinical Phase I trials to evaluate INS018_055's safety, tolerability, and PK properties. The trials were conducted in New Zealand and China and involved 78 healthy volunteers. The results showed that INS018_055 was safe and well tolerated in healthy volunteers, with good oral bioavailability and PK properties. The favorable Phase I trial results not only completed the AI Pharma clinical proof of concept, but also lay the foundation for subsequent clinical trials. The research team plans to further validate these promising results in Phase II and Phase III clinical trials.
This research demonstrates the potential of AI in drug discovery, especially in identifying new therapeutic targets and designing specific inhibitors. With AI technology, it takes only about 18 months from target identification to nomination as a preclinical candidate compound, significantly speeding up the drug development process. This research not only provides new therapeutic strategies for fibrotic diseases, but also provides a strong case for the use of AI in drug discovery.
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Original Article:
Ren F.; et al. (2024). A small-molecule TNIK inhibitor targets fibrosis in preclinical and clinical models. Nature Biotechnology. 2024: 1-13.
Services Related in the Article:
Target Identification
AI-powered Drug Discovery and Design
AI-assisted Drug High Throughput Screening
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