Idiopathic pulmonary fibrosis study completes enrolment


Insilico Medicine has completed patient enrolment in a Phase IIa study in China, which is investigating the safety, tolerability, and preliminary efficacy of AI-designed TNIK inhibitor INS018_055 for idiopathic pulmonary fibrosis (IPF).

The randomised, double-blind, placebo-controlled study is being conducted across 29 clinical centres in China and has completed enrolment of the planned target of 71 patients in four participant groups, including three experimental and one placebo.

The primary objective is to evaluate the safety and tolerability of INS018_055 orally administered for up to 12 weeks in adult subjects with IPF compared to placebo.

In addition, Insilico is preparing a Phase IIb proof-of-concept study to be initiated in 2025 to explore the efficacy and further safety of INS018_055.

Idiopathic pulmonary fibrosis (IPF) is a chronic scarring lung disease characterised by progressive and irreversible decline in lung function, affecting approximately five million people worldwide.

Due to the lack of differential symptoms, patients diagnosed with IPF are often in advanced stages, with a median survival of three years.

Current treatments, primarily antifibrotic agents, may slow disease progression but often fail to halt it, and they come with a range of side effects that can severely impact quality of life.

“Starting with an unmet clinical need, Insilico fast-tracked the programme’s early drug discovery with the support of our proprietary AI platform,” said Feng Ren, Co-CEO and Chief Scientific Officer of Insilico Medicine. “I am excited about the clinical progress in this programme, which is not only another milestone achieved by Insilico’s wholly owned pipeline, but also marks a step forward in the validation of AI-driven drug discovery and development.”

In March 2024, a study published in Nature Biotechnology explained the discovery and development of INS018_055 in detail from AI algorithms to Phase II clinical trials.

Diana Spencer, Senior Digital Content Editor, DDW

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