Insilico Medicine has received Investigational New Drug (IND) clearance from the US Food and Drug Administration for ISM8969, an orally available NLRP3 inhibitor developed using artificial intelligence, enabling the start of clinical studies in the United States.
The IND approval allows Insilico to initiate a Phase I clinical trial to assess the safety, tolerability and pharmacokinetic profile of ISM8969 in healthy volunteers, with the goal of determining appropriate dose levels for further clinical development. The drug candidate is being developed for the treatment of Parkinson’s disease and other neurodegenerative conditions associated with chronic inflammation.
ISM8969 was discovered and optimised using Insilico’s AI-driven drug discovery platform, Pharma.AI, including its generative chemistry engine, Chemistry42. Preclinical studies have shown that the molecule has favourable drug-like properties, the ability to cross the blood–brain barrier, and strong potential to modulate neuroinflammation by inhibiting the NLRP3 inflammasome, a key driver of inflammatory processes implicated in neurodegenerative disease progression.
Excessive activation of NLRP3 is known to cause sustained inflammation through the overproduction of pro-inflammatory cytokines, leading to neuronal damage. By targeting this pathway, ISM8969 aims to support neuronal survival and function. The compound was nominated as a potential best-in-class preclinical candidate in December 2024.
To advance the global development of ISM8969, Insilico Medicine has entered into a co-development collaboration with Hygtia Therapeutics. Under the agreement, both companies will hold equal global rights and interests in the programme. Insilico is eligible to receive up to $66 million in upfront and milestone-based payments as part of the deal.
Insilico Medicine, a clinical-stage biotechnology company listed in Hong Kong, has built a growing portfolio of AI-enabled drug discovery programmes and has established multiple partnerships with global pharmaceutical companies.
The company reports that its AI-powered approach has significantly reduced early-stage drug discovery timelines, enabling the rapid nomination of multiple preclinical candidates over recent years.
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