Insilico Medicine announced on June 17 the completion of first-in-human dosing in a Phase I study of ISM8969, a small-molecule inhibitor designed using artificial intelligence for the treatment of chronic neuroinflammation and central nervous system disorders, including Parkinson's disease. The company is conducting this single-center, randomized, double-blind, placebo-controlled trial in Australia as part of its co-development collaboration with Hygtia Therapeutics.
The Phase I study will evaluate the safety, tolerability, pharmacokinetics, and pharmacodynamics of orally administered ISM8969 in both healthy participants and obese adults at risk of cardiovascular disease. The trial aims to enroll 80 healthy participants and 20 obese adult participants. Cerebrospinal fluid samples will be collected to assess the drug’s penetration into the central nervous system and characterize its profile in the target compartment.
ISM8969 targets the NLRP3 inflammasome—a component involved in innate immune response—which can drive sustained neuroinflammation when excessively activated. By inhibiting NLRP3, ISM8969 seeks to modulate pathological inflammation that leads to neurodegenerative conditions such as Parkinson’s disease.
Preclinical studies showed that ISM8969 has promising activity and safety profiles both in vitro and in vivo against inflammation across multiple mouse models. Unlike other NLRP3 inhibitors that are peripherally restricted, ISM8969 is able to cross the blood-brain barrier for potential treatment of neuroinflammation-related diseases. Insilico nominated ISM8969 as its preclinical candidate for this program in December 2024.
Insilico has entered an exclusive global strategic co-development agreement with Hygtia Therapeutics for this candidate. Both companies hold equal stakes in global rights; Insilico leads regulatory submissions and clinical trials while remaining eligible for up to $66 million in payments as milestones are met.
As an AI-native biotechnology company, Insilico reports reaching preclinical candidate nomination faster than traditional methods—averaging 12 to 18 months compared with several years—by synthesizing fewer molecules per program. Since 2021, it has nominated dozens of candidates using its proprietary AI platform.
