In late December 2025, Insilico Medicine announced that its collaboration with Hisun Pharmaceutical had achieved a significant milestone: the nomination of a preclinical candidate just eight months after the two companies entered a strategic collaboration. The achievement underscores the accelerating speed at which AI-driven drug discovery platforms can advance programs from target identification through lead optimization to candidate selection.
A Dramatic Acceleration
Traditional early-stage drug discovery typically requires 2.5 to 4 years from project initiation to preclinical candidate nomination. Insilico's Pharma.AI platform has consistently demonstrated the ability to compress this timeline. More than 20 of Insilico's internal programs initiated between 2021 and 2024 achieved preclinical candidate nomination in just 12 to 18 months on average. The Hisun collaboration represents an even further acceleration, reaching the same milestone in approximately 8 months.
Pharma.AI Platform at Work
The collaboration leveraged Insilico's proprietary Pharma.AI platform, which integrates three core AI-driven modules. PandaOmics was used for AI-powered target identification and validation, drawing on multiomics data, knowledge graphs, and large language models to identify therapeutic targets with high confidence. Chemistry42, the generative chemistry engine, designed and optimized novel small molecule candidates. InClinico provided predictive analytics for clinical trial design and probability of success estimation.
The platform's ability to rapidly iterate through design-make-test-analyze cycles, guided by AI predictions at each step, enables the dramatic compression of timelines. By using generative AI to propose optimized molecules and predictive models to prioritize the most promising candidates for synthesis and testing, Insilico reduces the number of experimental cycles needed to identify a viable preclinical candidate.
Hisun Pharmaceutical Context
Hisun Pharmaceutical is one of China's largest pharmaceutical companies, with extensive capabilities in drug manufacturing, clinical development, and commercialization. The partnership with Insilico reflects a broader trend of established pharmaceutical companies adopting AI-driven drug discovery methods to accelerate their pipelines and reduce development costs.
Implications for the Industry
The 8-month timeline from collaboration initiation to preclinical candidate nomination, if replicated consistently across programs, could fundamentally reshape the economics of drug discovery. Traditional programs that spend years and hundreds of millions of dollars in early discovery represent one of the largest cost drivers in pharmaceutical R&D. If AI platforms can reliably compress this phase to under a year, it could significantly increase the number of programs that can be pursued within a given R&D budget and accelerate the flow of novel therapeutics into clinical development.
Growing Validation
This milestone adds to Insilico's growing body of evidence supporting the practical utility of AI in drug discovery. Combined with the positive Phase 2a results for rentosertib, the Nature Medicine publication, the Hong Kong IPO, and the $888 million Servier deal, the Hisun achievement reinforces Insilico's position as one of the most validated AI drug discovery platforms in the industry.
