Insilico Medicine, Human Longevity Partner on AI Foundation Model for Aging Research

Insilico Medicine and Human Longevity announced a multi-million-dollar collaboration to develop what the companies describe as an industry-first AI foundation model focused on human longevity science and predictive healthcare. The companies said the system will combine multimodal AI models with large-scale biological and clinical datasets to study aging mechanisms and identify disease risks earlier.

The collaboration brings together Insilico’s generative AI drug discovery systems and Human Longevity’s de-identified multi-omic, imaging, and longitudinal health datasets collected over more than a decade. Human Life Foundation Models (HLFM), a company launched by Human Longevity, will work with Insilico on the development effort.

According to the companies, the project aims to build multimodal foundation models capable of detecting, diagnosing, and managing age-related conditions using clinical and biological data. Insilico said it will contribute model architecture, benchmarking, and training infrastructure through its MMAI Gym framework. Human Longevity said its datasets include integrated genomic, imaging, and health-record data from thousands of individuals.

Alex Zhavoronkov, Founder, CEO and CBO of Insilico Medicine, said the companies aim to create “a next-generation AI system capable of decoding the biology of aging.”

Wei-Wu He, Executive Chairman of Human Longevity, said the collaboration is intended to help predict complex diseases before symptoms emerge and support interventions designed to extend healthy lifespan.

AI Models Move Deeper Into Longevity Research

The announcement comes as biotechnology and pharmaceutical companies increase investments in AI systems trained on proprietary biological and clinical datasets. Recent partnerships across the sector have focused on combining large-scale healthcare data with multimodal AI models for drug discovery and diagnostics.

Merck and Mayo Clinic recently partnered on AI-enabled drug discovery systems built around clinical and molecular datasets.

Large pharmaceutical companies have also expanded investments in AI infrastructure tied to model development and computational biology workflows. NVIDIA and Eli Lilly earlier announced a $1 billion AI drug discovery lab focused on accelerating pharmaceutical research and model training.

Insilico has expanded its own pharmaceutical partnerships over the past year. Eli Lilly recently widened its collaboration with the company in a deal valued at up to $2.75 billion tied to AI-generated therapeutics.

The company has increasingly positioned longevity research as part of its long-term AI drug discovery strategy. In April, Insilico launched a longevity board chaired by Andrew Adams, Group Vice President of Molecular Discovery at Eli Lilly.

Longevity Market Draws AI Investment

The companies tied the collaboration to growing commercial interest in longevity science and preventive healthcare. UBS estimated the global longevity market at roughly $5.3 trillion and projected it could reach $8 trillion by 2030.

AI-driven drug discovery has become a major focus area within that market as companies attempt to model biological aging, identify biomarkers, and predict disease progression using large datasets.

The transition from computational prediction to validated therapies remains a major challenge across the industry, particularly in areas involving long-term disease progression and biological aging.

Insilico said the jointly developed models are expected to support early disease detection, health risk prediction, and the discovery of new therapeutics and personalized interventions related to aging and lifespan extension.