Insilico Medicine has entered into a multi-million-dollar strategic partnership with Human Life Foundation Models (HLFM), a newly established entity under Human Longevity, to jointly develop what the companies describe as the industry’s first large-scale AI foundation model dedicated to human longevity science.
The collaboration comes at a time when demographic shifts are reshaping global labor markets and consumption patterns, pushing longevity beyond the boundaries of scientific inquiry into the realm of macroeconomic strategy. According to recent analysis from UBS, the global longevity economy is already valued at approximately $5.3 trillion and is projected to expand to $8 trillion by 2030. Within this rapidly growing sector, AI-enabled longevity research is emerging as a core driver, leveraging deep modeling of aging biology, predictive disease analytics, and accelerated development of preventive interventions to extend healthy human lifespan.
Under the agreement, Insilico Medicine and HLFM will co-develop an advanced multimodal AI foundation model designed to decode complex biological mechanisms of aging and enable predictive diagnostics. Insilico will contribute its expertise in multimodal model development and deep learning systems, utilizing its MMAI Gym framework to deliver model architecture design, benchmarking protocols, training guidelines, and core computational algorithms that will underpin the joint platform.
HLFM will integrate these capabilities with Human Longevity’s proprietary, de-identified multi-omics and clinical datasets. Built over more than a decade, this dataset spans genomic, imaging, and longitudinal health records from thousands of individuals, forming one of the most comprehensive integrated biological data resources globally. By leveraging this dataset, HLFM aims to train the foundation model to achieve clinical-grade precision in detecting, diagnosing, and managing health conditions.
The companies expect the jointly developed model to move toward commercialization, supporting applications such as early detection of age-related diseases, predictive health risk modeling, AI-driven longevity drug discovery, and personalized intervention strategies. These advancements are positioned to accelerate the transition of global healthcare systems from reactive treatment models to proactive, prevention-focused longevity science.
Alex Zhavoronkov, Founder and CEO of Insilico Medicine, said the partnership combines Insilico’s strengths in large-scale AI model development with HLFM’s unique longitudinal datasets to build what he described as a “superintelligent” system capable of decoding the most complex mechanisms of human aging. He emphasized that the initiative is not only about predicting lifespan but also about enabling high-precision identification of age-related risks and accelerating the discovery of longevity therapeutics.
Wei-Wu He, Executive Chairman of Human Longevity, noted that the company was founded on the vision of transforming medicine through large-scale biological data and artificial intelligence. He said the formation of HLFM and its collaboration with Insilico mark a critical step toward building foundational models for human health and longevity, with the potential to enable earlier prediction of complex diseases and guide targeted interventions to extend healthspan.
Longevity science has been central to Insilico Medicine’s mission since its inception. As early as 2015, Zhavoronkov raised the question “Can NVIDIA cure aging?” at the NVIDIA GTC conference, drawing significant attention from the technology community. More recently, the company established what it calls the industry’s first Longevity Committee, chaired by Andrew Adams, Vice President of Molecular Discovery at Eli Lilly, to accelerate AI-driven anti-aging drug development. To date, Insilico researchers have published more than 50 scientific papers related to aging and longevity, covering biomarkers, therapeutic targets, and intervention strategies aimed at addressing both aging and disease.