The International Society for Stem Cell Research (ISSCR) today announced the release of a special anniversary episode of The Stem Cell Report podcast, “Stem Cell-ebration: 5 Years of Breakthrough Science and Insightful Conversations,” marking five years of exploring the science, people, and stories shaping the field. The podcast features work that has published in the ISSCR’s journal, Stem Cell Reports.

Since its launch, The Stem Cell Report podcast has captured a period of remarkable progress in stem cell research – one that has reshaped understanding of human development, disease, and the potential of regenerative medicine. The podcast reaches a global audience, with 48 episodes downloaded across 139 countries, reflecting strong engagement across the scientific community.

Insilico Medicine has expanded its Science MMAI Gym, a large-scale training and benchmarking platform for artificial intelligence, with the launch of three public leaderboard portals designed to evaluate AI performance across scientific research and drug discovery. Positioned as both a training environment and benchmarking system, MMAI Gym enables the development of domain-specific AI models while rigorously assessing their capabilities on real-world tasks.

The newly launched benchmark categories include ScienceAI Bench, which evaluates general scientific reasoning across disciplines such as biology, chemistry, and materials science; the Drug Discovery Benchmark (DDB), focused on end-to-end pharmaceutical R&D tasks; and Insilico Bench, a proprietary suite targeting complex and emerging scientific challenges. Together, these benchmarks draw from both curated industry datasets and proprietary, experimentally grounded data, enabling multi-dimensional evaluation across more than 200 tasks.

The platform reflects a broader shift toward standardized, scalable evaluation of scientific AI systems. Previous results from Insilico demonstrate that models trained within MMAI Gym can achieve up to tenfold performance improvements on key drug discovery benchmarks. In collaboration with Liquid AI, Insilico also developed a compact foundation model that achieved state-of-the-art performance across multiple drug discovery tasks, with findings presented at ICLR 2026.

By integrating training, benchmarking, and public evaluation, MMAI Gym aims to accelerate the adoption of reliable, high-performance AI systems across pharmaceutical research and beyond.