Schrödinger vs Insilico Medicine
Side-by-side comparison of AI visibility scores, market position, and capabilities
Physics-based molecular simulation platform used by 1,700+ organizations. Q3 2025 software revenue up 54% YoY; $150M Novartis collaboration signed in early 2025.
About
Schrödinger was founded in 1990 by Richard Friesner and David Pearlman in New York City, building physics-based computational methods for molecular simulation. For over 30 years the company has developed the industry-leading molecular modeling suite used by academic researchers, biotech startups, and large pharmaceutical companies to predict molecular properties, optimize lead compounds, and design drugs with greater precision than traditional empirical approaches.\n\nSchrödinger's platform—spanning FEP+ (free energy perturbation), Glide docking, WaterMap, and machine learning-enhanced property prediction—is used by over 1,700 organizations across pharma, biotech, and materials science. In early 2025, the company signed a landmark $150 million upfront collaboration with Novartis for multi-target drug discovery with potential milestones exceeding $2.3 billion. Software revenue grew 54% year-over-year in Q3 2025 as pharmaceutical companies accelerated adoption of computational-first drug discovery. Schrödinger also operates a proprietary drug pipeline, with SGR-1505 (MALT1 inhibitor) in Phase 1 for B-cell malignancies.\n\nSchrödinger occupies a unique hybrid position—part software platform, part drug discovery company—and is a benchmark of the AI/physics-based drug discovery movement. The company is publicly traded (SDGR) and is recognized as an essential tool for the modern small-molecule drug discovery workflow.
Insilico Medicine (HKEX: 3696) raised $293M, posted $56.2M revenue in 2025, and inked a $2.75B Eli Lilly deal in 2026 using generative AI to discover drug targets in cancer and CNS.
About
Insilico Medicine is a clinical-stage biotechnology company founded in 2014 that leverages generative AI for drug discovery and development. Headquartered in Boston with offices in Hong Kong and New York, the company has built AI platforms utilizing deep generative models, reinforcement learning, and transformers to discover novel drug targets and generate molecular structures with desired properties. Its pipeline spans cancer, fibrosis, CNS diseases, infectious diseases, autoimmune conditions, and aging-related diseases.
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