Recursion

Recursion maps biology with industrial-scale experiments and AI, building a foundation for predicting drug mechanisms and accelerating therapeutic programs.

Overview

Recursion approaches drug discovery as a data problem at industrial scale. Its automated laboratories generate millions of cellular images and multi-omic profiles, creating one of the world’s largest proprietary biological datasets. Machine-learning models then translate that data into maps of biological relationships — how genes, compounds, and disease states interact — powering target identification and mechanism-of-prediction for drug programs. Acquisitions have added chemistry and molecular-design capabilities, extending the platform from biological insight to candidate. Partnerships with pharmaceutical companies apply the system to their programs, and the company’s wet-lab-plus-compute integration means experiments are designed to feed models rather than merely answer single questions. The result is a discovery engine where every experiment compounds the value of the last. Recursion’s dataset and models also support clinical development planning, where understanding patient biology at high resolution can sharpen trial design and patient stratification decisions. The company continues to expand its dataset through acquisitions and partnerships, deepening the biological coverage that makes its foundation models increasingly difficult for competitors to replicate.

Key Features

• Industrial-scale automated experimental data generation
• Biological foundation models mapping gene, compound, and disease relationships
• Target identification and mechanism-of-action prediction
• Integrated chemistry and molecular-design capabilities
• Pharma partnerships applying the platform to therapeutic programs
• Experiment design optimized to feed models rather than answer isolated questions

Pricing

Recursion works through partnerships with pharmaceutical companies and internal therapeutic programs, with deal structures combining research funding, milestones, and downstream economics rather than software licensing.

Who Is It For

Pharmaceutical partners seeking deep biological insight at scale, and data-driven discovery teams who believe experiment volume and model quality are the binding constraints in drug development. It fits organizations that want their discovery decisions grounded in dense, standardized biological data rather than fragmented studies of individual hypotheses.