About Valence Discovery
Valence Labs is Recursion's AI research engine dedicated to decoding biology through advanced computational methods. The company focuses on three core pillars: Predict, Explain, and Discover. They build on over a decade of experience in perturbative biology, developing models that predict functional responses of cells to perturbations at unprecedented scale using multimodal foundation models trained on phenomics and transcriptomics datasets. Their work combines interventional data with novel methods for predicting and simulating molecular interactions to generate causal explanations for how molecular interventions shape cellular function. Using lab-in-the-loop engines of biological discovery, Valence Labs bridges functional readouts with mechanistic understanding to generate, test, and refine novel therapeutic hypotheses. The company's ambitious vision centers on creating 'virtual cells'—mechanistic models of cellular function that can accurately predict patient responses to interventions before clinical trials begin. Powered by Recursion's OS automated biology and chemistry labs generating over 60 petabytes of data, BioHive supercomputer for massive-scale computing, and a world-class interdisciplinary team, Valence Labs aims to transform drug discovery by enabling safer, more economical testing and optimization of therapeutic hypotheses through computational simulation rather than traditional experimental approaches.
Mission & Story
Mission
Decoding biology to radically improve lives
Who It Serves
Milestones & Awards
Recent Milestones
Published TxPert model for predicting cellular responses to genetic perturbations (May 2025), launched OpenQDC open-source quantum datasets hub (November 2024), published Virtual Cells perspective paper (2025)
Awards & Recognition
BioHive described as pharmaceutical industry's leading supercomputer
Key Partnerships
Company Details
Work here?
Claim this listing to update company information and connect with our audience.
Claim This ListingOfficial Sources
Similar Companies in this Market
View all 64 →A2A Pharmaceuticals
AI-driven pharmaceutical company focused on discovering and developing novel drug candidates using computational biology and machine learning.
AbCellera
AbCellera uses AI and machine learning to discover and develop antibody-based therapeutics and vaccines.
Absci
Absci uses AI-powered computational biology and machine learning to accelerate drug discovery and optimize therapeutic proteins and antibodies.
Adaptyv Bio
11-50 employees
Adaptyv Bio operates the world's fastest protein validation lab, providing automated experimental testing services for AI-designed proteins. The company enables protein engineers to validate binding, expression, and thermostability of novel protein designs through a fully automated platform with 3-week turnaround times.
Aitia
Aitia is a drug discovery and development company leveraging AI and computational biology to identify novel therapeutic targets and accelerate drug development.
Anagenex
Anagenex is a biotechnology company focused on drug discovery and development. The company appears to operate in the pharmaceutical research space, though specific details about their technology platform, therapeutic areas, and target markets are not available from the provided content.
Aqemia
Aqemia is a drug discovery company advancing next-generation medicines using generative AI and deep physics. The company combines AI-augmented discovery with computational chemistry to develop novel therapeutics at scale.
Arctoris
51-200 employees
Arctoris is a Partnership Research Organisation (PRO) providing automated wet lab biology R&D and data generation services for biotech, techbio, and pharma companies through its Ulysses® robotic platform.
Data Accuracy Notice: Company information on HealthAI Central is compiled from public sources and updated regularly. While we strive for accuracy, details such as funding figures, employee counts, and product offerings may change. We recommend verifying critical information directly with the company before making business decisions.