BioHive
Pharmaceutical industry's leading supercomputer for AI drug discovery
Company profile
Company profile
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.
Company description Valence Discovery official website
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01 · Operating footprint
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Company 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)
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02 · Flagship portfolio
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Pharmaceutical industry's leading supercomputer for AI drug discovery
Open-source hub of ML-ready quantum mechanics datasets
State-of-the-art model predicting transcriptional responses to unseen genetic perturbations
Mechanistic models of cellular function that guide the discovery of novel therapeutics
03 · Research intelligence
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Research
Journal of medicinal chemistry · Aug 10, 2023
Photoredox Activation of Anhydrides for the Solvent-Controlled Switchable Synthesis of gem-Difluoro Compounds.Angewandte Chemie (International ed. in English) · Oct 17, 2022
Clinical validation
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Regulatory
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04 · Company-reported outcomes
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Over 60 petabytes of data across phenomics, transcriptomics, and other modalities
40+ quantum mechanics datasets covering 1.5 billion geometries across 70 atom species
05 · Leadership
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06 · Company updates
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07 · HAIC coverage
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08 · Official presence
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09 · Market pathway
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Market context
Companies using AI, machine learning, or computational biology to discover new drug candidates, identify drug targets, predict drug efficacy, or accelerate pharmaceutical development. Includes both small molecule and biologics development, precision oncology drug discovery, and AI-driven target identification and molecule design.
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