The ARPA-H Computational ADME-Tox and Physiology Analysis for Safer Therapeutics (CATALYST) program will leverage artificial intelligence and machine learning to develop computer models that mimic real human biology to predict safety and effectiveness for Investigational New Drug candidates.   

Funding for awardees varies in amount and is contingent upon the recipient meeting aggressive milestones specific to their project.  

CATALYST performer teams are led by:  

  • The Charles Stark Draper Laboratory in Cambridge, Mass. seeks to develop a patient-centered, predictive model using the patient data layer, human organ data layer, biopsy data layer, and microphysiology data layer. This team will build a human data stack that can be used to understand how different patients respond to novel therapies. Awarded 26 September 2025. 
  • Deep Origin in San Francisco intends to build an FDA-qualifiable, self-improving in silico ADME-Tox and dosage prediction platform aimed at reducing and eventually replacing animal models, so drug developers can test how a medicine moves through and affects the human body on a computer before it ever reaches a person. Awarded 26 September 2025. 
  • Inductive Bio in Brooklyn, N.Y. aims to transform preclinical drug safety assessment for small molecules by building in silico organ toxicity models for liver and heart that integrate the latest AI advances with physiology-based mathematical models., helping identify potential heart and liver side effects earlier and more accurately during drug development. Awarded 26 September 2025. 
  • The Jackson Laboratory in Bar Harbor, Maine intends to replicate broad human cardiovascular variation to comprehensively characterize non-arrhythmic cardiotoxicity using transcriptomic, metabolic, and phenotypic analyses. By building digital cardio models based on mouse and human physiology, drugs can be evaluated against a wide range of heart genetic profiles and physiology differences based on patient populations. Awarded 26 September 2025. 
  • Black Mesa Technology, Inc., in Bedford, Mass. Intends to establish and document a good experimental practice (GxP) environment to assure quality and security of data and AI methods framework, ensuring the AI tools behind CATALYST are trustworthy, secure, and meet regulatory-quality standards. Awarded 25 September 2025. 
  • Cedars-Sinai Medical Center in Los Angeles will leverage its extensive biobank samples to derive patient-specific cell-based models of cardio- and neurotoxicity, which can be exposed to real-world stressors like aging to develop clinically accurate computational toxicity predictions. This will make safety assessments in older patients and patients with comorbidities more accurate before clinical trials. Awarded 25 September 2025. 
  • Peptilogics, Inc., in Pittsburgh seeks to develop ADME-Tox predictive models and methods for therapeutic peptides while including aspects related to off-target protein-ligand complexes and post-translational modifications, helping designers of next-generation peptide drugs spot unintended targets and side effects earlier in development. Awarded 26 September 2025. 
  • University of North Carolina at Chapel Hill aims to build antibody drug-customized organ-on-chip models and three in-silico platforms focused on improving ADME-Tox predictions in humans including pregnant individuals, so developers of antibody-based medicines can better predict how these drugs work in the body and assess safety for populations often left out of trials, including during pregnancy. Awarded 25 September 2025.