Inductive Bio Announces an up to $21M Award to Develop AI Drug Toxicity Models that Improve Drug Safety Assessment with Leading Academic and Biopharmaceutical Organizations

NEW YORK, December 8, 2025 — Inductive Bio, an AI drug discovery partner developing virtual chemistry labs, announced today that it has received an up to $21M award to lead a project to develop next-generation models of drug toxicity to advance safer therapeutics and reduce reliance on animal testing. The company has teamed up with Amgen, Cincinnati Children’s Hospital Medical Center, Baylor College of Medicine, and Torch Bio, a University of Michigan Medical School spinout company, to use AI trained on data from advanced human model systems to build toxicity prediction models that could fundamentally change how drug safety is assessed. ‍

‍This approach has the potential to reduce late-stage development failures by leveraging human biology-based predictive models and, ultimately, to accelerate the delivery of safe, innovative medicines to patients. ‍

‍Under the ambitious project called DATAMAP (Digital Acceleration of Toxicity Assessment with Mechanistic and AI-driven Predictions), the team will generate biological data using advanced organoids, ex-vivo human tissue systems, and microphysiological systems - models that more accurately represent human biology than traditional approaches.

The contract award is from the Advanced Research Projects Agency for Health (ARPA-H) Computational ADME-Tox and Physiology Analysis for Safer Therapeutics (CATALYST) program. CATALYST aims to revolutionize preclinical drug safety prediction by developing human-based models that accurately estimate toxicity and safety profiles for drug candidates. Roughly 90% of clinical-stage drug candidates never reach patients in the broader market, and a quarter of those failures result from safety issues during clinical trials that were not predicted by preclinical animal testing.

The initial work will be focused on drug induced liver injury (DILI) and cardiotoxicity, which drive nearly 40% of drug withdrawals due to safety concerns. Inductive will build AI models from the resulting data and work with the FDA to validate their regulatory applications. Amgen will advise on the development, real-world context of use in drug development, and potential applications to novel therapies.

“While animal tests have historically been the gold standard for assessing drug safety pre-clinically, the reality is that they often fail to capture how humans will actually respond to new therapeutic candidates,” said Ben Birnbaum, Inductive’s co-founder and the Principal Investigator for the project team. “We’re excited to bring together Inductive’s datasets and AI models with organoids, ex-vivo human tissue, and microphysiological systems to better predict drug safety issues that animal testing misses. Our biopharmaceutical collaborator will demonstrate these technologies’ real-world impact by submitting an investigational new drug application (IND) to the FDA using the technology. We look forward to making them available to every drug discovery team in order to minimize the number of promising drug candidates that fail in the clinic and reduce reliance on animal testing.”

The DATAMAP project aligns with a broader FDA directive to advance new-approach methodologies as alternatives to reliance on animal testing in drug development - a shift that has gained momentum as advances in human biology modeling and AI create viable alternatives to traditional preclinical approaches.

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About Inductive Bio

Inductive builds virtual chemistry labs that help drug hunters design higher quality molecules, faster. Inside these labs, AI chemistry assistants run millions of experiments on digital organs trained on data from human organs and organoids, enabling teams to predict how molecules will behave in the body. The most promising molecules move from the virtual lab to the wet lab in a tight feedback loop that accelerates the advancement of high-quality molecules. Inductive already powers dozens of active discovery programs, including collaborations with leading biopharma partners.

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