Enchant v3 is the next generation of Iambic’s multimodal transformer model, trained using 41 billion parameters on more than 6,000 molecular properties across 16 biomedical data modalities

Enchant v3 ingests diverse datasets, deploys a mixture-of-experts architecture, and tests multiple hypotheses in parallel to optimize discovery and development decisions
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San Diego – Sept. 21, 2026 – Iambic, a clinical-stage life science and technology company developing novel medicines using its AI-driven platform, today unveiled Enchant v3, the next generation of its multimodal transformer model built to advance end-to-end drug discovery and development. Enchant is the ‘brain’ behind Iambic’s molecular superintelligence platform that, when combined with Iambic’s in-house high-throughput experimental chemistry and biology capabilities, can learn from and predict many properties for a target compound profile. Read the report about Enchant v3 here.

“Enchant v3 is an architectural leap over Enchant v2, with new capabilities to be deployed for internal and partner drug discovery and development efforts,” said Fred Manby, PhD, Co-Founder and CTO, Iambic. “Earlier versions of Enchant have demonstrated utility across our pipeline, helping us predict critical preclinical and clinical endpoints. Enchant has shown robust scaling laws, with larger models exhibiting more powerful predictive capabilities. Enchant v3 continues this trend and constitutes our next step to make better technology for better medicines.”

Enchant was built to:

• Ingest diverse data, including public and proprietary data and different modalities, such as assays, text, images, multi-omics, biomolecular structures and sequences, clinical trial data, and more
• Leverage model scale so that Enchant gets better at predicting one endpoint when trained on data from other, related endpoints and on other molecules
• Break through data walls that have historically separated preclinical drug discovery from clinical development
• Convert model outputs into probability-guided decisions by using uncertainty quantification to maximize useful information from laboratory experiments and prioritize potential compounds

Highlights of Enchant’s next generation, v3, include:

• 41 billion parameters for greater reasoning complexity
• Pretrained on 4.5 trillion tokens
• 6,000+ molecular properties for multi-parameter optimization
• 16 biomedical modalities, including text, assay data, molecule structure, protein structure, 3D structure, images, multi-omics, biologics, clinical trial data, and pharmacokinetics, for a more comprehensive understanding of the underlying chemistry and biology as well as clinical tractability
• Predictable scaling laws, demonstrating that increased model scale correlates with improved prediction accuracy across a diverse range of preclinical and clinical endpoints

When we launched Enchant in 2024, it was not obvious that scaling laws would hold in a domain like drug discovery,” said Matt Welborn, PhD, SVP of Machine Learning, Iambic. “Biomedical data is richer than text, more complicated to work with, but allows us to build a unique capability. Across three generations of the model, the scaling has held – whenever we have added parameters, data, and modalities, the predictions improved, including for endpoints where data is sparse."

Enchant v3 was designed to enable two key objectives – increase the probability of success for drug candidates and expand into new therapeutic areas and modalities to advance more internal and partner programs. For greater insight, including specific examples of how Enchant has helped advance the Iambic pipeline, read today’s report on Enchant v3 here.

About Iambic

Iambic’s mission is to make better technology for better medicines. By utilizing molecular superintelligence — integrating proprietary AI with automated, scalable chemistry and biology experimentation — our platform is designed to address the totality of drug discovery and development. We believe the utility of our platform is demonstrated by the discovery of a novel drug candidate advanced to clinic in approximately two years, along with a diverse preclinical pipeline. Our leading AI technologies include Enchant and NeuralPLexer for multimodal endpoint prediction designed to improve the speed, precision, and success rates of drug discovery and clinical development. At Iambic, we are building an engine that is designed to power the future of medicine. | iambic.ai