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Iambic Announces Enchant v2, its Next Generation AI Model for Predicting the Clinical Viability of Drug Discovery Programs

Iambic Announces Enchant v2, its Next Generation AI Model for Predicting the Clinical Viability of Drug Discovery Programs

Business Wire05-05-2025
SAN DIEGO--(BUSINESS WIRE)--Iambic, a clinical-stage life science and technology company developing novel medicines using its AI-driven discovery and development platform, published on major advances to Enchant, Iambic's breakthrough multimodal transformer model for predicting clinical and preclinical endpoints related to the drug discovery and development process. This new version of Enchant marks a pivotal advance in the use of large-scale transformers for drug discovery and supports a fundamental hypothesis: with the right model, architecture, and training strategy, one can achieve exceptional predictive power even in the most data-constrained settings.
"Enchant is an exceptionally powerful multimodal transformer model for drug discovery and development,' said Fred Manby, Ph.D., Co-Founder and CTO of Iambic. "Enchant was created to make high-confidence predictions in sparse data regimes—where biology is uncertain and clinical data is limited. That setting reflects the real-world challenge of understanding how a novel therapeutic might affect a patient. By enabling higher-confidence predictions around clinical and preclinical endpoints tied to drug design, portfolio prioritization, and trial strategy, we may begin to address the fundamental issue of improving translation and increasing the likelihood of success in clinical trials. With this version of Enchant and those to come, we believe it is poised to help redefine the trajectory of modern medicine."
Enchant's predictions around clinical and preclinical endpoints could help address the fundamental issue of how to increase the likelihood of success translating a potential therapeutic to and through clinical trials. This ability complements Iambic's already demonstrated ability to rapidly progress a potential drug into clinical trials. Read more about how Enchant, Iambic's breakthrough multimodal transformer model, can determine the viability of new drug molecules and make high-confidence predictions with sparse data at Enchant v2: Pushing the Boundaries of Predictive Drug Discovery.
About Iambic's AI-Driven Discovery Platform
The Iambic AI-driven platform was created to address the most challenging design problems in drug discovery, leveraging technology innovations such as Enchant (multimodal transformer model that predicts clinical and preclinical endpoints) and NeuralPLexer (best-in-class predictor of protein and protein-ligand structures). The integration of physics principles into the platform's AI architectures improves data efficiency and allows molecular models to venture widely across the space of possible chemical structures. The platform enables identification of novel chemical modalities for engaging difficult-to-address biological targets, discovery of defined product profiles that optimize therapeutic window, and multiparameter optimization for highly differentiated development candidates. Through close integration of AI-generated molecular designs with automated chemical synthesis and experimental execution, Iambic completes design-make-test cycles on a weekly cadence.
About Iambic
Founded in 2020 and headquartered in San Diego, California, Iambic is disrupting the therapeutics landscape with its unique AI-driven drug-discovery platform. Iambic has assembled a world-class team that unites pioneering AI experts and experienced drug hunters with strong track records of success in delivering clinically validated therapeutics. The Iambic platform has demonstrated delivery of high-quality, differentiated therapeutics to the clinical stage with unprecedented speed and across multiple target classes and mechanisms of action. The Iambic team is advancing an internal pipeline of clinical assets to address urgent unmet patient needs. Learn more about the Iambic team, platform, and pipeline at iambic.ai.
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