Revolution Medicines, a late-stage clinical oncology company, and Iambic Therapeutics, an AI-driven drug discovery company, have announced a multi-year technology and research collaboration to pursue novel drug candidates using Iambic’s AI models.
Iambic will use Revolution Medicine’s structures and molecular libraries to train a bespoke version of NeuralPLexer, Iambic’s AI model for protein-ligand structure prediction.
Both companies will have access to the improved models, with each company retaining rights to a limited number of exclusive targets, as well as the ability to designate additional exclusive targets to pursue independently. In the agreement, Iambic will receive up to $25 million through a combination of upfront and expected near-term performance-based milestone payments, as well as ongoing research and development reimbursements.
“The capabilities of Iambic’s AI-driven discovery platform, partnered with our unique collection of proprietary data, present an opportunity to rapidly explore oncology targets known to be challenging to address through conventional drug discovery approaches,” said Mark Goldsmith, MD, PhD, CEO and chairman of Revolution Medicines, in a public release.
NeuralPLexer employs a flow matching architecture to achieve fast inference times and high-accuracy prediction of biomolecular interactions to promote scalability across large datasets. Additionally, NeuralPLexer is generalizable across different target classes and mechanisms of action, offering an appealing tool for drug discovery across clinical indications.
Revolution Medicines will also have access to Iambic’s PropANE model, a pre-trained graph neural network deployed across dozens of drug properties for lead selection and optimization.
Last September, Iambic announced a partnership with Lundbeck, a pharmaceutical company focused on neurological disease, to leverage NeuralPLexer for small molecule drug discovery to address migraines. In contrast, the technology enablement collaboration with Revolution Medicines directly provides the partner with software tools to be applied in their own internal discovery research.
Tom Miller, PhD, CEO and co-founder of Iambic, emphasizes that the translation of the company’s AI models to real-world drug discovery problems is what differentiates the company in the AI space.
“It’s one thing to have a tool that can do impressive benchmarking. It’s another to demonstrate that an AI model delivers discoveries that will advance internal programs to the clinic, as we’ve shown at Iambic,” Miller told GEN.
A San Diego-based company, Iambic was founded in 2020 and is currently composed of 90 employees. In April 2024, Iambic advanced its first pipeline candidate, a selective and brain-penetrant small molecule inhibitor of HER2 signaling for solid tumors (IAM1363), into the clinic. IAM1363 moved from discovery to a first-in-human study in under two years—less than one-third of the average six-year conventional early drug development timeframe.
Iambic completed dose expansion of IAM1363 in June and plans to report more clinical data later this year. Iambic’s KIF18A inhibitor program for targeting chromosomally unstable tumor cells is anticipated to be the company’s second drug to enter the clinic in Q4 of 2025.
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