Isomorphic Labs first-in-class cryptic-pocket strategy

The real advantage is not just finding a molecule faster, it is finding a place on the protein that rivals are not even aiming at yet. If IsoDDE can reliably spot cryptic and allosteric pockets, Isomorphic can start programs on targets that standard screening misses, design molecules around less crowded binding sites, and claim composition and method patents around a novel mechanism instead of competing in the same active site race as everyone else.

• This matters most in oncology and immunology, where many biologically validated targets have been hard to drug with classic small molecule workflows. Relay built an allosteric oncology program around PI3K, and Schrödinger also markets cryptic pocket discovery as a way to open harder targets, which shows the value sits in target enablement, not just model accuracy.
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• The workflow is concrete. IsoDDE searches a protein for hidden cavities that may only appear when a ligand binds, then generates new compounds for that pocket and scores them for binding, selectivity, solubility, and permeability. That is different from testing a fixed library against an already obvious pocket.
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• Commercially, pharma partners are paying for this capability before clinical proof. Isomorphic signed Lilly and Novartis collaborations in January 2024, then expanded Novartis in February 2025. That suggests large drug companies see differentiated access to hard targets as valuable enough to fund early, even before a named clinical candidate.
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The next step is a shift from interesting structure predictions to proprietary asset creation. If Isomorphic keeps turning hidden pockets into drug programs, it can build a pipeline where the moat comes from owning the target hypothesis, the binding site, and the chemistry together, which is where the strongest economics in AI drug discovery will sit.