IsoDDE is presented as a next‑generation AI platform designed to advance in silico drug discovery by improving predictive accuracy, expanding target reach, and IsoDDE is presented as a next‑generation AI platform designed to advance in silico drug discovery by improving predictive accuracy, expanding target reach, and

Isomorphic Labs’ Next‑Gen IsoDDE Engine Advances AI‑Driven Design Of Complex And Hard‑To‑Target Molecules

2026/02/10 21:18
3 min read
Isomorphic Labs Unveils IsoDDE: The Most Advanced AI Platform For In Silico Drug Design

Isomorphic Labs, a Google DeepMind spin‑off, has presented IsoDDE, described as the most advanced publicly disclosed AI system for computational drug design as of February 2026. 

The platform is positioned as a full‑cycle in silico engine that moves beyond the structure‑prediction focus of AlphaFold 3 and aims to address several long‑standing limitations in digital drug‑development workflows. 

According to the company, IsoDDE is designed to generalize to unfamiliar biological systems, predict binding affinities without relying on traditional physics‑based simulations, identify hidden regulatory pockets, and operate effectively with antibodies and other complex biomolecules.

In internal programs, Isomorphic Labs reports that IsoDDE is already used to interpret previously uncharacterized structures, detect pockets that had not been experimentally annotated, and generate new chemical matter for targets considered difficult to drug. The system is presented as a unified computational framework intended to bridge the gap between structural prediction and practical drug‑design tasks, offering accuracy levels that the company claims exceed earlier deep‑learning and physics‑based approaches.

The platform’s development follows rapid progress in AI‑enabled molecular modeling since the release of AlphaFold 3 in 2024. While that model significantly advanced protein–ligand structure prediction, it did not fully resolve the challenge of applying computational methods to real‑world drug‑discovery pipelines, where models must handle diverse biochemical properties and extrapolate to systems outside their training distribution. IsoDDE is positioned as an attempt to close this gap by providing a scalable foundation capable of navigating unexplored regions of biological and chemical space.

Isomorphic Labs states that IsoDDE is already integrated into collaborations with major pharmaceutical companies, where the platform performs in silico design and prediction while partners conduct experimental validation and clinical development. The company has also continued to expand its internal pipeline. Between 2025 and 2026, it secured substantial investment, including a $600 million round in March 2025, and is preparing several proprietary molecules—primarily in oncology—for entry into clinical trials.

IsoDDE is presented as a next‑generation computational engine intended to enhance predictive accuracy, broaden the scope of druggable targets, and accelerate the transition from molecular modeling to experimentally validated therapeutic candidates.

IsoDDE Marks New Benchmark In AI‑Driven Drug Design

IsoDDE is described as a significant advancement in predictive accuracy and functional scope, offering a more detailed view of the molecular systems that govern human biology and improving the computational design of compounds intended to influence them. 

Within ongoing research programs at Isomorphic Labs, the platform is reported to be used routinely to interpret structures that have not been previously characterized, to detect pockets that were not experimentally identified, and to generate new chemical matter aimed at challenging therapeutic targets. 

The company indicates that development will continue toward expanding the boundaries of in silico drug design, with the intention of applying these enhanced capabilities to areas of drug discovery that have historically proven difficult.

The post Isomorphic Labs’ Next‑Gen IsoDDE Engine Advances AI‑Driven Design Of Complex And Hard‑To‑Target Molecules appeared first on Metaverse Post.

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