Ginkgo Datapoints, Tangible Scientific, and Inductive Bio have announced a collaboration to move Absorption, Distribution, Metabolism, and Excretion (ADME) profiling earlier in the drug discovery process—from lead optimization to hit identification. The initiative combines AI, lab automation, and tighter compound logistics to accelerate decision-making.
The partnership targets a common bottleneck in small-molecule development where comprehensive ADME data is typically generated only after a lead series is selected. By evaluating these properties earlier, teams aim to reduce late-stage failures and optimize compound selection from the outset.
Ginkgo Datapoints brings its large-scale screening capabilities and machine learning models, while Tangible Scientific contributes automated experimental platforms. Inductive Bio adds expertise in compound management and logistics, enabling faster iteration between computational predictions and wet-lab validation.
No specific financial terms, trial phases, or regulatory timelines were disclosed. The collaboration focuses on technology development rather than a specific therapeutic candidate, limiting immediate investor applicability. Ginkgo Bioworks, the parent company, continues to expand its AI-enabled drug discovery services amid a competitive landscape.
The approach introduces potential workflow changes that could shorten discovery timelines for small-molecule programs. However, real-world validation data and cost comparisons against standard ADME screening remain absent from the announcement.