Aligning Artificial Intelligence and Laboratory Execution in Drug Discovery
Artificial intelligence is transforming molecular design, but synthesis remains the limiting step in drug discovery. To translate computational advances into real productivity gains, organizations must better align digital design with laboratory execution. AI-driven orchestration provides a practical framework to coordinate design, synthesis, and testing within existing R&D infrastructures, accelerating the transition from in silico hypotheses to in vitro validation and improving the productivity of the DMTA cycle.
Yann Gaston-Mathé, Iktos

Artificial intelligence is transforming molecular design, but synthesis remains the limiting step in drug discovery. To translate computational advances into real productivity gains, organizations must better align digital design with laboratory execution. AI-driven orchestration provides a practical framework to coordinate design, synthesis, and testing within existing R&D infrastructures, accelerating the transition from in silico hypotheses to in vitro validation and improving the productivity of the DMTA cycle.
The Acceleration Paradox
Artificial intelligence is reshaping how molecules are conceived. Generative models can now explore vast regions of chemical space, proposing and optimizing candidate structures with unprecedented speed.
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