Bridging Chemists and AI: An Expert-Augmented Framework for Interpretable Route Evaluation

ArXi:2605.29108v1 Announce Type: new Selecting efficient multi-step synthetic routes is a central challenge in organic synthesis, particularly in medicinal and process chemistry, where route choice directly impacts feasibility, cost, and development efficiency. Data-driven assessment systems often oversimplify the multi-objective nature of synthesis design and rely on proxy datasets, such as patent routes, rather than universally grounded criteria. To address this, we