Enterprise AI Analysis

Procrustean Bed for AI-Driven Retrosynthesis: A Unified Framework for Reproducible Evaluation

Progress in computer-aided synthesis planning (CASP) is obscured by the lack of standardized evaluation infrastructure and the reliance on metrics that prioritize topological completion over chemical validity. We introduce RetroCast, a unified evaluation suite that standardizes heterogeneous model outputs into a common schema to enable statistically rigorous, apples-to-apples comparison. The framework includes a reproducible benchmarking pipeline with stratified sampling and bootstrapped confidence intervals, accompanied by SynthArena (syntharena.ischemist.com), an interactive platform for qualitative route inspection. We utilize this infrastructure to evaluate leading search-based and sequence-based algorithms on a new suite of standardized benchmarks. Our analysis reveals a divergence between "solvability" (stock-termination rate) and route quality; high solvability scores often mask chemical invalidity or fail to correlate with the reproduction of experimental ground truths. Furthermore, we identify a "complexity cliff" in which search-based methods, despite high solvability rates, exhibit a sharp performance decay in reconstructing long-range synthetic plans compared to sequence-based approaches. We release the full framework, benchmark definitions, and a standardized database of model predictions to support transparent and reproducible development in the field

Client Problem: Current computer-aided synthesis planning (CASP) lacks standardized evaluation, relying on metrics like 'solvability' (Stock-Termination Rate) that prioritize topological completion over chemical validity. This often masks chemical invalidity and fails to reproduce experimental ground truths. Search-based methods also show a sharp performance decay for long-range synthetic plans, posing a challenge for complex syntheses.

Solution Overview: RetroCast is introduced as a unified, open-source evaluation suite to standardize heterogeneous model outputs into a common schema for rigorous, apples-to-apples comparison. It features a reproducible benchmarking pipeline with stratified sampling, bootstrapped confidence intervals, and an interactive platform (SynthArena) for qualitative route inspection. This framework aims to provide transparent and reproducible development by offering chemically meaningful multi-ground-truth evaluation protocols, addressing the limitations of prior metrics.