Authors: Sateesh Kumar Beepala
Abstract: Artificial Intelligence (AI) is transforming synthetic Organic Chemistry by enabling rapid and efficient planning of synthetic routes through Computer-Aided Retrosynthesis (CASP). Traditional Retrosynthetic analysis, based on expert knowledge, has evolved into AI-driven systems capable of learning from millions of published chemical reactions. Modern approaches, including machine learning (ML), deep learning (DL), graph neural networks (GNNs), and transformer models, have significantly improved reaction prediction, retrosynthetic route generation, and reaction optimization. AI-powered platforms such as IBM RXN, ASKCOS, AiZynthFinder, and SYNTHIA have become valuable tools in pharmaceutical research, natural product synthesis, and sustainable chemistry. This review summarizes recent advances in AI-assisted retrosynthesis, highlights current applications, discusses existing challenges, and outlines future prospects for intelligent and autonomous chemical synthesis.
