Green organic synthesis in drug discovery: emerging roles of artificial intelligence and quantum chemical approaches

Green organic synthesis has emerged as an area of interest in drug discovery research because of the environmental, regulatory, and economic challenges associated with traditional synthetic methods. Despite the availability of green chemistry solutions, pharmaceutical synthesis is still limited to empirical optimization and trial-and-error approaches. Recent advances in artificial intelligence and quantum chemistry are now making it possible to predict outcomes in reaction design, retrosynthesis, catalyst design, and reaction mechanisms. Artificial intelligence can facilitate data-driven prediction and optimization, while quantum chemistry can provide insights into mechanism details and selectivity. This review highlights recent advances in combining AI with quantum chemistry to further green organic synthesis in reaction prediction, catalyst and solvent optimization, and drug-related examples. These approaches are on the cusp of enabling more efficient, selective, and environmentally benign synthetic methodologies for sustainable drug discovery.