New active pharmaceutical ingredients lay the foundations for innovative and better medical treatments. However, identifying them and, above all, producing them through chemical synthesis in the laboratory is no mean feat. To home in on the optimum production process, chemists normally use a trial-and-error approach: they derive possible methods for laboratory synthesis from known chemical reactions and then test each one with experiments; a time-consuming approach that is littered with dead ends.
Now scientists at ETH Zurich, together with researchers from Roche Pharma Research and Early Development, have come up with an approach based on artificial intelligence (AI) that helps to determine the best synthesis method, including its probability of success. “Our method can greatly reduce the number of lab experiments required,” explains Kenneth Atz, who developed the AI model as a doctoral student together with Professor Gisbert Schneider at the Institute of Pharmaceutical Sciences at ETH Zurich.
Active pharmaceutical ingredients usually consist of a scaffold onto which are bound what are known as functional groups. These are what gives the substance its highly specific biological function. The scaffold’s job is to bring the functional groups into a defined geometric alignment so that they can act in a targeted manner. Imagine a crane construction kit, in which a framework of connecting elements is bolted together in such a way that functional assemblies like rollers, cable winches, wheels and the driver’s cab are arranged correctly in relation to each other.
Introducing chemical functions
One way to produce drugs with a new or improved medicinal effect involves placing functional groups at new sites on the scaffolds. This might sound simple, and it certainly wouldn’t pose a problem on a model crane, but it is particularly difficult in chemistry. This is because the scaffolds, being primarily composed of carbon and hydrogen atoms, are themselves practically nonreactive, making it difficult to bond them with functional atoms such as oxygen, nitrogen or chlorine. For this to succeed, the scaffolds must first be chemically activated via detour reactions.