A new artificial intelligence (AI)-based model developed by scientists at ETH Zurich could help determine optimal synthesis methods for new active pharmaceutical ingredients (API).
Published in Nature Chemistry, the work promises to help scientists avoid a trial-and-error approach, whereby chemical reactions are tested sequentially in a way which can be highly time consuming.
Working with the research and early development unit of Swiss cancer giant Roche (ROG: SIX), ETH Zurich has developed the model to help predict where a pharmaceutically active molecule can be chemically modified.
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