From Target to Trial: Artificial Intelligence in Psychiatric Drug Development

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How Artificial Intelligence Could Improve Psychiatric Drug Development

Developing new medicines for mental health conditions is difficult, expensive, and often unsuccessful. One reason is that people with the same diagnosis can differ greatly in their underlying biology and in how they respond to treatment. Clinical trials also rely heavily on symptom ratings and can be affected by placebo responses. This editorial explains how artificial intelligence (AI) could help at several stages of psychiatric drug development. AI can help researchers identify promising drug targets, design new treatment molecules, and use biological, brain-imaging, and clinical data to predict treatment response and improve clinical trials. Emerging approaches include digital twins, synthetic control groups, and digital measures of symptoms and behaviour. However, these technologies are still developing and should not be viewed as a solution to all the challenges of psychiatric drug development. Wider use will require representative datasets, strong data governance, transparent and interpretable models, rigorous clinical validation, and appropriate regulation.