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From chemist to AI agent builder: inside the rise of agentic AI in drug discovery
Dr Raminderpal Singh speaks with Dr Srijit Seal about why specialised AI agents are outperforming general-purpose models in drug discovery and what a new consortium paper shows about their use in practice.
ArticleMachine learning identifies biological signals linked to emotional hunger
Researchers at Phenomix Sciences are using machine learning and genetic risk scoring to investigate emotional hunger, an obesity phenotype linked to emotional and reward-driven eating behaviours. Dr Timothy O’Connor discusses how the approach could improve patient stratification, obesity research and treatment selection.
ArticleBeyond tangles: why soluble intracellular tau should guide drug discovery
Tau tangles are a hallmark of Alzheimer’s disease and related disorders, but evidence suggests the real damage may come from rare, soluble tau species inside neurons. Targeting these hidden drivers of circuit dysfunction could be key to restoring memory and cognition.
ArticleWhy AI models need patient data to deliver in drug discovery
Despite rapid advances in AI, many drug discovery models still struggle to translate computational predictions into clinical outcomes. Thomas Clozel explains how Owkin is training AI on large-scale patient-derived data while integrating experimental and clinical validation directly into model development.
Opinion and interviews
Computational design drives new generation of synthetic promoters
Designing gene control from scratch is becoming possible. SynGenSys is using computational design to create synthetic promoters for advanced therapies.
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