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AI-Driven Retrobiosynthesis for Mechanistic Discovery in Cancer and Precision Medicine

by jo.dobson@kcl.ac.uk | Dec 4, 2025

Rapid advances in omics technologies, coupled with major improvements in computational and analytical tools, have enabled the generation of high-quality, cost-efficient multi-omics data that are now driving the emergence of precision health and precision medicine...

Cross-Condition Digital Biomarkers from Wearable and Smartphone Data: Toward a Unified Framework for Behavioral and Physiological Monitoring in Mental and Neurological Disorders

by jo.dobson@kcl.ac.uk | Dec 3, 2025

Background:Advances in wearable and smartphone technologies have opened new possibilities for continuous, real-world monitoring of health and behaviour. While numerous studies have explored digital biomarkers within specific conditions such as depression or epilepsy,...

AI-Driven Cohort Identification: Multi-Agent System for Neurology Clinical Trial Recruitment

by jo.dobson@kcl.ac.uk | Dec 3, 2025

Background:Patient recruitment is a major challenge in clinical trials (CT) and the most common cause of trial discontinuation. Over half (55%) of publicly funded CTs fail to reach their recruitment targets [4], leading to incomplete studies, increased costs when...

GenAI for Early Detection of Treatment Resistance and Fair Access to Clozapine in Schizophrenia

by jo.dobson@kcl.ac.uk | Dec 3, 2025

Background Schizophrenia causes substantial personal and societal burden, with about one-third of patients developing treatment-resistant schizophrenia (TRS), defined as non-response to two adequate antipsychotic trials. Clozapine is the only proven TRS treatment, yet...

From Efficiency to Dysfunction: Defining the Principles of Brain Efficiency to Understand Psychiatric and Neurological Disorders

by luke | Dec 1, 2025

Learning from Machines to Understand the Brain We usually look to the brain to inspire how we build smarter, more efficient machines, but this project flips that idea. By learning from how machines stay efficient, we can uncover why the brain becomes inefficient in...
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  • John Jumper, PhD, from Google’s DeepMind talks about AlphaFold2

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