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Scientists at the University of Washington’s Institute for Protein Design have used artificial intelligence to create antibodies entirely from scratch, a breakthrough that could reshape drug discovery.
At ELRIG’s Drug Discovery 2025, Drug Target Review spoke with the teams turning big ideas into usable tools – automation, AI and biology – that help scientists work smarter.
Cellarity has published a new paper in detailing an AI-powered framework that integrates single-cell transcriptomics to make drug discovery faster and more successful.
Nature’s pharmacy has yielded half of today’s medicines, yet most of its potential remains untapped. AI is now changing how quickly new therapies can be found.
Vish Srivastava considers the benefits of expanding the role of real-world data in drug discovery to provide improved therapies, faster and with greater success.
AI has advanced molecule design, yet synthetic feasibility remains a bottleneck. Chemistry-first approaches offer a practical way forward.
A new fibre-optic method lets researchers monitor amyloid plaque buildup in living, freely moving mice – offering a minimally invasive way to track Alzheimer’s disease progression and test potential therapies.
Multiomics, AI and liquid biopsies are giving researchers real-time insight into tumour biology and enabling more personalised cancer therapies. Find out how these technologies are advancing biomarker discovery, improving patient stratification, and guiding the design of new treatments.
Scientists have mapped the diversity of fibroblasts and discovered how ‘rogue’ fibroblasts drive multiple diseases, revealing drug targets that could transform treatments across the body.
AI is increasingly used in drug discovery, but hidden bias and ‘black box’ models threaten trust and transparency. This article explores how explainable AI can turn opaque predictions into clear, accountable insights.
By combining human tissue models with explainable AI, researchers can analyse complex patient data to identify which treatments work best for which patients. First applied to inflammatory bowel disease, this approach could improve clinical trial success rates across many diseases.
Quantitative Systems Pharmacology (QSP) is fast becoming a standard tool in drug development, offering a human-relevant way to predict drug effects before the clinic. Dr Josh Apgar of Certara explains how it is helping to cut reliance on animal testing and speed discovery.
AI is starting to transform drug discovery, but progress is still slow and big challenges remain. Thibault Géoui explores the gaps, hurdles and breakthroughs needed before it can truly change pharma R&D.
Thibault Géoui explains why AI could finally help pharma overcome its productivity crisis and why the payoff won’t come as quickly as the optimists claim.
Drug discovery is slow, costly and often unsuccessful. DTR hears how GATC Health is applying AI and multiomics to make the process faster, more precise and less reliant on trial and error.
