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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.
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.
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.
Effective financial management is vital for clinical trial success, yet many preclinical and clinical companies face inefficiencies due to outdated systems. Jennifer Kyle, CEO of Condor Software, explains how advanced financial platforms can streamline processes, improve forecasting and ensure better resource allocation throughout drug development.
Want to understand the real impact of AI in 3D sample analysis? This episode cuts straight to how machine learning is accelerating research and overcoming current limitations.
Researchers at the University of North Carolina at Charlotte have used artificial intelligence to look at how the H5N1 bird flu virus is evolving to evade the immune system - insights that could make way for development of effective future therapies.
James Atwood, COO of Opentrons, shares how accessible lab automation is helping research teams tackle tighter budgets, faster timelines and complex discovery workflows.
A new study suggests statins, cheap and widely used cholesterol drugs, could be repurposed to reduce the risk of death from sepsis. Researchers reported a 39 percent drop in 28-day mortality, highlighting their potential role in critical care.
Forget the buzzwords - SLAS 2025 showed what’s genuinely driving progress in drug discovery: usable AI, collaborative platforms and tools that solve real problems.
The body undergoes changes with age that can lead to conditions like sarcopenia and osteoarthritis, burdening individuals and healthcare systems. Find out how Rejuvenate Biomed uses AI to decode ageing biology and develop combination therapies targeting the root causes of age-related diseases, offering hope for better treatments and quality of…
K Navigator, a new AI-powered research co-pilot, is set to transform biomedical science by helping researchers explore complex data and accelerate discoveries.
In this second interview of the series, Andreas Kolleger, Head of GenAI Innovation at Neo4j, discusses how knowledge graphs and AI are transforming scientific discovery and improving life sciences workflows.
In this first interview of a two-part series, Andreas Kolleger explores the convergence of knowledge graphs and large language models. As the head of GenAI innovation at Neo4j, Andreas brings a unique cross-industry perspective on how these technologies can enhance life sciences workflows.
Drug development is plagued by high costs, long timelines and low success rates, but what if AI could change that? Read on to discover real-world examples and explore the transformative potential of AI in drug development.
