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Schrödinger has announced a collaboration with Eli Lilly’s TuneLab platform, integrating advanced AI-driven drug discovery workflows into its LiveDesign enterprise informatics system.
Headlamp Health has launched Lumos AI®, a new decision-support platform designed to bring greater precision to neuroscience drug development.
What happens when AI stops guessing and starts reasoning? Agentic AI is bringing scientific logic into the heart of drug discovery.
A new survey by the Pistoia Alliance reveals a growing ‘scientific content crisis’ in life sciences, showing that incomplete data and weak governance are limiting the accuracy and adoption of AI in research and development.
Can automation and AI finally make science run at the speed of thought? Eric Ma shares how disciplined systems, not new models, will drive the next wave of discovery.
BCG’s Chris Meier outlines how advances in AI and new UK policies could accelerate drug development, streamline clinical trials and strengthen the country’s life sciences sector.
Demands on central laboratories are consistently increasing, heightening the challenge to deliver operational excellence and the highest standard of scientific integrity with both speed and agility. ICON Laboratories is transforming the way we leverage data and intelligent operational models to meet evolving trial needs.
Everyone talks about AI speeding up drug discovery, but Eric Ma explains why, without clean data and statistical discipline, it can actually do the opposite.
Bigger isn’t always better. In drug discovery, Dr Michael Ritchie argues that the future belongs not to those with the most data, but to those who understand its biological depth.
Within3’s Jason Smith explores how artificial intelligence is breathing new life into next-generation launch situation rooms; delivering actionable insights for pharmaceutical companies.
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 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.
