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Using GenAI and expert reasoning, drug developers can now explore an asset’s long-term potential as early as the preclinical stage. This shift is helping to reshape pipeline planning and refine therapeutic strategy.
Scientists have developed a new AI-guided tool that predicts how bowel cancer becomes resistant to treatment – which could lead to development of new personalised therapies.
AI is changing how clinical trials are run - quietly but significantly. Find out how digital twins are helping sponsors reduce control arms and accelerate development without changing trial endpoints.
Think drug discovery is slow? This biotech is moving faster, smarter and deeper – by asking the question that no one else has.
How do new cancer drugs make it to patients? This episode uncovers the challenges, successes, and AI advancements driving oncology treatments from preclinical screening to clinical trials.
DenovAI has unveiled a powerful AI-driven protein design platform capable of creating new, functional synthetic proteins from scratch - marking a big step forward for drug discovery.
Genomics laid the foundation for precision medicine, but on its own, it offers only part of the picture. This article explores how integrated multiomics can provide the deeper biological context needed to drive more effective therapies forwards.
Drug development has long been hindered by fragmented data and complex processes, but a new wave of AI is reshaping the landscape. By integrating genomic, clinical and molecular data, multimodal models are revealing hidden patterns and accelerating more precise advancements in medicine.
Preclinical and clinical development are critical to the success of ADCs, where early strategic decisions regarding manufacturability and scalability can make or break a project. Iwan Bertholjotti of Lonza emphasises the importance of proactive planning to avoid costly delays and ensure smooth progress towards clinical success.
Forget the buzzwords - SLAS 2025 showed what’s genuinely driving progress in drug discovery: usable AI, collaborative platforms and tools that solve real problems.
As AI reshapes scientific work, two founders debate how best to build tools scientists can trust — should we embed expertise into the model or the team? From agent-powered labs to hypothesis-generating machines, the future of drug discovery is being reimagined right now.
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 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.
