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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.
In this second part of a two-part series, we continue Sujeegar Jeevanandam’s exploration of the future of AI in drug discovery. We share his vision for transformative AI applications, such as simulating human pharmacokinetics and pharmacodynamics, and offer strategic recommendations for biotechs looking to adopt AI.
Download our latest report to discover how AI is transforming drug discovery, accelerating treatments and driving personalised care.
Insilico Medicine’s AI-designed drug for idiopathic pulmonary fibrosis (IPF), Rentosertib, has been granted an official name by USAN. This is the first drug where both the target and compound were discovered using generative AI, marking a major milestone in AI-driven drug development.
AI is transforming drug discovery, but its adoption mirrors past technological shifts in the industry. In this first part of a two-part series, we reveal Sujeegar Jeevanandam’s observations of the parallels between AI and the electronic lab notebook revolution, highlighting key challenges, lessons learned, and what the future holds for…
AI-driven drug development, powered by advanced models and expanding data access, is becoming a reality. Learn why navigating regulatory hurdles and mastering biology’s inherent complexities are crucial to fully unlocking its potential.
In this article, Dr Raminderpal Singh explores the transformative impact of the Deepseek R1 open-source large language model on drug discovery. Its potential offers exciting opportunities for both scientists and software developers, marking a significant advancement for the life sciences community.
Drug discovery scientists develop and test complex hypotheses using data and expertise, and build workflows to support this. In this third and final article, Dr Raminderpal Singh and Nina Truter summarise the tools used in the scientific workflow – and include key considerations.
Grifols has received a $21 million grant from The Michael J. Fox Foundation to fund a pioneering study aimed at identifying early biomarkers for Parkinson's disease (PD).
