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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).
Researchers at the University of Virginia School of Medicine have developed computer models to create more targeted antibiotics. This approach aims to fight antibiotic resistance by focusing on specific bacteria in different parts of the body, reducing the reliance on broad-spectrum antibiotics.
AI is set to transform drug development in 2025, streamlining processes and opening new possibilities. Learn how this technology is transforming clinical trials and reshaping the pharmaceutical industry.
The path to faster breakthroughs in precision medicine begins with overcoming the complexities of multi-modal data. Discover how innovative solutions are enabling more personalised treatments.
Results from Pistoia Alliance’s Lab of the Future survey has shared important findings about the challenges life science companies face.
In this four-part series, Dr Raminderpal Singh will discuss the challenges surrounding limited data quality, and some pragmatic solutions. In this second article, he discusses the problems that occur when using data of poor quality.
