All Machine Learning (ML) articles – Page 6
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ArticleWhat SLAS 2025 really told us about drug discovery
Forget the buzzwords - SLAS 2025 showed what’s genuinely driving progress in drug discovery: usable AI, collaborative platforms and tools that solve real problems.
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ArticleHow AI and LLMs are transforming drug discovery: part 2
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.
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ArticleAI at the forefront of age-related disease treatment
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 ...
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NewsK Navigator: an AI co-pilot transforming biomedical research
K Navigator, a new AI-powered research co-pilot, is set to transform biomedical science by helping researchers explore complex data and accelerate discoveries.
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ArticleUsing knowledge graphs in drug discovery (Part 1): how they link to large language models
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.
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ArticleEarly evidence and emerging trends: How AI is shaping drug discovery and clinical development
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.
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ArticleThe evolution of AI in drug discovery: learning from history's mistakes (Part 2)
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.
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ReportBeyond the Lab: Artificial Intelligence
Download our latest report to discover how AI is transforming drug discovery, accelerating treatments and driving personalised care.
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NewsFirst AI-designed drug, Rentosertib, officially named by USAN
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.
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ArticleThe evolution of AI in drug discovery: learning from history's mistakes (Part 1)
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 ...
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ArticleNavigating the AI revolution: a roadmap for pharma’s future
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.
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ArticleLarge language models: now more affordable and reliable than ever
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.
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ArticleScientific workflow for hypothesis testing in drug discovery: part 3 of 3
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.
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NewsAI identifies life-saving treatment for rare Castleman's disease
An AI tool has identified adalimumab, a drug used for arthritis and Crohn’s disease, as a life-saving treatment for rare Castleman’s disease (iMCD). This finding offers hope for patients with the condition.
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NewsNew study shows CGM data can predict diabetes complications
UVA researchers found that continuous glucose monitor data can predict nerve, eye, and kidney damage in type 1 diabetes.
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NewsThe Michael J Fox Foundation for Parkinson’s Research awards grant to Grifols for pioneering study
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).
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NewsUVA’s computer models target antibiotics to combat resistance
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.
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ArticleHow AI will reshape pharma in 2025
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.
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ArticleThe paradox of data in precision medicine
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.
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NewsThe Pistoia Alliance: key findings on AI
Results from Pistoia Alliance’s Lab of the Future survey has shared important findings about the challenges life science companies face.