All Machine Learning (ML) articles – Page 5
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ArticleFuture-proofing drug development with GenAI
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.
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News
How bowel cancer beats treatment - and how AI can stop it
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.
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ArticleThe AI model that is changing clinical trial design
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.
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ArticleThe biotech mapping thousands of hidden therapeutic clues
Think drug discovery is slow? This biotech is moving faster, smarter and deeper – by asking the question that no one else has.
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ArticleTranslating Promising Drug Candidates from Preclinical Screening to Clinical Trials
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.
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NewsTurning AI into a biological design engine
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.
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ArticleThe next phase of the multiomics evolution, powered by AI
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.
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ArticleFrom siloed data to breakthroughs: multimodal AI in drug discovery
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.
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ArticleStrategic planning in ADC development: insights from Lonza
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.
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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.