All Machine Learning (ML) articles – Page 2
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ArticleQuality over quantity: drug discovery automation in 2026
Automation in 2026 is no longer judged by the volume of experiments, but by the reliability of the evidence they produce. As complex biology and tighter budgets collide, industry leaders are pivoting toward automated workflows to secure the data integrity required for confident, early-stage decision-making.
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NewsNew Lumos AI platform targets precision in mental health drugs
Headlamp Health has launched Lumos AI®, a new decision-support platform designed to bring greater precision to neuroscience drug development.
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ArticleAgentic AI: teaching machines to think like scientists
What happens when AI stops guessing and starts reasoning? Agentic AI is bringing scientific logic into the heart of drug discovery.
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NewsInsilico secures $888million Servier partnership for AI oncology
Insilico Medicine and Servier have announced a multi-year collaboration to accelerate the discovery of new cancer therapies, using artificial intelligence to tackle challenging oncology targets and shorten early-stage drug development timelines.
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ArticleThe data fragmentation problem holding drug discovery back
The DMTA cycle depends on clear data flow, yet most labs still work across disconnected systems. Sean McGee, Director of Product at Certara, explains how better infrastructure and AI can help teams work faster and make decisions with more confidence.
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NewsNew AI model links genetic mutations to specific diseases
Scientists have developed a new artificial intelligence tool that can identify harmful genetic mutations and predict the types of diseases they are likely to cause, offering faster diagnosis and new opportunities for drug discovery.
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ArticleRNA that lasts longer and lands exactly where it should
RNA therapies are moving past burst-and-fade limits. New advances in circular RNA and targeted delivery could transform how we treat autoimmune disease, infections and beyond.
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ArticleProtein folding interference: a new path to hard-to-drug targets
Protein folding interference offers access to targets long considered unreachable by traditional drug discovery. By acting on transient folding intermediates, this approach presents a new opportunity to eliminate disease-driving proteins.
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NewsLife sciences face ‘scientific content crisis’ in AI adoption
A new survey by the Pistoia Alliance reveals a growing ‘scientific content crisis’ in life sciences, showing that incomplete data and weak governance are limiting the accuracy and adoption of AI in research and development.
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NewsBits2Bonds: AI system accelerates discovery of RNA delivery polymers
Researchers at LMU Munich have developed Bits2Bonds, the first platform to fuse molecular simulations with machine learning – accelerating the discovery of polymer carriers for therapeutic RNA.
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NewsAI powers discovery of new CBLB inhibitor ISM3830
Insilico Medicine has announced ISM3830, an AI-designed CBLB inhibitor that has demonstrated promising preclinical results.
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OpinionMaking science run at the speed of thought: the reality of AI in drug discovery – Part 2
Can automation and AI finally make science run at the speed of thought? Eric Ma shares how disciplined systems, not new models, will drive the next wave of discovery.
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ArticleFast, scalable free energy prediction with nonequilibrium switching
Nonequilibrium switching (NES) offers a faster, more scalable way to predict how strongly drugs bind to their targets. By replacing slow equilibrium simulations with rapid, parallel transitions, NES delivers accurate free energy predictions at speed.
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ArticleAI and policy reform set to reshape UK drug development
BCG’s Chris Meier outlines how advances in AI and new UK policies could accelerate drug development, streamline clinical trials and strengthen the country’s life sciences sector.
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ArticleMaking science run at the speed of thought: the reality of AI in drug discovery – Part 1
Everyone talks about AI speeding up drug discovery, but Eric Ma explains why, without clean data and statistical discipline, it can actually do the opposite.
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ArticleDeep data not big data
Bigger isn’t always better. In drug discovery, Dr Michael Ritchie argues that the future belongs not to those with the most data, but to those who understand its biological depth.
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ArticleAI and the future of biomarker analysis in early R&D
AI is transforming biomarker analysis in early drug discovery, revealing hidden biological patterns that improve target discovery, patient selection and trial design for more precise and predictive R&D.
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NewsNew framework enhances reliability of virtual cell models
Shift Bioscience have announced new research revealing that AI-driven virtual cell models perform far better than previously thought when assessed with correctly calibrated metrics.
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NewsScientists use AI to create antibodies entirely from scratch
Scientists at the University of Washington’s Institute for Protein Design have used artificial intelligence to create antibodies entirely from scratch, a breakthrough that could reshape drug discovery.
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ArticleInside ELRIG Drug Discovery 2025: automation, AI and human-relevant models
At ELRIG’s Drug Discovery 2025, Drug Target Review spoke with the teams turning big ideas into usable tools – automation, AI and biology – that help scientists work smarter.