All Machine Learning (ML) articles
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InterviewFrom scientist to bioinformatician: how AI coding tools dissolved the activation energy barrier
A biotech CEO with decades of scientific experience but sporadic coding practice gained practical bioinformatics capabilities in six weeks using AI coding assistants.
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NewsNew AI-designed T-cell engager LGTX-101 to be presented at AACR in San Diego
LabGenius Therapeutics will present preclinical data for LGTX-101, its AI-designed Nectin-4 x CD3 T-cell engager, at AACR 2026 in San Diego.
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NewsELRIG announces keynote speakers for Advances in Cell-based Screening 2026 in Gothenburg
ELRIG has announced the keynote speakers for its 2026 Advances in Cell-based Screening conference in Gothenburg, where scientists will gather to explore how human-first models, advanced cell biology and AI are changing the future of drug discovery.
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NewsNew target found for glaucoma treatment
Scientists have discovered that specialised immune cells in the eye help keep its drainage system clear and regulate pressure, which could inform new treatments for glaucoma.
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NewsNew AI tool could accelerate drug discovery and cut lab costs
Scientists have developed a machine learning system that can predict how complex chemical reactions will produce the correct molecular form for medicines.
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InterviewHow self-driving labs are changing drug development
Automation and artificial intelligence are changing how scientists design, test and refine new molecules. At the University of Toronto, Stuart R Green and the Acceleration Consortium are building a self-driving lab that could change the pace of early drug discovery.
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ArticleInternational Women’s Day: digital pathology in early drug discovery
For International Women’s Day, Dr Amanda Hemmerich, Global Director of Digital Pathology & Innovation at IQVIA Laboratories, describes how digital pathology is being applied in early drug development and what it takes to build credibility in a multidisciplinary technical field.
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ArticleWhy most labs are not ready for AI: Cenevo shares what must change
Most labs want to use AI, but few have the digital foundations to support it. Cenevo’s leaders explain why progress is slow and what laboratories must fix before AI can deliver real value.
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ArticleMaking immunotherapy safer and more accessible through continuous digital monitoring
Immunotherapies such as CAR-T are extending survival, yet reliance on inpatient monitoring for cytokine release syndrome continues to restrict access. This article explores how continuous digital monitoring and AI-driven analysis could enable safer outpatient delivery and support more scalable immunotherapy adoption.
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ArticleThe map and compass: integrating BD&L early to de-risk drug discovery
In drug discovery, great science alone is not enough because commercial viability ultimately decides which programmes survive and attract partners. This Q&A explores how integrating Business Development and Licensing (BD&L) from the earliest stages can guide R&D strategy, sharpen decisions and de-risk the path to market.
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NewsInsilico and MSK partner on AI research for gastroesophageal cancer
A new research collaboration between Insilico Medicine and Memorial Sloan Kettering Cancer Center aims to harness generative AI technology to identify novel therapeutic targets for gastroesophageal cancers.
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NewsNew OC-PAM AI tool tracks cancer organoid drug response
Scientists have developed an AI-enhanced imaging platform that enables non-invasive, label-free and longitudinal monitoring of cancer organoids and spheroids.
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OpinionAI in drug discovery: predictions for 2026
As AI drug discovery enters 2026, the industry faces a pivotal year of clinical tests, regulatory clarity, and market consolidation. Here, Dr Raminderpal Singh examines where AI is delivering measurable gains in early discovery, where hype outpaces reality and why Phase III results will determine whether the technology can truly ...
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ArticleAI begins to enter Alzheimer’s drug discovery pipelines
Artificial intelligence is increasingly used to analyse large, multimodal Alzheimer’s datasets and inform target discovery and trial design. A new JPAD special issue highlights how these methods are moving from experimentation towards practical application in drug discovery.
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NewsNew paper warns against phasing out animal testing too quickly
A push by the US Food and Drug Administration to phase out animal testing in drug development could improve efficiency and reduce animal suffering, but experts warn that moving too quickly may pose risks to patient safety.
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Article2026: the year AI stops being optional in drug discovery
AI is moving from a supporting role into the core of drug discovery. By 2026, it is expected to shape how targets are chosen, how biology is analysed and how development decisions are made.
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Newsinsitro expands AI drug discovery with CombinAbleAI acquisition
insitro has acquired Israeli AI therapeutics company CombinAbleAI and launched its TherML platform, creating an end-to-end, modality-agnostic system for designing small molecules, antibodies, oligonucleotides and other complex biologics.
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NewsNew study revives long-doubted target for depression drugs
Researchers have shown that changing the molecular structure of NK1 receptor antagonists may restore antidepressant effects after decades of failed trials.
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ArticleAI steps into drug safety: predicting liver injury earlier than ever before
Drug-induced liver injury remains one of drug development’s most costly pitfalls. Now, AI and transcriptomics may offer a way to spot risks long before they reach patients.
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NewsSchrödinger partners with Lilly TuneLab on AI drug discovery
Schrödinger has announced a collaboration with Eli Lilly’s TuneLab platform, integrating advanced AI-driven drug discovery workflows into its LiveDesign enterprise informatics system.