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New beta lab platform to streamline early-stage research
UK life science software company Lab Thread has launched the beta of its unified lab platform, designed to streamline research workflows.
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Research & Development
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Life 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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RNA that knows where to go: the rise of targeted delivery
What if RNA medicines could be guided directly to tumours, sparing healthy tissue and reducing side effects? Advances in targeted delivery are bringing that vision closer to reality.
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Making 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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AI 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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Transforming central labs with automation and AI: setting new standards for modern trials
Demands on central laboratories are consistently increasing, heightening the challenge to deliver operational excellence and the highest standard of scientific integrity with both speed and agility. ICON Laboratories is transforming the way we leverage data and intelligent operational models to meet evolving trial needs.
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AI 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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Nasal drug delivery: the non-invasive future of treatment
Advances in formulation science and device technology are transforming nasal drug delivery, enhancing absorption, stability and patient adherence. This article examines the innovations driving its growth and highlights future applications ranging from systemic treatments to nose-to-brain therapies and vaccines.
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Nuclera expands into Australasia with Solve Scientific partnership
Cambridge-based biotech firm Nuclera has partnered with Solve Scientific Australia to expand access to its eProtein Discovery™ System across Australia and New Zealand.
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Meta-Flux expands AI platform to speed up drug development
Dublin-based biotech Meta-Flux has raised €1.8M ($2M) in seed funding to expand its AI-driven platform for preclinical drug development, helping researchers predict drug success and accelerate the pathway from lab to clinic.
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Overcoming barriers to oncology combination therapies in the UK and EU
Colleagues at IQVIA discuss ways to expedite positive HTA outcomes for innovative combination therapies, alleviating the bottlenecks inherent in the current system.
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Making sense of AI: bias, trust and transparency in pharma R&D
AI is increasingly used in drug discovery, but hidden bias and ‘black box’ models threaten trust and transparency. This article explores how explainable AI can turn opaque predictions into clear, accountable insights.
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Animal-free drug discovery is closer with QSP
Quantitative Systems Pharmacology (QSP) is fast becoming a standard tool in drug development, offering a human-relevant way to predict drug effects before the clinic. Dr Josh Apgar of Certara explains how it is helping to cut reliance on animal testing and speed discovery.
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Consumables engineered for speed and reproducibility in drug discovery
What if familiar lab formats could be redesigned to remove the weak points in permeability and absorbance testing? This article explores how design choices in common consumables can improve both speed and reproducibility in early-stage research.
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How AI is quietly changing drug manufacturability
AI is moving beyond drug design to answer a critical question: can a promising compound actually be manufactured at scale? By predicting synthetic feasibility early, machine learning tools are helping drug developers avoid costly failures, streamline R&D and design molecules that are both effective and practical to produce.
