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How AI and cell data combine to make drug discovery faster
Cellarity has published a new paper in detailing an AI-powered framework that integrates single-cell transcriptomics to make drug discovery faster and more successful.
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Artificial Intelligence
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From wild fungi to faster drug discovery
Nature’s pharmacy has yielded half of today’s medicines, yet most of its potential remains untapped. AI is now changing how quickly new therapies can be found.
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From war rooms to launch rooms: how AI is changing the game
Within3’s Jason Smith explores how artificial intelligence is breathing new life into next-generation launch situation rooms; delivering actionable insights for pharmaceutical companies.
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The predictive validity crisis: Pharma’s productivity paradox – Part II
Part II shows that the predictive validity crisis can be solved by rethinking how the industry chooses models, measures outcomes and integrates systems. Success stories from Vertex, Regeneron and AstraZeneca illustrate how aligning biology, measurement and strategy can reverse decades of declining productivity.
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How real-world data is accelerating drug discovery
Vish Srivastava considers the benefits of expanding the role of real-world data in drug discovery to provide improved therapies, faster and with greater success.
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Building reliable organoid models for human-relevant drug discovery
Organoids are changing the landscape of biomedical research, with automation and AI driving new levels of consistency, scalability and human relevance. Aaron Risinger of Molecular Devices discusses how these technologies are advancing precision medicine – and the challenges that remain.
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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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Chemistry-aware AI offers new routes in small molecule design
AI has advanced molecule design, yet synthetic feasibility remains a bottleneck. Chemistry-first approaches offer a practical way forward.
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The predictive validity crisis: Pharma’s productivity paradox – Part I
Drug discovery now costs 100 times more per FDA-approved drug than in 1950, despite vast advances in biology and computing. The core problem is the collapse of predictive validity in preclinical models, which sits at the heart of pharma’s productivity paradox.
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Eye movements as objective biomarkers: accelerating CNS drug development
Measuring disease progression remains one of the biggest hurdles in CNS drug development. Eye movements, now trackable with just a laptop and webcam, are emerging as a sensitive and scalable biomarker that could transform how trials are designed and therapies reach patients.
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Beyond templates: advancing protein–protein interaction structure prediction with AI
Dr Alan Nafiiev evaluates template-based, docking and template-free approaches to PPI prediction, highlighting how AI can enhance structural accuracy.
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Inside Zasocitinib: a new model for TYK2 inhibition in immune-mediated diseases
Zasocitinib is a highly selective, investigational TYK2 inhibitor developed to target immune-mediated diseases with fewer off-target effects than traditional JAK inhibitors. This article explores its mechanism, selectivity data and clinical progress.
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The science behind the systematic discovery of molecular glues
For decades, molecular glues have been stumbled upon rather than designed. A new scientific approach is now changing that – expanding what is considered druggable.
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Fibroblast mapping reveals potential universal drug targets
Scientists have mapped the diversity of fibroblasts and discovered how ‘rogue’ fibroblasts drive multiple diseases, revealing drug targets that could transform treatments across the body.
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ProRNA3D-single: new AI for drug discovery and disease research
Virginia Tech computer scientists have created a new AI tool, ProRNA3D-single, that can generate 3D models of how viral RNA binds to human proteins – a development that could speed up drug discovery.
