All Computational Techniques articles – Page 3
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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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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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NewsDeepTarget tool helps identify secondary cancer drug targets
A new computational tool, DeepTarget, is demonstrating context-specific targets and repurposing opportunities, showing that what may be a side effect in one patient could serve as a treatment in another.
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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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NewsZuckerberg's Biohub announces AI-powered biology to accelerate drug discovery
The initiative combines cutting-edge artificial intelligence with large-scale biological data, with the aim to transform how new treatments, drugs and therapies are developed.
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NewsAlzheimer’s may disrupt fat tissue and raise metabolic disease risk
Researchers have discovered that Alzheimer’s may disrupt communication between nerves and blood vessels in fat tissue which could explain why people with Alzheimer’s are often diagnosed with heart disease and metabolic problems.
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NewsRNA folding: new model could change future drug design
A Japanese research team has simulated how RNA molecules fold, using cutting-edge computational tools to model complex structures with accuracy – a breakthrough that could accelerate the development of RNA-based medicines and therapies.
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NewsHow 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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ArticleHow 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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ArticleChemistry-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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NewsCloneSeq-SV: new blood test tracks ovarian cancer recurrence
Researchers have developed a new blood test method, CloneSeq-SV, that tracks treatment-resistant ovarian cancer cells over time. The approach could help predict recurrence and guide targeted therapies.
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ArticleBeyond 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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ArticleFrom data to therapy: emerging tech driving cancer drug discovery
Multiomics, AI and liquid biopsies are giving researchers real-time insight into tumour biology and enabling more personalised cancer therapies. Find out how these technologies are advancing biomarker discovery, improving patient stratification, and guiding the design of new treatments.
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ArticleInside 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.