All Computational Techniques articles – Page 3
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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.
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ArticleThe 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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ArticleMaking 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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NewsAI designs new antibiotics to take on drug-resistant superbugs
Penn engineers have built an AI model that creates new antibiotics – and early tests show some work as well as existing approved drugs.
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ArticleAnimal-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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ArticleBeyond the hype: a veteran’s honest assessment of AI in drug discovery – Part 3
AI is starting to transform drug discovery, but progress is still slow and big challenges remain. Thibault Géoui explores the gaps, hurdles and breakthroughs needed before it can truly change pharma R&D.
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ArticleBeyond the hype: a veteran's honest assessment of AI in drug discovery - Part 2
Thibault Géoui explains why AI could finally help pharma overcome its productivity crisis and why the payoff won’t come as quickly as the optimists claim.
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NewsStriosomes may hold the key to better treatments for mental disorders
Scientists have developed a new computational model that reveals how the striosomal compartment of the brain’s striatum influences decision-making – which could lead to improved therapies for psychiatric disorders.
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ArticleHow 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.
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ArticleFixing failed drugs: AI solutions for toxicity in drug discovery – part 3
What role could large language models and AI agents play in drug safety? In Part 3, Layla Hosseini-Gerami of Ignota Labs discusses how emerging technologies might make toxicity analysis faster, more accessible and part of the drug discovery workflow from day one.
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NewsNew AI model PROTsi identifies aggressive tumours using protein markers
Researchers in Brazil and Poland have developed an AI-powered tool that predicts cancer aggressiveness by analysing protein expression - offering new insights into tumour behaviour.
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ArticleFixing failed drugs: AI solutions for toxicity in drug discovery – part 2
Why do so many drug candidates fail before reaching patients – and can AI help stop the losses? In Part 2, Layla Hosseini-Gerami of Ignota Labs outlines the scope of the toxicity problem and explains why failures often come too late to fix.
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ArticleFixing failed drugs: AI solutions for toxicity in drug discovery – part 1
Why do so many drug candidates fail before reaching patients – and can AI help stop the losses? In Part 1, Layla Hosseini-Gerami of Ignota Labs outlines the scope of the toxicity problem and explains why failures often come too late to fix.
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ArticleWhat single cells are revealing about brain disorders
Single-cell and spatial technologies are giving researchers an unprecedented view of how brain diseases like Alzheimer’s really work. The result? Faster discovery, clearer targets and a new path towards more effective treatments.
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NewsVirtual cell model rankings just got a major upgrade
Shift Bioscience has published a new study introducing enhanced metrics and baselines for evaluating virtual cell models - boosting gene target discovery and accelerating its rejuvenation therapeutics pipeline.