All Artificial Intelligence & Computational Tools articles – Page 2
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NewsScripta Therapeutics raises $12m to advance neurodegenerative research
Oxford-based techbio start-up Scripta Therapeutics has announced a $12 million seed funding round helping them to reshape conventional drug discovery.
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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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ArticleInside ELRIG Drug Discovery 2025: automation, AI and human-relevant models
At ELRIG’s Drug Discovery 2025, Drug Target Review spoke with the teams turning big ideas into usable tools – automation, AI and biology – that help scientists work smarter.
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ReportLab Automation: Where Discovery Scales
Automation now plays a central role in discovery. From self-driving laboratories to real-time bioprocessing, this report explores how data-driven systems improve reproducibility, speed decisions and make scale achievable across research and development.
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ArticleFrom 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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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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ArticleThe 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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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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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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NewsNon-invasive method images brain development in juvenile mice
Stanford researchers have developed a non-invasive method to make juvenile mice’s skin transparent, allowing repeated imaging of developing neural circuits. The breakthrough could be used to develop new treatments for neurodevelopmental disorders.
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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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ArticleConsumables 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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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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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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ArticleWhy smarter financial planning could be key to clinical trial success
Effective financial management is vital for clinical trial success, yet many preclinical and clinical companies face inefficiencies due to outdated systems. Jennifer Kyle, CEO of Condor Software, explains how advanced financial platforms can streamline processes, improve forecasting and ensure better resource allocation throughout drug development.
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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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ArticleFixing drug discovery’s most persistent problem with AI
AI will not replace drug discovery, but it might finally fix one of its most frustrating bottlenecks. Read how a targeted approach to ADMET is cutting through the noise.
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ArticleSolving the disconnect between lab and data scientists: part 2
As the lab–data science divide continues, Ian Kerman looks ahead to a future of deeper collaboration – one where shared skills, smarter tools and a shift in mindset could finally break down the barriers. In this second interview, he shares his vision, practical ideas and advice for the next generation ...
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ArticleThe next phase of the multiomics evolution, powered by AI
Genomics laid the foundation for precision medicine, but on its own, it offers only part of the picture. This article explores how integrated multiomics can provide the deeper biological context needed to drive more effective therapies forwards.
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