All Informatics articles – Page 6
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WebinarOptimizing antibody leads in early drug discovery with key developability insights
Stop costly biologic failures. This masterclass reveals high-throughput strategies to optimize antibody leads upfront.
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ArticleNext-generation drug design: how generative AI can tackle undruggable targets
Generative AI is broadening the boundaries of what is possible in drug discovery. In this article, Murat Tunaboylu, CEO and Co-founder of Antiverse, reveals how the zeitgeist technology is enabling scientists to tackle previously undruggable targets like GPCRs and ion channels to deliver patient impact faster.
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ArticleWhat SLAS 2025 really told us about drug discovery
Forget the buzzwords - SLAS 2025 showed what’s genuinely driving progress in drug discovery: usable AI, collaborative platforms and tools that solve real problems.
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ArticleHow AI and LLMs are transforming drug discovery: part 2
As AI reshapes scientific work, two founders debate how best to build tools scientists can trust — should we embed expertise into the model or the team? From agent-powered labs to hypothesis-generating machines, the future of drug discovery is being reimagined right now.
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ArticleAI at the forefront of age-related disease treatment
The body undergoes changes with age that can lead to conditions like sarcopenia and osteoarthritis, burdening individuals and healthcare systems. Find out how Rejuvenate Biomed uses AI to decode ageing biology and develop combination therapies targeting the root causes of age-related diseases, offering hope for better treatments and quality of ...
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NewsK Navigator: an AI co-pilot transforming biomedical research
K Navigator, a new AI-powered research co-pilot, is set to transform biomedical science by helping researchers explore complex data and accelerate discoveries.
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ArticleUsing knowledge graphs in drug discovery (Part 2): how they’re shaping scientific progress
In this second interview of the series, Andreas Kolleger, Head of GenAI Innovation at Neo4j, discusses how knowledge graphs and AI are transforming scientific discovery and improving life sciences workflows.
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ArticleUsing knowledge graphs in drug discovery (Part 1): how they link to large language models
In this first interview of a two-part series, Andreas Kolleger explores the convergence of knowledge graphs and large language models. As the head of GenAI innovation at Neo4j, Andreas brings a unique cross-industry perspective on how these technologies can enhance life sciences workflows.
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NewsAI designs peptides for 'undruggable' diseases
A new AI-powered approach is tackling the challenge of 'undruggable' diseases by designing peptides that can bind to and destroy previously untreatable proteins.
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NewsThe Pistoia Alliance: key findings on AI
Results from Pistoia Alliance’s Lab of the Future survey has shared important findings about the challenges life science companies face.
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WebinarOvercoming critical challenges in AI-driven drug discovery
The increasing use of AI in the life science field marks a pivotal point in history. Although AI is now an indispensable tool in drug discovery, promising to save vast amounts of time and money, there are still many hurdles scientists encounter. This webinar will explore these challenges and offer ...
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ArticlePart three: pragmatic guidelines to getting the best out of LLMs
There have been a slew of announcements over the past few months from AI-led biotechs around the potential of Large Language Models (LLM) in early drug discovery. In the third of a three-part series, Dr Raminderpal Singh presents some pragmatic guidelines for scientists in accessing and obtaining value from LLMs. ...
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ArticleKickstarting the use of AI for biotechs: part two
Traditional wet lab scientists working on target discovery, drug identification and drug optimisation have an opportunity to catch up with their AI-enabled peers – but why should they, and how? In this article – the second of a three-part series – Dr Raminderpal Singh touches on methods that are being ...
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WebinarSAFIRE: AI predicted ADME for drug discovery: leveraging BioPrint
Join Dr Carleton Sage to learn about predicting ADME properties as a key approach to improving the efficiency of small molecule drug discovery. AI ADME model development approaches and case studies within drug discovery projects will be discussed.
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News
Novel prediction tool accurately determines disease stage
A new learning-based framework enables patients and caregivers to predict the timing of any of the five clinical groups of AD development.
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WhitepaperWhitepaper: Targeting kinases in the innate immune response
The guide provides examples of how Transcreener allowed rapid assay development to enable screening for kinases in innate immune pathways.
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WhitepaperCase Study: Target discovery for rheumatoid arthritis
Learn more about Euretos computational disease model and how it predicts many of the known drug targets for RA.
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Whitepaperebook: Maximizing preclinical confidence in target efficacy and safety
This ebook outlines Euretos’ approach to target discovery and indication expansion. Whilst also discussing data-driven target selection.
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WebinarTurning Plans into Reality: Real Examples of Custom Automation Projects
Watch our industry experts to learn about the tangible benefits and best practice of custom flow cytometry automation projects. You’ll discover how to reduce your challenges implementing tailored automation, controlling the quality of the data produced and improving the reliability of your data acquisition.
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NewsNew computational tool may fuel vaccine development
La Jolla biologists harness machine learning and computational tools to make sense of immune system data.