Technology – Page 5
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ArticleAccessible automation may change your day-to-day sooner than you think
Automation is fast and precise, but too often expensive and hard to use. Now modular, DIY tools are breaking down barriers and putting lab automation in every researcher’s hands.
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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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ArticleWhy scientists are targeting the gut to treat peanut allergy
A new oral immunotherapy could change how peanut allergy is treated, targeting the gut to retrain the immune system and reduce the risk of life-threatening reactions. INP20’s nanoparticle technology promises a safer, more precise approach that could replace lifelong avoidance with lasting tolerance.
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ArticlePDX models are back – and they’re exposing what cell lines missed
As cancer drugs continue to fail in translation, researchers are turning back to patient-derived xenograft (PDX) models – this time with better science. Could they be the missing link between the lab and the clinic?
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ArticleBetter assays: the key step in moving drugs from lab to clinic
From gene therapy to Long Covid, better assays are helping researchers move promising drug candidates from early studies into clinical trials. Dr Alexandre Lucas explains the technologies, challenges and innovations driving this progress.
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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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ArticleLab of the future: four technologies to watch
From precision proteomics to AI-powered immune profiling, next-generation laboratory technologies are changing how new therapies are discovered and developed. Here are four innovations set to shape the lab of the future - and the future of drug discovery.
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ArticleAI meets human tissue to fast-track precision medicine development
By combining human tissue models with explainable AI, researchers can analyse complex patient data to identify which treatments work best for which patients. First applied to inflammatory bowel disease, this approach could improve clinical trial success rates across many diseases.
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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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ArticleInside the search-and-develop model tackling 1,000 untreated skin diseases
With over 1,000 skin diseases lacking approved treatments, a search-and-develop model is changing how new therapies are sourced and developed. Chief Scientific Officer, Jacob Pontoppidan Thyssen, outlines the strategy behind it.
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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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ArticleGene therapies that listen and respond: the power of RNA regulation
Most gene therapies rely on static DNA promoters to control gene activity, but nature uses far more sophisticated tools. Dr Matthew Dale explores how harnessing RNA-level control could enable treatments that sense and respond in real time, offering unprecedented precision and safety.
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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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ArticleWhat if drug discovery took months, not decades?
Drug discovery is slow, costly and often unsuccessful. DTR hears how GATC Health is applying AI and multiomics to make the process faster, more precise and less reliant on trial and error.
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ArticleChallenges in developing robust potency assays for ADCs
Developing robust potency assays for Antibody-Drug Conjugates (ADCs) is crucial for ensuring their clinical success, but designing assays that meet both technical and regulatory standards is challenging. Here, Abzena’s CSO Campbell Bunce explores the complexities of assay development and the importance of ensuring accuracy, consistency and regulatory alignment for ADCs ...
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ArticleBeyond the hype: a veteran’s honest assessment of AI in drug discovery - Part 1
An interview with Thibault Géoui reveals why this technology wave might finally break through pharma’s productivity crisis – and why it will take longer than 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.