All High-Throughput Screening (HTS) articles
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NewsInsilico launches specialist AI models for drug discovery chemistry
Insilico Medicine has unveiled a suite of compact, domain-trained AI models targeting ADMET prediction, retrosynthesis and target activity across GPCR and kinase panels, claiming state-of-the-art results on more than 70 benchmarks.
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ArticleSix assay requirements every researcher using NAMs should know
As NAMs become more widely used in drug discovery, assays must meet the demands of more complex models. Discover six requirements for reliable, reproducible and biologically meaningful data.
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ArticlePROTACs vs molecular glues: which degrader fits your target?
PROTACs and molecular glues can both remove disease-associated proteins, but choosing between them is not simple. Our new Discovery Toolkit compares the options to help discovery teams choose the right strategy.
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NewsStem cell-grown kidney organoids could help uncover new treatments for AKI
Researchers at Monash University have grown miniature human kidneys from stem cells that could give drug discovery teams a more human-relevant model for investigating acute kidney injury and identifying therapies that promote tissue recovery.
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Article600+ patient-derived cancer models expand the search for drug targets
Hundreds of new patient-derived cancer models could strengthen target validation, identify cancer vulnerabilities and provide more representative systems for preclinical drug discovery.
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NewsMulti-target screening refines ADC development for cervical cancer
A large-scale transcriptomic study has pinpointed distinct cell-surface targets for antibody-drug conjugate development across cervical cancer subtypes, revealing how tissue-of-origin comparisons and subpopulation analysis can uncover targets missed by conventional screening approaches.
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ArticleWhy intracellular targets remain a major drug discovery challenge – and how they’re becoming druggable
Many biologically important intracellular targets remain difficult to drug. Dr Rab Prinjha examines how screening within living cells could help tackle them.
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NewsAI identifies experimental drug targeting undruggable cancer protein
Mayo Clinic researchers have used AI to screen nearly 40,000 compounds and identify a small molecule inhibitor targeting GIPC1, a protein previously considered undruggable, with preclinical results showing slowed tumour growth and enhanced chemotherapy response.
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NewsAI and genetics identify WNK2 inhibitor for osteoarthritis treatment
Researchers at University of Utah Health have used artificial intelligence and human genetic data to identify a promising early-stage drug candidate targeting WNK2, a protein linked to inherited osteoarthritis, with the lead compound reducing inflammatory gene activity and supporting cartilage cell health in laboratory models.
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NewsNew molecular glue platform broadens E3 ligase targeting for cancer drug development
Researchers at Dana-Farber Cancer Institute have developed a scalable platform for discovering molecular glue degraders, reporting the first metabolically activated example and broadening the scope of targeted protein degradation in cancer.
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NewsResearchers develop AI system to accelerate tuberculosis drug discovery
Researchers at Texas A&M have developed AI-driven platforms to help scientists navigate the bottlenecks of tuberculosis drug discovery, from eliminating nuisance compounds to unlocking years of archived research data.
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NewsTumour organoids may expand access to targeted cancer drugs
Two studies from Weill Cornell Medicine demonstrate that patient-derived tumour organoids can accurately replicate cancers long-term and incorporate immune microenvironments, offering new potential for personalised treatment selection.
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NewsAI and lab techniques accelerate tuberculosis drug discovery
Researchers at UMass Amherst have combined high-throughput laboratory screening with an AI neural network to identify compounds capable of breaching the protective outer membrane of Mycobacterium tuberculosis, potentially accelerating the search for new TB therapeutics.
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NewsFish-inspired sensor detects heartbeat of lab-grown cardiac organoids
A biomechanical well plate inspired by the pressure-sensing lateral line of fish can wirelessly monitor the pulse of multiple lab-grown cardiac organoids simultaneously, offering a scalable new platform for cardiovascular drug testing.
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ArticleAntibody recycling, FcRn and the next generation of biologics
One receptor can protect antibodies from degradation, extend their half-life and become a drug target itself. Explore the science behind FcRn and how researchers measure its function.
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NewsLabGenius and LG Chem partner on AI-driven cancer antibodies
LabGenius Therapeutics has partnered with LG Chem to develop next-generation multispecific antibodies targeting solid tumours. The collaboration combines AI-driven drug discovery with oncology development expertise to identify therapeutics with improved selectivity and reduced toxicity.
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NewsResearchers develop automated DESI-MS platform for faster cancer drug discovery
Scientists at Purdue University have created an automated ultrahigh-throughput platform that integrates chemical synthesis, biological testing and mass spectrometry into a single workflow, potentially reducing the time needed to identify promising cancer drug candidates from weeks to hours.
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NewsGinkgo Bioworks launches ADME-One platform for early-stage screening
Ginkgo Bioworks has launched ADME-One, an integrated platform combining high-throughput ADME testing with AI-powered human pharmacokinetic projections.
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ArticleOne sample. One shot. The pressure on sample preparation in drug discovery
In drug discovery, a failed sample run is not just a setback – it can mean months of lost work and significant cost. At Analytica 2026, three Eppendorf experts explain how the right tools, workflows and mindset are changing that.
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ArticleTurning CRISPR hits into confident drug discovery decisions
Functional genomics is central to modern drug discovery, yet high attrition rates persist. In this article, Dr Salman Tamaddon-Jahromi, a postdoctoral research associate at the University of Cambridge, discusses how end-to-end CRISPR screening strategies, iPSC-derived neuronal models and layered quality control can convert functional genomics signals into actionable therapeutic hypotheses.