Tools and techniques
Tools and techniques
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Tools and techniques
ArticleBeyond tangles: why soluble intracellular tau should guide drug discovery
Tau tangles are a hallmark of Alzheimer’s disease and related disorders, but evidence suggests the real damage may come from rare, soluble tau species inside neurons. Targeting these hidden drivers of circuit dysfunction could be key to restoring memory and cognition.
ArticleWhy AI models need patient data to deliver in drug discovery
Despite rapid advances in AI, many drug discovery models still struggle to translate computational predictions into clinical outcomes. Thomas Clozel explains how Owkin is training AI on large-scale patient-derived data while integrating experimental and clinical validation directly into model development.
ArticleWhen antibiotics are not enough: the case for immune-engaging therapies
As antimicrobial resistance grows and patient populations become more complex, the limitations of antibiotics are becoming harder to ignore. Dr Helen Bright, CSO at Centauri Therapeutics, discusses a new approach that targets both the pathogen and the host.
ArticleAACR 2026 part 1: AI design, precision biology and the next wave of oncology innovation
At AACR 2026, industry leaders discussed how oncology R&D is moving beyond isolated technological advances towards integrated discovery systems.
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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.
ArticleWhen scale meets insight: reinventing SPR for the future of drug discovery
Carterra’s new 48-channel SPR platform reimagines throughput, automation and data quality for modern discovery workflows.
ArticleWhy lower organisms matter for neurodegeneration drug discovery
In the wake of recent government policy aimed at actively replacing animal models in drug discovery, we consider a possible solution to the translational shortfalls of current cellular methodologies for neurodegenerative disease.
ArticleAnalytica 2026: Connecting data across drug discovery workflows
Drug discovery is generating more data than ever, but the challenge is making sure that data is reliable, connected and usable. At Analytica 2026 in Munich, Drug Target Review spoke with technology developers and industry leaders across the exhibition floor to understand how these challenges are being addressed.
ArticleAI builds dual-action cancer drug targeting PKMYT1
Research published in Nature Communications shows how generative AI can be used to design complex dual-action cancer drug candidates. Insilico Medicine has developed a PKMYT1 degrader that both eliminates the target protein and blocks its activity, demonstrating the growing role of AI in advanced drug discovery.
ArticleImproving selectivity in antibody–drug conjugates
Promatix Biosciences is developing a new generation of bispecific antibody–drug conjugates using proprietary membrane proteomics data to identify highly selective target pairings. CEO Dr Michael Hunter explains how the company’s TXPro database enables discovery of previously unexplored tumour biology to improve therapeutic index and reduce on-target/off-tumour toxicities in solid tumours.
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.
ReportOrganoids and Organ Chips: Improving Decision-Making in Early Drug Discovery
Early drug discovery has no shortage of models, but predicting what will translate to patients remains difficult. This report examines how organoids, organ-on-chip systems and imaging technologies are used to measure drug response, analyse resistance mechanisms and assess how well findings reflect clinical outcomes in human-relevant models.
ArticleThe scale divide: competing strategies in AI drug discovery
Two approaches to AI in preclinical drug discovery are diverging, from multi-thousand GPU systems to models with only a handful of parameters, with early results raising questions about which will deliver.
ArticleBeyond serendipity: rational design and AI’s expansion of the undruggable target landscape
For decades, drugging the ‘undruggable’ was thought to require luck rather than logic. Today, AI is transforming serendipity into strategy by enabling rational, data-driven approaches to previously inaccessible targets.
ArticleOperational data: the hidden driver of faster drug discovery
The key to faster, smarter drug discovery lies in data that’s often overlooked. By exposing hidden delays and inefficiencies, this data enables teams to shorten discovery cycles and progress promising candidates faster.
ArticleFrom fragments to maps: scaling drug–target interaction data
Most drug–target data were never designed to be compared at scale. Pharmome mapping takes a different approach, building a shared dataset intended to support more predictable discovery.
ReportCRISPR & Genomics: Turning Data into Confident Drug Discovery Decisions
Early drug discovery has no shortage of genomic data, but confidence remains scarce. This report examines how CRISPR, functional genomics and human-relevant models are being applied to determine which signals matter, how they influence disease biology and which targets and strategies are worth pursuing.
InterviewComputational design drives new generation of synthetic promoters
Designing gene control from scratch is becoming possible. SynGenSys is using computational design to create synthetic promoters for advanced therapies.
InterviewPhysics-based modelling offers a new way to study drug targets
Australian start-up OmnigeniQ has demonstrated what it describes as the first deterministic, physics-based computation of a human protein in its native state.
ArticleAnticipating adaptation: understanding and overcoming cancer drug resistance
Neil Bhowmick explores how understanding the mechanisms of cancer drug resistance has reframed our approach to treatment, revealing containment and control as realistic goals for therapeutic strategies.