Discover tools and techniques supporting modern drug discovery, including assays, biomarkers, sequencing, molecular modelling, analytical technologies and translational research methods that improve target validation, therapeutic development, data generation and scientific decision-making.
From uncovering new drug targets to predicting human toxicity, organ chips are showing what they could bring to drug discovery. Professor Donald Ingber of Harvard University discusses where the technology is heading next.
From early research to quality control, maintaining analytical continuity is no easy task. Could a single sequencing workflow help simplify analytical assessment?
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.
Non-animal methods are already used throughout early drug discovery, yet animal testing continues to dominate regulatory safety assessment. Recent initiatives suggest change is coming, but significant scientific and practical challenges remain.
As drug developers pursue increasingly complex therapies, traditional bioanalytical approaches are being put to the test. How is the field adapting to meet these new demands?
By combining CRISPR knock-in with small peptide tags, researchers can study proteins in their native cellular context, generating more predictive data for translational drug discovery.
Studying individual cells has revolutionised biomedical research, but it doesn’t tell the whole story. Discover how spatial biology is revealing disease mechanisms with implications for biomarkers, immunotherapy and drug development.
Static cultures can miss critical immune–tumour interactions. Learn how the Mera™ flow-based human tissue model better captures T-cell activity to strengthen preclinical immunotherapy research.
Researchers at Cardiff University have identified urolithin A – a compound produced by gut bacteria during the metabolism of substances found in pomegranates – as a new approach for treating cardiovascular disease.
In part two of our AACR 2026 coverage, industry leaders were focussed on how the field is no longer constrained by data generation or molecular design, but by the challenge of connecting systems, standardising workflows and ensuring biological insights.
Traditional preclinical models are struggling to keep pace with a new generation of targeted therapies. As regulators embrace new approach methodologies (NAMs), vascularised tissue platforms are offering a more human-relevant approach to predicting drug efficacy and safety.
Researchers at Phenomix Sciences are using machine learning and genetic risk scoring to investigate emotional hunger, an obesity phenotype linked to emotional and reward-driven eating behaviours. Dr Timothy O’Connor discusses how the approach could improve patient stratification, obesity research and treatment selection.
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.
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.
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.
At AACR 2026, industry leaders discussed how oncology R&D is moving beyond isolated technological advances towards integrated discovery systems.
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.
Carterra’s new 48-channel SPR platform reimagines throughput, automation and data quality for modern discovery workflows.
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.
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.