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.
Genome-wide association studies have linked thousands of genetic variants to disease, yet most remain disconnected from drug-relevant biology. Neville Sanjana, Professor at New York University and Core Faculty Member at the New York Genome Center, explains how scalable CRISPR screens systematically link noncoding variants to causal genes and therapeutic targets.
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.
Rare neurological diseases remain one of the most challenging areas in drug discovery, with many patients still lacking treatment options. Dr Nitza Thomasson discusses returning to Servier to lead its rare neurology therapeutic area and explains why resilience, curiosity and persistence are essential for those looking to build a meaningful career in STEM.
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.
Dr Aaron Wenger reveals how improvements in long-read sequencing technology is enabling the elucidation of complex disease mechanisms for targeted and effective treatments for rare diseases.
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.
AI is accelerating drug discovery at an unprecedented pace. Thousands of antibody candidates can now be designed in silico within hours. The challenge now is keeping experimental workflows fast enough to keep up. High-throughput expression and integrated developability assessment are making it possible to move from sequence to data in days.
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.
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.
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.
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.
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.
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.
Designing gene control from scratch is becoming possible. SynGenSys is using computational design to create synthetic promoters for advanced therapies.
Australian start-up OmnigeniQ has demonstrated what it describes as the first deterministic, physics-based computation of a human protein in its native state.
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.
Research published in Clinical Lymphoma, Myeloma and Leukemia identifies Kappa Myeloma Antigen and Lambda Myeloma Antigen as highly selective immunotherapy targets across plasma cell dyscrasias.