Stability problems can derail promising biologics late in development. Bringing high-throughput testing earlier into discovery could help researchers identify risks before they become costly failures.
AI agents promise to transform drug discovery, but where do they really add value? Dr Eric Ma examines search, model choice, vendor lock-in and why scientific expertise matters more than ever.
A drug can form exactly the complex it was designed to make and still fail to work. Two recently approved induced proximity drugs show why what happens after complex formation – not formation alone – can decide the outcome.
Agentic AI, ultralarge virtual screening, molecular glues and human-relevant models were among the key developments in early drug discovery during Q3 2026. Drug Target Review examines what changed, why it matters and what to watch heading into Q4.
Researchers at Albert Einstein College of Medicine have identified a cellular recycling pathway whose age-related decline allows senescent ‘zombie’ cells to evade immune clearance.
A new machine learning-based platform called MALVINA measures bacterial invasion, intracellular accumulation and DNA damage at single-cell resolution, exposing infection dynamics that conventional assays cannot detect.
ELRIG Drug Discovery 2026 returns to ExCeL London for its 20th year, with AI, automation and advanced cell models among the technologies set to feature across the two-day programme.
Researchers at the University of Birmingham have identified the P2X7 receptor as a key driver of neuroinflammation in human brain tissue, raising the prospect of repurposing existing therapies to treat various brain conditions.
As sequencing continues to grow in importance across biotherapeutic discovery and development, where can it make the biggest impact and how can fragmented workflows be overcome?
Five leading cancer researchers from across genomics, proteomics, cell biology, chemical biology and gene therapy dig into what’s driving cancer drug discovery forward and what’s still holding progress back.
AI agents promise to transform drug discovery, but where do they really add value? Dr Eric Ma examines search, model choice, vendor lock-in and why scientific expertise matters more than ever.