The strongest disease signal may not point to the best drug target. AI could help researchers identify what matters within complex biological networks.
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.
PacBio and AI drug discovery company TychoBio are generating full-length RNA datasets from more than 10,000 samples to train AI models and accelerate the development of RNA therapies for rare diseases.
Three leading scientists in protein science, structural biology and AI will headline the Protein Sciences in Drug Discovery conference at GSK Stevenage in November 2026, exploring advances in AI-driven drug design, native mass spectrometry and membrane protein folding.
Experimental synaptic restoration compound tazbentetol has demonstrated neuroprotective effects in the retinas of diabetic mice, offering a potential new therapeutic avenue for diabetic retinal neuropathy ahead of detectable vascular damage.
Penn State researchers have shown that inhibiting the protein VPS34 increases GD2 display on neuroblastoma cell surfaces, making tumours more visible to anti-GD2 antibodies and improving outcomes in preclinical combination studies.
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.