The right signals can make or break an organoid model. From growth and differentiation to downstream drug testing, cytokines and growth factors are critical to creating cultures researchers can rely on.
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 gene responsible for producing a critical enzyme in inflammatory signalling has been identified after more than 30 years, with findings suggesting the pathway acts as both an immune alarm and a cellular shield with implications for cancer, IBD and asthma.
A hybrid microrobotic platform combining living bacteria, nanoparticles and targeted chemotherapy has achieved 82.4 percent tumour inhibition in preclinical bladder cancer models.
From self-driving laboratories to advanced cellular models, ELRIG Drug Discovery 2026 showcases technologies helping researchers generate better data, evaluate drug candidates and improve early discovery.
Researchers at Nagoya University have identified BCAT1, an enzyme involved in proline supply for collagen synthesis, as a potential target for reducing cardiac fibrosis following myocardial infarction.
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.