Danny Burke, CEO of ecancer, shared on LinkedIn:
“Ecancer is a media partner of the upcoming 15th Tumour Models Summit London: How can the latest tumour models accelerate translational success in oncology?
From improving preclinical predictability to strengthening confidence in clinical decision-making, the right model can make all the difference.
Join experts at the 15th Tumour Models Summit London to discuss:
- Next-generation in vitro and in vivo tumour models
- Advancing patient-derived and organoid platforms
- Improving translational relevance in oncology Randamp;D
- Enhancing preclinical study design and data quality
- Accelerating oncology drug development pipelines
– 2nd – 3rd December 2026
– London, UK.”
Improve Reproducibility, Manage Costs, and Accelerate Timelines Through Selecting and Combining Tumour Models to Deliver Novel Targets, Faster Insights and Stronger Clinical Translation
The 15th Tumour Models Summit London is Europe’s longest-standing and most comprehensive meeting dedicated to advancing preclinical and translational tumour modelling.
As oncology pipelines become increasingly dependent on immunotherapies, cell therapies, ADCs, radioligand therapies, and precision medicines, development teams face growing pressure to improve translational confidence, identify predictive models, and generate decision-grade evidence earlier in development.
Join leaders from Roche, AstraZeneca, Johnson and Johnson, Eli Lilly, Immunocore, Merck, MolecularPartners, ImmunoKey, and innovative oncology biotechs to explore how human-relevant models, NAMs, AI-enabled approaches, patient-derived systems, biomarkers, tumour microenvironment models, and integrated development strategies can improve candidate selection, predict clinical outcomes, and reduce late-stage attrition.
Whether your focus is model validation, safety prediction, tumour microenvironment biology, translational biomarkers, AI-driven prediction, or regulatory strategy, this is the industry’s definitive forum for improving oncology model translatability.