From bispecific to multispecific antibodies: a highly promising field
Development of therapies modulating two or more targets is increasing rapidly despite facing a number of hurdles
Redesigning oncology clinical trials with agentic AI
Semi-autonomous and autonomous foundation models are helping cancer research and anticancer drug development
Data show how ESMO’s scales and recommendations can guide the optimisation of outcomes in patients with targetable mutations
In two studies, the use of ESCAT matching and ESMO recommendations for germline assessment lead to effective targeted treatment
What is the way forward for undruggable tumour targets?
2026 ESMO TAT Honorary Awardee, Prof. Timothy A. Yap, sees a bright future ahead for novel synthetic lethal strategies, driven by advances in technology and novel biomarkers
A driving force to accelerate drug development
Fostering academic clinical research is one of the ESMO’s priorities, and artificial intelligence may be a major driver
Tailored combinations of tools are the way forward to assess quality of life in rare cancers
Recent studies emphasise that the current approach does not fully capture the needs and experiences of patients with rare tumours
How to close the age gap in clinical cancer research?
From geriatric assessment to artificial intelligence, an ESMO/SIOG paper highlights effective strategies to improve the representation of older patients in clinical trials
Trustworthy and explainable AI – a key to equitable oncology?
Mitigating research biases by rigorous data analysis and validation can pave the way for a wider adoption of artificial intelligence in cancer care
RAS inhibition: a game changer in pancreatic cancer?
Preclinical findings show antitumour activity of triple KRAS inhibition in mouse models, but it will take years of rigorous research to assess its clinical efficacy in oncology patients
Cancer Research
Rethinking the immunotherapy paradigm for a sustainable and equal cancer care
Dose optimisation of immune checkpoint inhibitors may help address current healthcare resource constraints and improve treatment access