The first ESMO guidance for AI-based biomarkers
In a newly released framework paper, ESMO defines criteria for assessing and implementing AI-based biomarkers in oncology
Ma: “We all need more than one mentor”
For Prof. Brigette Ma, dealing with diversity and finding opportunities in criticisms are essential to grow as oncology professionals
Artificial intelligence as a reliable research partner
Extensive research is focusing on the development of tools that may enhance drug development and personalised oncology in the near future
AI may be key to streamline patient allocation to clinical trials
As a proof of concept, an AI-powered large language model matching platform shows promise in patient selection
How AI is expediting clinical research: the use of synthetic real-world data
While synthetic real-world data may help overcome current challenges in clinical trials, it also introduces new complexities
Rethinking the limits of tissue-agnostic cancer therapy
The promises of a tumour-agnostic oncology are still challenged by conventional clinical trial design and regulatory processes
Optimising cancer therapy in the era of technological progress
Findings from latest research reflect emerging opportunities in oncology to refine treatments by challenging current paradigms of care
Novel tissue-agnostic biomarker approaches could improve response to immunotherapy
Several studies describe pan-cancer approaches utilising the latest technology for better patient selection and outcomes
Change is on the horizon in the management of uveal melanoma
Novel strategies are offering the possibility of extended patient survival and durable disease control
Innovative strategies lead to mixed benefits for rare cancers
Positive findings are presented for advanced Merkel-cell carcinoma plus phaeochromocytoma and paragangliomas, while negative findings are equally important to guide future research