This session will explore the critical need for standardised approaches to automate patient matching to cancer clinical trials, a space currently lacking formal protocols. The discussion will begin with an overview of existing initiatives tackling this challenge, such as the NCI Clinical Trial Matching Program (US), PMATCH (Canada), ACTIN (EU), GEARBOx (US, pediatric context), and EOSC4Cancer (EU), comparing their methodologies and highlighting key differences between adult and paediatric contexts.

Key stakeholders from patient advocacy, computational biology, machine learning, pharmaceutical companies, predictive biomarker research, and clinical leadership will be invited to share insights on integrating electronic health records, genomic data, and eligibility criteria. Tools like ONCOLINER, OncoKB, and CKB, which aim to standardise variant and biomarker reporting, will be examined for their applicability in supporting such protocols. This session will aim to identify opportunities for GA4GH to develop standards in clinical trial matching for cancer and set the stage for ongoing discussions through a potential meeting series. The conversation may also address innovative approaches, including preclinical animal models, to advance predictive capabilities and accelerate trial enrollment.  The session will also incorporate a rare disease (RD) perspective, recognising the complementary challenges both cancer and RD domains face in clinical trial matching. While both fields emphasise the critical role of patient-trial matching, RD research often relies on unique considerations, such as N-of-1 trials and smaller, highly specific patient cohorts. The discussion will highlight the shared need for standardised representation of patient profiles and trial criteria, essential for effective management and matching across both domains. With the growing use of generative AI in addressing these challenges, insights from both fields can inform the development of robust, adaptable standards.