Hempstead

Researchers are investigating the use of an Artificial Intelligence-based tool to help match patients with advanced solid and blood cancers to appropriate clinical trials. This international registry study includes both adult and pediatric patients who have already been considered for clinical trial enrollment by their primary healthcare providers. The study aims to assess the feasibility, clinical usefulness, financial impact, and patient outcomes related to this AI-driven matching approach. The intervention involves a specialized software application that connects with existing electronic health records to extract and analyze individual patient data. This data is compared with a database of available clinical trials using machine learning algorithms to dynamically identify the best matches based on trial availability and patient characteristics. The study is observational and non-interventional, with treatment decisions made by the patients healthcare team supported by virtual tumor boards and AI reports. Data collection occurs every three months over about 36 months, including 24 months of patient enrollment and 12 months of follow-up. Participants will voluntarily enroll and continue receiving care as usual. Researchers will collect and analyze clinical data, biomarker information, and enrollment barriers to evaluate how many eligible patients actually enroll in trials and the impact on survival outcomes. The primary outcome is the proportion of patients eligible for versus actually enrolling in clinical trials, with secondary outcomes including overall survival, progression-free survival, and virtual tumor board use. The study plans to enroll over 50,000 patients worldwide to gather real-world evidence on this AI-assisted trial matching process.