Clinical trials are crucial for advancing cancer treatments and improving patient outcomes. As cancer treatment has become more tailored to individual patients, oncological clinical trials have become increasingly complex. AI-assisted clinical trial screening holds great potential. The time required for eligibility determination by AI-based clinical trial matching system was 2 hours versus manual reviewers at 150 hours. In 2019, the Clinical Trial Navigation (CTN) Program was designed in collaboration with people with lived experience (PWLE) to resolve the gap in navigating the search for cancer clinical trials. As of 2023, the CTN program doubled the rates of referral to trials at the Windsor Regional Hospital. To optimize this program, ongoing efforts are focused on expediting the processes within CTN including consideration of use of AI. The proposed study will compare AI programs versus the ongoing CTN program in terms of clinical trial matching. If successful, the results can be used to eventually integrate AI in CTN processes.
Integrating AI into clinical trial matching is essential to expedite the process, resulting in improved patient outcomes and satisfaction. Through this study, we aim to compare the current CTN clinical trial matching to an AI generated matching system. This study will focus on the comparative ability of AI and the CTN manual program, in terms of individualized trial generation and matching among patients with HER2 positive breast cancer and sarcoma. By integrating AI, the CTN program has the ability to up-scale in response to increased demand.
