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Abstract ID 128897 Poster Board 253 Author: Deepika Khedekar, MPharm, Independent Researcher Affiliations: Centralized Clinical Lead, IQVIA Focus Area: Cancer Pharmacology, Clinical Pharmacology Background: The landscape of cancer clinical trials faces daunting challenges, with a notable 95% failure rate driven by multifaceted barriers including trial access, recruitment difficulties, engagement issues, funding disparities, and a significant underrepresentation of minority populations. This complex backdrop is compounded by the critical bottleneck of participant recruitment, where approximately 70% of cancer trials experience significant delays or fail to find participants and less than five percent of adult cancer patients participate in cancer trials.Given the annual global toll of 10 million cancer-related deaths and the current success rate of merely 5% in the oncology trials, there is an urgent need for a comprehensive strategy to elevate participation rate in oncology trials–a need the CancerEngage model aims to fulfill. Objective: This study aims to systematically examine the barriers to trial access and participant enrollment in cancer trials through an extensive review of existing literature and opinion articles. It proposes the CancerEngage model, designed to address these critical issues. Methods: I conducted an exhaustive literature review focusing on research papers and opinion pieces from clinical research professionals, oncology experts, and trial sponsors. This review identified key barriers impeding access and enrollment in cancer trials. In response, I developed CancerEngage, which incorporates eight strategic pillars tailored to bridge these gaps, utilizing a blend of emerging technologies and methodological innovations. The pillars are outlined as follows: The Pillars of the CancerEngage Model: Modernization of Trial Criteria: Broadening eligibility criteria to encompass a wider array of patients, thereby enhancing trial inclusivity. Dedicated Trials for Older Patients: Developing trials specifically designed for the unique needs and conditions of older patients to ensure their adequate representation and to study the efficacy of treatments across diverse age groups. Promotion of Diversity in Clinical Trials: Instituting mandatory diversity benchmarks to guarantee trials reflect the demographic composition of the broader population, aiming for equitable representation of all racial and ethnic groups. AI-Driven Human-In-Loop Trial Awareness: Employing artificial intelligence with a human-in-the loop model to create and distribute customized, culturally and linguistically tailored trial information, improving engagement across diverse populations. Drone Distribution of Trial Materials: Utilizing drone technology to deliver trial materials to hard-to-reach areas, overcoming geographical barriers to trial information dissemination and expanding the reach of cancer trial programs. Virtual Reality (VR) for Trial Familiarization: Implementing VR simulations to provide prospective participants with a realistic preview of trial processes, aimed at reducing trial-related anxiety, building trust, and increasing enrollment. Mobile Trial Units: Deploying mobile units to rural and underserved areas to facilitate on-site trial participation, significantly expanding trial access. Patient Centricity: Integrating patient feedback and preferences into trial design and execution, ensuring trials are patient-friendly and responsive to participant needs. Results: The literature review elucidated significant barriers to cancer trial participation, leading to the development of CancerEngage. While acknowledging limitations–such as the varying applicability of the model's pillars across different trial contexts–the proposed model emphasizes the potential of collaborative efforts to overcome these challenges. Preliminary feedback suggests that CancerEngage could significantly enhance trial accessibility, diversity, and participant engagement rates. Conclusion: CancerEngage represents a pivotal shift towards addressing the longstanding challenges of cancer trial participation. By foregrounding technological innovation and patient-centric methodologies, the model offers a promising avenue to boost participation rates, thereby expediting cancer research and the development of new treatments. This model not only holds the potential to transform oncology trials but also serves as a blueprint for broader clinical trial reform. Future endeavors will focus on the model's implementation across clinical research organizations and the evaluation of its impact on overcoming participation barriers. Conflict of Interest Statement: No conflicts of interest to declare.
Deepika Khedekar (Mon,) studied this question.