Conversational AI integrating precision oncology data improved patient understanding of genomic results, enhanced communication confidence, and increased engagement with clinical trials.
Does a Conversational AI-Patient Advocacy framework improve understanding and engagement in populations at risk for cancer?
A Conversational AI-Patient Advocacy framework integrating precision oncology data may improve patient understanding and engagement in at-risk populations.
Abstract Background: Populations at risk for colorectal and other cancers continue to face barriers to equitable healthcare, including limited health literacy, fragmented communication, and underrepresentation in genomic research. Traditional approaches to patient engagement often overlook cultural and linguistic variety, leaving many patients without the knowledge or tools to fully participate in their care. To address this gap, we developed a Conversational AI-Patient Advocacy framework designed to help patients understand, access, and benefit from precision oncology in a personalized informed way. Methods: Built upon our validated AI-HOPE ecosystem, which has been successfully implemented and tested across several precision oncology research applications, this innovative platform functions as a digital patient advocate that integrates insights from the AACR Project GENIE database—a global cancer registry linking clinical and genomic data from all populations. Using natural language processing and explainable AI, the system translates complex cancer related questions into accessible, plain-language explanations, supports patient comprehension of diagnostics and treatment options, and connects users to advocacy and educational resources. The framework emphasizes empathy-driven dialogue, cultural adaptability, and accessibility for all populations, including those historically underrepresented in precision medicine. Results: Preliminary implementation using GENIE-derived datasets enabled population-level insights into cancer mutation patterns that were then translated into conversational narratives for patients. Early testing demonstrated improved understanding of genomic results, enhanced confidence in patient-provider communication, and increased engagement with advocacy resources and clinical trial information. Conclusions: Conversational AI-Patient Advocacy represents a new paradigm for virtual patient advocacy, combining patient education with precision oncology insights derived from large-scale databases like AACR GENIE. By acting as a virtual advocate, this technology empowers patients to navigate their care journey with clarity and trust—bridging the gap between complex cancer data and actionable understanding for all populations. Citation Format: Araceli Estrada, Brigette Waldrup, Francisco G. Carranza, Sophia Manjarrez, Enrique Velazquez-Villarreal. Empowering populations at risk through conversational artificial intelligence: a framework for patient advocacy and precision oncology abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 6.
Estrada et al. (2026) studied this question. Conversational AI integrating precision oncology data improved patient understanding of genomic results, enhanced communication confidence, and increased engagement with clinical trials.