Abstract 6: Empowering populations at risk through conversational artificial intelligence: a framework for patient advocacy and precision oncology.

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.

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Journal
Cancer Research
Published
2026-04-03
DOI
https://doi.org/10.1158/1538-7445.am2026-6
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Abstract 6: Empowering populations at risk through conversational artificial intelligence: a framework for patient advocacy and precision oncology.

Sophia Manjarrez, Brigette Waldrup, Enrique I. Velazquez-Villarreal, Francisco G. Carranza et al.
Cancer Research
Artificial Intelligence in Healthcare and Education
article

Abstract 6: Empowering populations at risk through conversational artificial intelligence: a framework for patient advocacy and precision oncology.

Sophia Manjarrez, Brigette Waldrup, Enrique I. Velazquez-Villarreal, Francisco G. Carranza, Araceli Estrada
article en

Abstract

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.

Cancer ResearchVol. 86(7_Supplement)
City Of Hope National Medical Center (US), City of Hope (US), Maryland State Arts Council (US)
Quality Education
Openalex Percentile: Top 31%
Artificial Intelligence in Healthcare and Education
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