[ARTIFICIAL INTELLIGENCE-ASSISTED LITERATURE REVIEW: A CASE STUDY IN FUMARATE HYDRATASE-DEFICIENT RENAL CELL CARCINOMA].

Abstract

Introduction: Fumarate hydratase-deficient renal cell carcinoma (FHdRCC) is a rare and aggressive form of kidney cancer that presents significant therapeutic challenges. Due to its rarity, treatment decisions often rely on comprehensive literature reviews to identify potential therapeutic options. This article presents a case of a 37-year-old patient with metastatic FHdRCC who showed partial response to Nivolumab but experienced persistent lymphatic involvement and symptoms requiring ongoing intervention. The clinical team sought to evaluate alternative combination therapies through a literature review. Elicit, an AI-powered research assistant, was employed to structure the literature review process through an automated analysis of scientific papers. This case served as a test of Elicit's capabilities in synthesizing treatment options for rare cancers, compared to traditional research methodologies. The platform demonstrated significant limitations in its search capabilities due to restricted database access. However, it showed efficiency in analyzing provided papers and organizing clinical data by key categories. These findings suggest that while Elicit may serve as a helpful support tool for literature analysis, it is best used as a complement to traditional search methods, with careful verification of its output by clinical experts. Disclosures: Dolev Vaknin, Or Degany, Rotem Sisso-Avron, and Prof. Sharon Einav are employed by Medint Medical Intelligence, which conducted the literature review that served as the basis for this paper.