Evaluating Cancer Drug-Targeting Pathways with Large Language Models

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Evaluating Cancer Drug-Targeting Pathways with Large Language Models

Ayla Zhang and Jake Y. Chen, The University of Alabama, USA

Abstract

Integrating artificial intelligence into drug discovery holds great potential for prioritizing therapeutic targets. This study presents a novel framework combining bioinformatics tools and AI-driven evaluations to streamline target identification. Using pancreatic adenocarcinoma (PAAD) as a case study, we analyzed 252 candidate genes and associated pathways derived from the PAGER database. ChatGPT-4o evaluated pathways by scoring them across seven categories using structured prompts and weighted criteria to ensure robustness.

Keywords

Pancreatic adenocarcinoma, drug target validation, ChatGPT-4o evaluation framework, oncology drug development

Full Text : https://aircconline.com/csit/papers/vol14/csit150405.pdf
Abstract URL: https://aircconline.com/csit/abstract/v15n04/csit150405.html
Volume URL : https://airccse.org/csit/V15N04.html

#chatgpt #artificialintelligence #largelanguagemodels #database #naturallanguageprocessing
Category
Oncology
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