Abstract 1823 Automating Aptamer Information Extraction Using Fine-Tuned GPT-4o Mini for the UTexas Aptamer Database

Aptamers are oligonucleotide sequences with specific target-binding affinities, offering significant potential in diagnostics, therapeutics, and drug delivery. The UTexas Aptamer Database provides a centralized repository for aptamer-related data, critical for advancing research in these fields. However, its current reliance on manual data extraction from scientific literature limits scalability and introduces inefficiencies. To address this, we aim to develop a fine-tuned Large Language Model (LLM) to automate literature parsing, accelerating database curation and enhancing research accessibility.