Article

Benchmarking Large Language Models for Predicting Therapeutic Antisense Oligonucleotide Efficacy

2026-02-19

Abstract excerpt

Antisense oligonucleotides (ASOs) are a promising class of therapeutic drugs that can target and modulate genes associated with various diseases. This study benchmarks Large Language Models (LLMs) for predicting ASO therapeutic efficacy through a two-stage approach: (1) molecular embedding-based fine-tuning using SMILES representations, and (2) prompt engineering with zero-shot and few-shot learning using DNA sequ...

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Literature Corpus work: 790fcb36-4492-5b2c-b235-1f5f1c5da941
DOI: 10.64898/2026.02.17.706455

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