arXiv · 2606.14031
Applicability Condition Extraction for Therapeutic Drug-Disease Relations
Abstract
Identifying conditions that a certain drug takes therapeutic effect on a target disease is crucial for clinical decision-making support. However, most existing biomedical information extraction methods have focused on identifying only relations between drugs and diseases, while largely overlooking the context-specific conditions where such relations can apply. To address this problem, we introduce the task of applicability condition extraction for therapeutic drug-disease relations from biomedical research literature. We create the first dataset that has manually annotated triples of drugs, diseases, and applicability conditions on biomedical paper abstracts with 1,119 drug-disease pairs. Using this dataset, we systematically evaluate the performance of a range of existing methods. In addition, we propose a new method that enhances LoRA to consider relations between drugs and diseases. Our method consistently outperforms strong baselines across different evaluation settings.
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Guanting Luo, Noriki Nishida, Yuji Matsumoto, Yuki Arase. 2026-06-12. Applicability Condition Extraction for Therapeutic Drug-Disease Relations. https://arxiv.org/abs/2606.14031
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