{"ID":2824571,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2601.03277","arxiv_id":"2601.03277","title":"MixRx: Predicting Drug Combination Interactions with LLMs","abstract":"MixRx uses Large Language Models (LLMs) to classify drug combination interactions as Additive, Synergistic, or Antagonistic, given a multi-drug patient history. We evaluate the performance of 4 models, GPT-2, Mistral Instruct 2.0, and the fine-tuned counterparts. Our results showed a potential for such an application, with the Mistral Instruct 2.0 Fine-Tuned model providing an average accuracy score on standard and perturbed datasets of 81.5%. This paper aims to further develop an upcoming area of research that evaluates if LLMs can be used for biological prediction tasks.","short_abstract":"MixRx uses Large Language Models (LLMs) to classify drug combination interactions as Additive, Synergistic, or Antagonistic, given a multi-drug patient history. We evaluate the performance of 4 models, GPT-2, Mistral Instruct 2.0, and the fine-tuned counterparts. Our results showed a potential for such an application,...","url_abs":"https://arxiv.org/abs/2601.03277","url_pdf":"https://arxiv.org/pdf/2601.03277v1","authors":"[\"Risha Surana\",\"Cameron Saidock\",\"Hugo Chacon\"]","published":"2025-12-28T05:37:56Z","proceeding":"q-bio.OT","tasks":"[\"q-bio.OT\",\"cs.AI\",\"cs.CL\",\"cs.LG\"]","methods":"[\"Large Language Model\",\"Language Model\"]","has_code":false}