{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Keat K"],"funding":["NCATS NIH HHS","NHLBI NIH HHS","NHGRI NIH HHS"],"pagination":["229-246"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11734741"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["30"],"pubmed_abstract":["Pharmacogenetics represents one of the most promising areas of precision medicine, with several guidelines for genetics-guided treatment ready for clinical use. Despite this, implementation has been slow, with few health systems incorporating the technology into their standard of care. One major barrier to uptake is the lack of education and awareness of pharmacogenetics among clinicians and patients. The introduction of large language models (LLMs) like GPT-4 has raised the possibility of medical chatbots that deliver timely information to clinicians, patients, and researchers with a simple interface. Although state-of-the-art LLMs have shown impressive performance at advanced tasks like medical licensing exams, in practice they still often provide false information, which is particularly"],"journal":["Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing"],"pubmed_title":["PGxQA: A Resource for Evaluating LLM Performance for Pharmacogenomic QA Tasks."],"pmcid":["PMC11734741"],"funding_grant_id":["K23 HL143161","U24 HG010615","U24 HG013077","F31 HG013246","T32 HG000046","UL1 TR001878"],"pubmed_authors":["Keat K","Kim D","Tuteja S","Whirl-Carrillo M","Huang Y","Klein TE","Sangkuhl K","Gong L","Venkatesh R","Li B","Kumar R","Ritchie MD"],"additional_accession":[]},"is_claimable":false,"name":"PGxQA: A Resource for Evaluating LLM Performance for Pharmacogenomic QA Tasks.","description":"Pharmacogenetics represents one of the most promising areas of precision medicine, with several guidelines for genetics-guided treatment ready for clinical use. Despite this, implementation has been slow, with few health systems incorporating the technology into their standard of care. One major barrier to uptake is the lack of education and awareness of pharmacogenetics among clinicians and patients. The introduction of large language models (LLMs) like GPT-4 has raised the possibility of medical chatbots that deliver timely information to clinicians, patients, and researchers with a simple interface. Although state-of-the-art LLMs have shown impressive performance at advanced tasks like medical licensing exams, in practice they still often provide false information, which is particularly","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025","modification":"2026-06-01T17:54:56.499Z","creation":"2026-04-08T14:25:43.673Z"},"accession":"S-EPMC11734741","cross_references":{"pubmed":["39670373"],"doi":["10.1142/9789819807024_0017"]}}