Patrick Wu1,2, Scott D Nelson1,3, Juan Zhao1, Cosby A Stone4, QiPing Feng5, Qingxia Chen1,6, Eric A Larson7, Bingshan Li8,9, Nancy J Cox9,10, C Michael Stein5,10,11, Elizabeth J Phillips11,12,13, Dan M Roden1,10,11, Joshua C Denny1,14, Wei-Qi Wei1. 1. Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA. 2. Medical Scientist Training Program, Vanderbilt University School of Medicine, Nashville, Tennessee, USA. 3. HealthIT, Vanderbilt University Medical Center, Nashville, Tennessee, USA. 4. Division of Allergy, Pulmonary and Critical Care Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA. 5. Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA. 6. Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA. 7. Department of Medicine, University of South Dakota Sanford School of Medicine, Sioux Falls, South Dakota, USA. 8. Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA. 9. Vanderbilt Genetics Institute, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA. 10. Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA. 11. Department of Pharmacology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA. 12. Division of Infectious Diseases, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA. 13. Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, Tennessee, USA. 14. All of Us Research Program, National Institutes of Health, Bethesda, Maryland, USA.
Abstract
OBJECTIVE: We developed and evaluated Drug-Drug Interaction Wide Association Study (DDIWAS). This novel method detects potential drug-drug interactions (DDIs) by leveraging data from the electronic health record (EHR) allergy list. MATERIALS AND METHODS: To identify potential DDIs, DDIWAS scans for drug pairs that are frequently documented together on the allergy list. Using deidentified medical records, we tested 616 drugs for potential DDIs with simvastatin (a common lipid-lowering drug) and amlodipine (a common blood-pressure lowering drug). We evaluated the performance to rediscover known DDIs using existing knowledge bases and domain expert review. To validate potential novel DDIs, we manually reviewed patient charts and searched the literature. RESULTS: DDIWAS replicated 34 known DDIs. The positive predictive value to detect known DDIs was 0.85 and 0.86 for simvastatin and amlodipine, respectively. DDIWAS also discovered potential novel interactions between simvastatin-hydrochlorothiazide, amlodipine-omeprazole, and amlodipine-valacyclovir. A software package to conduct DDIWAS is publicly available. CONCLUSIONS: In this proof-of-concept study, we demonstrate the value of incorporating information mined from existing allergy lists to detect DDIs in a real-world clinical setting. Since allergy lists are routinely collected in EHRs, DDIWAS has the potential to detect and validate DDI signals across institutions.
OBJECTIVE: We developed and evaluated Drug-Drug Interaction Wide Association Study (DDIWAS). This novel method detects potential drug-drug interactions (DDIs) by leveraging data from the electronic health record (EHR) allergy list. MATERIALS AND METHODS: To identify potential DDIs, DDIWAS scans for drug pairs that are frequently documented together on the allergy list. Using deidentified medical records, we tested 616 drugs for potential DDIs with simvastatin (a common lipid-lowering drug) and amlodipine (a common blood-pressure lowering drug). We evaluated the performance to rediscover known DDIs using existing knowledge bases and domain expert review. To validate potential novel DDIs, we manually reviewed patient charts and searched the literature. RESULTS: DDIWAS replicated 34 known DDIs. The positive predictive value to detect known DDIs was 0.85 and 0.86 for simvastatin and amlodipine, respectively. DDIWAS also discovered potential novel interactions between simvastatin-hydrochlorothiazide, amlodipine-omeprazole, and amlodipine-valacyclovir. A software package to conduct DDIWAS is publicly available. CONCLUSIONS: In this proof-of-concept study, we demonstrate the value of incorporating information mined from existing allergy lists to detect DDIs in a real-world clinical setting. Since allergy lists are routinely collected in EHRs, DDIWAS has the potential to detect and validate DDI signals across institutions.
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