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Clinical Implementation of Pharmacogenomics and Drug-Drug Interaction Screening in a German Academic Teaching
Roman Tremmel1,2, Filippa Schreeck1,2, Simon Jaeger1,2,3
1Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany.
Abstract:
Pharmacogenomics (PGx) helps to explain variability in drug response, including adverse drug reactions. Functional variants in genes affecting drug absorption, distribution, metabolism, and excretion (ADME) have been described. Despite PGx guidelines (e.g., CPIC and DPWG) enabling genotype-guided drug and dose selection, preemptive implementation remains challenging due to various issues including standardized result communication and integration into electronic health record (EHR) systems. We implemented PGx testing as well as drug-drug interaction (DDI) screening in a German academic hospital and assessed their impact on physicians, general practitioners (GPs), and patients. A novel PGx workflow was established using a 60-genetic variant panel. CPIC/DPWG guideline-based PGx reports were integrated into the EHR system and provided as a mobile and web application for patients through a genetic information system. Medication profiles and questionnaires evaluated PGx-based decisions 3 months post-discharge. Among 255 patients, 95% had at least one actionable PGx variant, most commonly affecting statins, 5-fluorouracil, irinotecan, and pantoprazole. Actionable recommendations were provided in 21.5%, with hospital physicians modifying treatment subsequently in 75.5%. We identified 57 clinically significant DDIs, including PGx drugs in 21%. GPs maintained optimized treatment in 77% of those patients with a medication change initiated during hospitalization. One in 10 patients discussed results with their GPs. GPs favored PGx for future prescriptions and requested training. We showed that preemptive PGx testing can be successfully implemented in a German hospital with high acceptance among physicians and GPs, and that PGx integration into the EHR supports broader adoption in precision medicine.
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