Objectives: Pharmacogenetic (PGx) testing identifies variations in genes that help predict efficacy, risk of side effects, and appropriate doses of certain medications. Evidence-based guidelines from the Clinical Pharmacogenetic Implementation Consortium (CPIC) facilitate the application of PGx testing in clinical practice. Antiemetics, NSAIDs, and opioids, which are metabolized via cytochrome p450 enzymes, are commonly prescribed medications for gynecologic oncology patients. This study aimed to evaluate the prescribing rate for medications impacted by PGx variants by gynecologic oncologists. Methods: The study design was a cross-sectional retrospective review. The electronic medical record was queried for unique prescriptions orders placed by gynecologic oncologists at a single academic institution for CPIC level A/B medications between July 15, 2018- July 14, 2021. The frequencies of actionable phenotypes for PGx genes were estimated using the European phenotype frequencies provided by CPIC. The projected prevalence of drug-gene interactions (DGI) was estimated by multiplying prescription drug counts by phenotype frequencies. Results: A total of 10,624 patients were treated by the gynecologic oncology service and 86% were ordered at least one CPIC level A medication. The top five CPIC level A medications were ondansetron (n=6807, 64%), ibuprofen (n=5815, 55%), omeprazole (n=1929, 18%), tramadol (n=1450, 14%), and lansoprazole (n=1395, 13%). The top drug classes impacted by PGx were antiemetics (64%), NSAIDs (63%), proton pump inhibitors (PPIs) (44%) and opioids (14%). DGIs projected to have clinical consequence include: ibuprofen/CYP2C9 (n=989, 9%), ondansetron/CYP2D6 (n=204, 2%), omeprazole/CYP2C19 (n=136, 1%), lansoprazole/CYP2C19 (n=98, 1%) and tramadol/CYP2D6 (n=87, 1%). Additionally, 1015 patients with genetic results were identified in the Penn Medicine BioBank for further clinical follow-up to assess efficacy and adverse drug reactions. Conclusions: CPIC level A medications are commonly prescribed for gynecologic oncology patients. Implementation of multi-gene panels containing CYP2D6, CYP2C9, and CYP2C19 for the guidance of commonly prescribed antiemetics, analgesics, and PPIs would be of greatest benefit in this population. Further research is necessary to evaluate side effects and drug responses for patients with PGx variants in this patient population. Objectives: Pharmacogenetic (PGx) testing identifies variations in genes that help predict efficacy, risk of side effects, and appropriate doses of certain medications. Evidence-based guidelines from the Clinical Pharmacogenetic Implementation Consortium (CPIC) facilitate the application of PGx testing in clinical practice. Antiemetics, NSAIDs, and opioids, which are metabolized via cytochrome p450 enzymes, are commonly prescribed medications for gynecologic oncology patients. This study aimed to evaluate the prescribing rate for medications impacted by PGx variants by gynecologic oncologists. Methods: The study design was a cross-sectional retrospective review. The electronic medical record was queried for unique prescriptions orders placed by gynecologic oncologists at a single academic institution for CPIC level A/B medications between July 15, 2018- July 14, 2021. The frequencies of actionable phenotypes for PGx genes were estimated using the European phenotype frequencies provided by CPIC. The projected prevalence of drug-gene interactions (DGI) was estimated by multiplying prescription drug counts by phenotype frequencies. Results: A total of 10,624 patients were treated by the gynecologic oncology service and 86% were ordered at least one CPIC level A medication. The top five CPIC level A medications were ondansetron (n=6807, 64%), ibuprofen (n=5815, 55%), omeprazole (n=1929, 18%), tramadol (n=1450, 14%), and lansoprazole (n=1395, 13%). The top drug classes impacted by PGx were antiemetics (64%), NSAIDs (63%), proton pump inhibitors (PPIs) (44%) and opioids (14%). DGIs projected to have clinical consequence include: ibuprofen/CYP2C9 (n=989, 9%), ondansetron/CYP2D6 (n=204, 2%), omeprazole/CYP2C19 (n=136, 1%), lansoprazole/CYP2C19 (n=98, 1%) and tramadol/CYP2D6 (n=87, 1%). Additionally, 1015 patients with genetic results were identified in the Penn Medicine BioBank for further clinical follow-up to assess efficacy and adverse drug reactions. Conclusions: CPIC level A medications are commonly prescribed for gynecologic oncology patients. Implementation of multi-gene panels containing CYP2D6, CYP2C9, and CYP2C19 for the guidance of commonly prescribed antiemetics, analgesics, and PPIs would be of greatest benefit in this population. Further research is necessary to evaluate side effects and drug responses for patients with PGx variants in this patient population.