Background Response to antidepressant therapy is highly variable among individuals. Pharmacogenomic (PGx) testing presents an opportunity to guide drug selection while optimizing therapy outcomes and/or decreasing the risk for toxicity. Case presentation A patient with multiple comorbidities, including severe major depressive disorder (MDD), experienced adverse drug events and undesirable response to multiple antidepressant medications (i.e., bupropion, escitalopram, and venlafaxine). A clinical pharmacist assessed significant drug-gene, drug-drug, and drug-drug-gene interactions as well as other clinical factors to provide recommendations for antidepressant therapy optimization. Conclusion This case highlights the importance of PGx testing and the key role of pharmacists in identifying and mitigating drug-related problems and optimizing drug therapy in patients with MDD.
Pharmacogenomic (PGx) information can guide drug and dose selection, optimize therapy outcomes, and/or decrease the risk of adverse drug events (ADEs). This report demonstrates the impact of a pharmacist-led medication evaluation, with PGx assisted by a clinical decision support system (CDSS), of a patient with multiple comorbidities. Following several sub-optimal pharmacotherapy attempts, PGx testing was recommended. The results were integrated into the CDSS, which supported the identification of clinically significant drug–drug, drug–gene, and drug–drug–gene interactions that led to the phenoconversion of cytochrome P450. The pharmacist evaluated PGx results, concomitant medications, and patient-specific factors to address medication-related problems. The results identified the patient as a CYP2D6 intermediate metabolizer (IM). Duloxetine-mediated competitive inhibition of CYP2D6 resulted in phenoconversion, whereby the patient’s CYP2D6 phenotype was converted from IM to poor metabolizer for CYP2D6 co-medication. The medication risk score suggested a high risk of ADEs. Recommendations that accounted for PGx and drug-induced phenoconversion were accepted. After 1.5 months, therapy changes led to improved pain control, depression status, and quality of life, as well as increased heart rate, evidenced by patient-reported improved sleep patterns, movement, and cognition. This case highlights the pharmacist’s role in using PGx testing and a CDSS to identify and mitigate medication-related problems to optimize medication regimen and medication safety.
Pharmacotherapy for major depressive disorder (MDD) typically consists of trial-and-error and clinician preference approaches, where patients often fail one or more antidepressants before finding an optimal regimen. Pharmacogenomics (PGx) can assist in prescribing appropriate antidepressants, thereby reducing the time to MDD remission and occurrence of adverse drug events. Since many antidepressants are metabolized by and/or inhibit cytochrome P450 enzymes (e.g., CYP2C19 or CYP2D6), drug-induced phenoconversion is common in patients on antidepressant combinations. This condition influences the interpretation of a patient’s PGx results, overall risk of ineffective/adverse medication response due to multi-drug interactions, and the recommendations. This complex case describes a patient with MDD, generalized anxiety disorder, and chronic pain who experienced a fall due to excessive sedation following a prescribing cascade of fluoxetine, bupropion, and doxepin. These antidepressants delivered a significant additive sedative effect and interacted with the patient’s hydrocodone, potentially contributing to uncontrolled pain, upward dose titration of hydrocodone, and a higher overall sedative burden. The PGx results and drug-induced phenoconversion described in this case report explain the patient’s excessive sedation and possibly ineffective/toxic antidepressant and opioid treatment. This case report also illustrates how a more timely multi-drug interaction assessment (preferably in conjunction with preemptive PGx testing) may have informed a different prescribing pattern, reduced/avoided a prescribing cascade, and potentially prevented a drug-related fall.
The opioid epidemic in the United States has exposed the need for providers to limit opioid dispensing and identify at-risk patients prior to prescribing opioids. With pharmacogenomic testing, clinicians can analyze hundreds of medications-including commonly prescribed opioids-against genetic results to understand and predict risk and response. Moreover, knowledge of genotypic variants and altered function can help decrease trial and error prescribing, identify patients at-risk for adverse drug events, and improve pain control. This patient case demonstrates how pharmacogenomic test results identified drug-gene interactions and provided insight about a patient's inadequate opioid therapy response. With pharmacogenomic information, the patient's healthcare team discontinued opioid therapy and selected a more appropriate regimen for osteoarthritis (ie, celecoxib), resulting in improved pain control and quality of life.
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