Pharmacist-Led Medication Evaluation Considering Pharmacogenomics and Drug-Induced Phenoconversion in the Treatment of Multiple Comorbidities: A Case Report

Abstract

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.

Identifikasi Gen Yang Berisiko Untuk Psoriasis Vulgaris Melalui Pemanfaatan Informasi Genomic

“…Mengimplementasikan farmakogenomik untuk mendukung dalam pengambilan keputusan perawatan kesehatan untuk membantu pasien mendapatkan manfaat dari obat yang dipersonalisasi. Dengan demikian, apoteker dapat mengenali risiko Adverse Drug Reaction (ADR) atau kegagalan pengobatan dan memberikan alternatif berdasarkan genetika pasien (Del Toro-Pagán et al, 2021;Shah and Smith, 2015).…”

Effect of CYP2D6, 2C19, and 3A4 Phenoconversion in Drug-Related Deaths

“…These variables may include age, weight, sex, diseases, food, and concurrent drug use. Taking drugs that modify effects (inhibition or induction) on DMEs may result in drug-drug interactions (DDIs) and drug–drug–gene interactions (DDGIs) [ 4 , 5 ]. It is noteworthy to mention that the inhibitory strength of some substances, whether strong or weak (e.g., olanzapine, cocaine, and lidocaine), is either controversial in the literature or only in vitro data are available.…”

“…However, individuals with gUM may be at risk of therapeutic failure due to excessive metabolism [ 9 ]. Consequently, a mismatch between genotype and phenotype may have serious implications in clinical settings and lead to patients receiving inadequate therapy [ 4 , 10 ].…”

The Evaluation of CYP2D6, CYP2C9, CYP2C19, and CYP2B6 Phenoconversion in Post-Mortem Casework: The Challenge of Forensic Toxicogenetics

“…The genotype–phenotype discrepancy might explain some inconsistencies that have been found within genotype-based association studies. Particularly, the use of concomitant medication might trigger drug–drug and drug–drug–gene interactions (DDGI), especially when taking drugs with inhibitory or inductive effects on DME [ 10 , 12 ], e.g., the co-consumption of paroxetine, a strong CYP2D6 inhibitor, and tamoxifen, a drug metabolised by the same DME [ 12 , 13 ].…”

“…It is known that, beyond genetic factors, drug metabolism can be also influenced by non-genetic factors such as sex, age, weight, physiological conditions or diseases, diet, and use of concomitant drugs. These factors account for the phenomenon of phenoconversion, that is, a mismatch between the genotype-based prediction of cytochrome P450-mediated Metabolites 2023, 13, 661 2 of 15 drug metabolism and the real metabolising capacity [7,10,11]. The genotype-phenotype discrepancy might explain some inconsistencies that have been found within genotypebased association studies.…”