Clinical pharmacogenetics implementation consortium guideline (CPIC) for CYP2D6 and CYP2C19 genotypes and dosing of tricyclic antidepressants: 2016 update

Cost-effectiveness of pharmacogenetic screening in the management of major depressive disorder in the Spanish Healthcare System

BACKGROUND

Major depressive disorder (MDD) represents a sizable economic burden in Spain. Pharmacogenetic (PGx) screening to guide the choice of antidepressant medication (ADM) in MDD patients yields higher response and remission rates, which could reduce both healthcare and indirect costs.

METHODS

We built a cost-effectiveness probabilistic Markov model with microsimulation using Tree Age Pro 2022, simulating a patient cohort from the SNHS starting ADM for MDD, and comparing PGx screening before starting ADM versus no screening (No PGx). We carried out a probabilistic sensitivity analysis using the Monte Carlo simulation with microsimulation, set for 1000 iterations and 1000 microsimulation trials, both from societal and healthcare provider perspectives, for a time horizon of 3 years.

RESULTS

From a societal perspective, the model estimated a mean cost of 3172.85€ and effectiveness of 2.64 quality-adjusted life years (QALYs) for the No PGx strategy, and a mean cost of 1687.02€ and effectiveness of 2.84 QALYs for the PGx strategy. The mean ICER was -7820.56 €/QALY. From a healthcare provider perspective (no indirect costs considered), the mean cost was 662.62€ for the No PGx strategy, and 446.60€ for the PGx strategy. The mean ICER was -1130.16 €/QALY.

LIMITATIONS

The heterogeneity of input data from the literature, the need for assumptions of homogeneous distribution of variables and events across population and time, and the inherent limitations of cost-effectiveness analysis should be considered. The model omits combined therapies (ADMs with mood stabilizers, antipsychotics, cognitive behavioral therapy…).

CONCLUSIONS

PGx screening in MDD prior to ADM start is a dominant strategy in the SNHS.

Utilization of supportive care medications and opportunities for pre-emptive pharmacogenomic testing in pediatric and young adults with leukemia

This study aimed to evaluate the utilization of drugs with pharmacogenomic guidelines (PGx-drugs) for personalized dosing in pediatric leukemia. A retrospective observational study of pediatric leukemia patients admitted between 2009-2019 at a single-center academic children's hospital was conducted to determine PGx-drug exposure within 3 years of diagnosis. Along with baseline demographic and clinical characteristics of these patients, data regarding dates of diagnosis, relapse, death were collected. During the study period, inclusion criteria were met by 714 patients. The most frequently given medications were ondansetron (96.1%), morphine (92.2%), and allopurinol (85.3%) during the study period. In this cohort, 82% of patients received five or more PGx-drugs. Patients diagnosed with acute myeloid leukemia and leukemia unspecified were prescribed more PGx-drugs than other types of leukemia. There was a significant relationship between age at diagnosis and the number of PGx-drugs prescribed. Adolescents and adults both received a median of 10 PGx-drugs, children received a median of 6 PGx-drugs, and infants received a median of 7 PGx-drugs (p < 0.001). Patients with recurrent leukemia had significantly more PGx-drugs prescribed compared to those without recurrent disease, 10 drugs and 6 drugs, respectively (p < 0.001). Patients diagnosed with childhood leukemia are high utilizers of PGx-drugs. There is a vital need to understand how PGx testing may be utilized to optimize treatment and enhance quality of life. Preemptive PGx testing is a tool that aids in optimization of drug therapy and decreases the need for later treatment modifications. This can result in financial savings from decreased health-care encounters.

Drug metabolizing enzymes pharmacogenetic variation-informed antidepressant therapy approach for common mental disorders: A systematic review and meta-analysis

IMPORTANCE

Currently, 30-50 % of individuals with depression and 40 % with anxiety-collectively referred to as common mental disorders (CMDs), exhibit inadequate responses to antidepressant treatments.

OBJECTIVE

To assess the effectiveness and safety of drug-metabolizing enzyme pharmacogenetic variation informed treatment (PGxIT) versus usual antidepressant treatment (UT) in patients with CMDs.

DATA SOURCES

A literature search was conducted in the MEDLINE, Scopus, and Cochrane Library databases from inception until January 30, 2024.

STUDY SELECTION

Studies were selected based on CMD diagnoses, reporting on the genetic variations of drug-metabolizing enzyme (DME) genes in relation to antidepressants, involving PGxIT and UT groups with human subjects, and published in English.

DATA EXTRACTION AND SYNTHESIS

Data extraction and quality assessment were performed independently by two authors. A pooled risk ratio (RR) with 95 % CI was estimated using both random and fixed-effect models, and heterogeneity was assessed using Cochran's Q test and the I2 statistic. The publication bias of eligible studies was assessed using post hoc Doi plots and the LFK index.

RESULTS

This systematic review included 18 studies (n = 7021). The PGxIT demonstrated greater efficacy in the remission of symptoms of depressive disorder at 8 weeks (RR 1.523 [95 % CI: 1.255-1.843]; I2 = 48 %) and 12 weeks (RR 1.631 [95 % CI: 1.001-2.657]; I2 = 86 %; p < 0.01), and symptoms of anxiety disorder compared to UT. Additionally, the risk of adverse drug events (ADEs) was significantly lower in the PGxIT group (RR = 0.65 [95 % CI: 0.52-0.82]; I2 = 0 %) than in the UT group. The certainty of evidence for both outcomes was moderate.

CONCLUSIONS AND RELEVANCE

This systematic review and meta-analysis suggest that pharmacogenetically guided antidepressant treatment, based on genetic variation in drug-metabolizing enzymes, is associated with superior efficacy in the remission of symptoms for patients with depressive disorders and a reduction in ADEs compared to usual treatment and the findings of the systematic review for remission in anxiety disorders indicate that, PGx guided treatment is also associated with increased remission of symptoms in anxiety disorders compared to usual treatment.

SLCO1B1 and ABCG2 genotype-informed phenotypes are related to variation in ramipril exposure

Ramipril is an angiotensin-converting enzyme inhibitor used for hypertension and heart failure management. To date, scarce literature is available on pharmacogenetic associations affecting ramipril. The goal of this study was to investigate the effect of 120 genetic variants in 34 pharmacogenes (i.e., genes encoding for enzymes like CYPs or UGTs and transporters like ABC or SLC) on ramipril pharmacokinetic variability and adverse drug reaction (ADR) incidence. Twenty-nine healthy volunteers who had participated in a single-dose bioequivalence clinical trial of two formulations of ramipril were recruited. A univariate and multivariate analysis searching for associations between genetic variants and ramipril pharmacokinetics was performed. SLCO1B1 and ABCG2 genotype-informed phenotypes strongly predicted ramipril exposure. Volunteers with the SLCO1B1 decreased function (DF) phenotype presented around 1.7-fold higher dose/weight-corrected area under the curve (AUC/DW) than volunteers with the normal function (NF) phenotype (univariate p-value [puv] < 0.001, multivariate p-value [pmv] < 0.001, β = 0.533, R2 = 0.648). Similarly, volunteers with ABCG2 DF + poor function (PF) phenotypes presented around 1.6-fold higher AUC/DW than those with the NF phenotype (puv = 0.011, pmv < 0.001, β = 0.259, R2 = 0.648). Our results suggest that SLCO1B1 and ABCG2 are important transporters to ramipril pharmacokinetics, and their genetic variation strongly alters its pharmacokinetics. Further studies are required to confirm these associations and their clinical relevance.

Estimating the prevalence of potential and actionable drug-gene interactions in Irish primary care: A cross-sectional study

AIMS

Pharmacogenetics (PGx) is increasingly recognized as a strategy for medicines optimisation and prevention of adverse drug reactions. According to guidelines produced by the Clinical Pharmacogenetics Implementation Consortium (CPIC) and the Dutch Pharmacogenetic Working Group (DPWG), most medicines with drug-gene interactions (DGIs) are prescribed in primary care. This study aimed to estimate the prevalence of potential and actionable DGIs involving all medicines dispensed in Irish primary care.

METHODS

Dispensings of 46 drugs to General Medical Services (GMS) patients in the Health Service Executive Primary Care Reimbursement Service Irish pharmacy claims database from 01 January 2021 to 31 December 2021 were analysed to estimate the national prevalence of total dispensings and incidence of first-time dispensings of drugs with potential DGIs according to the CPIC and/or DPWG guidelines. Phenotype frequency data from the UK Biobank and the CPIC were used to estimate the incidence of actionable DGIs.

RESULTS

One in five dispensings (12 443 637 of 62 754 498, 19.8%) were medicines with potential DGIs, 1 878 255 of these dispensed for the first time. On application of phenotype frequencies and linked guideline based therapeutic recommendations, 2 349 055 potential DGIs (18.9%) required action, such as monitoring and guarding against maximum dose, drug or dose change. One in five (369 700, 19.7%) first-time dispensings required action, with 139 169 (7.4%) requiring a change in prescribing. Antidepressants, weak opioids and statins were most commonly identified as having actionable DGIs.

CONCLUSIONS

This study estimated a high prevalence of DGIs in primary care in Ireland, identifying the need and opportunity to optimize drug therapy through PGx testing.

Phenotypic Models of Drug-Drug-Gene Interactions Mediated by Cytochrome Drug-Metabolizing Enzymes

Genetic polymorphisms in drug metabolizing enzymes and drug-drug interactions are major sources of inadequate drug exposure and ensuing adverse effects or insufficient responses. The current challenge in assessing drug-drug gene interactions (DDGIs) for the development of precise dose adjustment recommendation systems is to take into account both simultaneously. Here, we analyze the static models of DDGI from in vivo data and focus on the concept of phenoconversion to model inhibition and genetic polymorphisms jointly. These models are applicable to datasets where pharmacokinetic information is missing and are being used in clinical support systems and consensus dose adjustment guidelines. We show that all such models can be handled by the same formal framework, and that models that differ at first sight are all versions of the same linear phenoconversion model. This model includes the linear pharmacogenetic and inhibition models as special cases. We highlight present challenges in this endeavor and the open issues for future research in developing DDGI models for recommendation systems.

Development of a Multifaceted Program for Pharmacogenetics Adoption at an Academic Medical Center: Practical Considerations and Lessons Learned

In 2019, Indiana University launched the Precision Health Initiative to enhance the institutional adoption of precision medicine, including pharmacogenetics (PGx) implementation, at university-affiliated practice sites across Indiana. The overarching goal of this PGx implementation program was to facilitate the sustainable adoption of genotype-guided prescribing into routine clinical care. To accomplish this goal, we pursued the following specific objectives: (i) to integrate PGx testing into existing healthcare system processes; (ii) to implement drug-gene pairs with high-level evidence and educate providers and pharmacists on established clinical management recommendations; (iii) to engage key stakeholders, including patients to optimize the return of results for PGx testing; (iv) to reduce health disparities through the targeted inclusion of underrepresented populations; (v) and to track third-party reimbursement. This tutorial details our multifaceted PGx implementation program, including descriptions of our interventions, the critical challenges faced, and the major program successes. By describing our experience, we aim to assist other clinical teams in achieving sustainable PGx implementation in their health systems.

Challenges and prospects in bridging precision medicine and artificial intelligence in genomic psychiatric treatment

Precision medicine is transforming psychiatric treatment by tailoring personalized healthcare interventions based on clinical, genetic, environmental, and lifestyle factors to optimize medication management. This study investigates how artificial intelligence (AI) and machine learning (ML) can address key challenges in integrating pharmacogenomics (PGx) into psychiatric care. In this integration, AI analyzes vast genomic datasets to identify genetic markers linked to psychiatric conditions. AI-driven models integrating genomic, clinical, and demographic data demonstrated high accuracy in predicting treatment outcomes for major depressive disorder and bipolar disorder. This study also examines the pressing challenges and provides strategic directions for integrating AI and ML in genomic psychiatry, highlighting the importance of ethical considerations and the need for personalized treatment. Effective implementation of AI-driven clinical decision support systems within electronic health records is crucial for translating PGx into routine psychiatric care. Future research should focus on developing enhanced AI-driven predictive models, privacy-preserving data exchange, and robust informatics systems to optimize patient outcomes and advance precision medicine in psychiatry.

CYP2D6 copy number determination using digital PCR

Background

CYP2D6 testing is increasingly used to guide drug therapy and thus, reliable methods are needed to test this complex and polymorphic gene locus. A particular challenge arises from the detection and interpretation of structural variants (SVs) including gene deletions, duplications, and hybrids with the CYP2D7 pseudogene. This study validated the Absolute Q™ platform for digital PCR-based CYP2D6 copy number variation (CNV) determination by comparing results to those obtained with a previously established method using the QX200 platform. In addition, protocols for streamlining CYP2D6 CNV testing were established and validated including the "One-pot" single-step restriction enzyme digestion and a multiplex assay simultaneously targeting the CYP2D6 5'UTR, intron 6, and exon 9 regions.

Methods

Genomic DNA (gDNA) samples from Coriell (n = 13) and from blood, saliva, and liver tissue (n = 17) representing 0-6 copies were tested on the Absolute Q and QX200 platforms. Custom TaqMan™ copy number (CN) assays targeting CYP2D6 the 5'UTR, intron 6, and exon 9 regions and a reference gene assay (TERT or RNaseP) were combined for multiplexing by optical channel. In addition, two digestion methods (One-pot digestion and traditional) were assessed. Inconclusive CN values on the Absolute Q were resolved using an alternate reference gene and/or diluting gDNA.

Results

Overall, results between the two platforms and digestions methods were consistent. The "One-pot" digestion method and optically multiplexing up to three CYP2D6 regions yielded consistent result across DNA sample types and diverse SVs, reliably detecting up to 6 gene copies. Rare variation in reference genes were found to interfere with results and interpretation, which were resolved by using a different reference.

Conclusion

The Absolute Q produced accurate and reliable CYP2D6 copy number results allowing for a streamlined and economical protocol using One-pot digestion and multiplexing three target regions. Protocols are currently being expanded to other pharmacogenes presenting with SVs/CNVs.

Investigating the Correlation between Genotypes and Hepatic Protein Expression of CYP2C9, CYP2C19, CYP2D6, and CYP3A5 Using Postmortem Tissue from a Danish Population

The cytochrome P450 (CYP) family of enzymes plays a central role in the metabolism of many drugs. CYP genes are highly polymorphic, which is known to affect protein levels, but for some low frequent CYP genotypes the correlation between genotype and CYP protein expression is less established. In this study, we determined the CYP2C9, CYP2C19, CYP2D6, and CYP3A5 genotypes of 250 Danish individuals included in a postmortem study. For 116 of the individuals, the hepatic CYP protein levels were investigated by a proteomics approach. Overall, we found the postmortem genetic and proteomic data to be in agreement with those of other studies performed on fresh hepatic tissue, showing the usability of postmortem hepatic tissue for this type of investigation. For less investigated genotypes, we could corroborate previously found results: 1) statistically significantly lower levels of hepatic CYP2C9 protein in individuals carrying the CYP2C9*3 variant compared with individuals with two wild type (wt) alleles; 2) comparable levels of CYP2C19 in CYP2C19*2/*17 and CYP2C19*1/*2 individuals; 3) reduced CYP2D6 protein levels in heterozygous individuals with the CYP2D6*3, CYP2D6*4, and CYP2D6*5 gene deletion variants; and 4) significantly lower levels of CYP3A5 protein in CYP3A5*3 homozygous individuals compared with individuals who were heterozygous for the CYP3A5*3 allele or homozygous individuals for the wt alleles. In conclusion, the use of postmortem tissue significantly increases the access to human specimens for research purposes, and postmortem proteomics can be used to investigate the link between CYP genotypes and hepatic protein expression. SIGNIFICANCE STATEMENT: In tissue samples from a large postmortem cohort (n = 250) we determined the CYP2C9, CYP2C19, CYP2D6, and CYP3A5 genotypes. Hepatic CYP protein levels were investigated in 116 individuals using a proteomics approach. For common genotypes, we found results similar to previous knowledge, pointing toward the usability of postmortem tissue. For the less investigated genotypes, we were able to corroborate genotype/protein expression correlations. It is a novel approach to use a large postmortem cohort to investigate genetic/protein expression correlations.

Implementation of pharmacogenomics: Where are we now?

Pharmacogenomics (PGx), examining the effect of genetic variation on interpatient variation in drug disposition and response, has been widely studied for several decades. However, as cost, as well as turnaround time associated with PGx testing, has significantly improved, the use of PGx in the clinical setting has been gaining momentum. Nevertheless, challenges have emerged in the broader clinical implementation of PGx. In this review, we will outline current models of PGx delivery and methodologies of evaluation, and discuss clinically relevant PGx tests and associated medications. Additionally, we will describe our approach for the broad implementation of pre-emptive DPYD genotyping in patients taking fluoropyrimidines in Ontario, Canada, as an example of clinically actionable PGx testing with sufficient clinical evidence of patient benefit that can become a new standard of patient care. We will highlight challenges associated with PGx testing, including a lack of diversity in PGx studies as well as general limitations that impact the broad adoption of PGx testing. Lastly, we examine the future of PGx, discussing new clinical targets, methodologies and analysis approaches.

Therapeutic drug monitoring of osimertinib in EGFR mutant non-small cell lung cancer by dried blood spot and plasma collection: A pilot study

AIMS

Therapeutic drug monitoring (TDM) has led to significant improvements in individualized medical care, although its implementation in oncology has been limited to date. Tyrosine kinase inhibitors (TKIs) are a group of therapies for which TDM has been suggested. Osimertinib is one such therapy used in the treatment of epidermal growth factor receptor (EGFR) mutation-driven lung cancer. Herein, we describe a prospective pilot study involving 21 patients on osimertinib primarily as a preliminary evaluation of drug levels in a real-world setting.

METHODS

Concentrations of the drug and its primary metabolites were measured with a validated liquid chromatography-mass spectrometry (LC-MS) assay across serial timepoints. As part of this study, inter-individual variability by dose and ethnicity as well as intra-individual variability across timepoints are explored. Furthermore, we attempted to validate dried blood spot (DBS)-based quantitation as an accurate alternative to plasma quantitation.

RESULTS

Successful quantitation of osimertinib and primary metabolites was achieved for our subjects. Compound plasma levels were highly correlated to DBS levels. There was no significant difference in concentrations with ethnicity or dosing or intra-individual variability across timepoints.

CONCLUSIONS

As such, we demonstrate that TDM for osimertinib is practical for future trials. We also validated the use of DBS as an alternative to conventional quantitation for exploration of TDM for osimertinib in larger trials and for other targeted therapies.

Interactions of antidepressants with concomitant medications-safety of complex therapies in multimorbidities

Depression is the fourth most serious disease in the world. Left untreated, it is a cause of suicide attempts, emergence or exacerbation worsening of serious diseases, bodily and mental disorders, as well as increased risk of cardiovascular diseases, stroke, diabetes, and obesity, as well as endocrine and neurological diseases. Frequent coexistence of depression and other diseases requires the simultaneous use of several drugs from different therapeutic groups, which very often interact and intensify comorbidities, sometimes unrelated mechanisms. Sufficient awareness of potential drug interactions is critical in clinical practice, as it allows both to avoid disruption of proper pharmacotherapy and achieve substantive results. Therefore, this review aims to analyze the interactions of antidepressants with other concomitant medications. Against the backdrop of experimental research and a thorough analysis of the up-to-date literature, the authors discuss in detail the mechanisms and effects of action of individual drug interactions and adaptogens, including the latest antidepressants.

Solanidine Metabolites as Diet-Derived Biomarkers of CYP2D6-Mediated Tamoxifen Metabolism in Breast Cancer Patients

Tamoxifen is an important antiestrogen for the treatment of hormone receptor-positive breast cancer and undergoes bioactivation by CYP2D6 to its active metabolite endoxifen. Genetic variation in CYP2D6 has been linked to endoxifen levels during tamoxifen therapy. Recent studies have suggested solanidine, a glycoalkaloid phytochemical in potatoes, undergoes CYP2D6-mediated metabolism to 4-OH-solanidine (m/z 414) and 3,4-seco-solanidine-3,4-dioic acid (SSDA; m/z 444). Using a retrospective cohort of 1,032 breast cancer patients on tamoxifen therapy, we examined the association of solanidine metabolites with CYP2D6 activity and its correlation with tamoxifen metabolism. Solanidine, 4-OH-solanidine, or SSDA was detected in 99.7% (N = 1,029) of plasma samples. Decreased solanidine metabolite ratios were found in CYP2D6 intermediate and poor metabolizers (P < 0.0001). Patients on CYP2D6 strong inhibitors had a 77.6% and 94.2% decrease in 4-OH-solandine/solanidine (P < 0.0001) and SSDA/solanidine (P < 0.0001), respectively. The ratio of endoxifen to tamoxifen was highly correlated with both 4-OH-solandine/solanidine (ρ = 0.3207, P < 0.0001) and SSDA/solanidine (ρ = 0.5022, P < 0.0001) ratios. Logistic regression modeling was used to determine that 4-OH-solanidine/solanidine and SSDA/solanidine ratios below 2.1 and 0.8, respectively, predicted endoxifen concentrations of <16 nM. In conclusion, solanidine, 4-OH-solanidine, and SSDA are diet-derived biomarkers of CYP2D6 activity. Moreover, in patients on tamoxifen therapy, 4-OH-solanidine/solanidine and SSDA/solanidine predicted endoxifen levels including the inhibitory effects of concomitantly prescribed CYP2D6-interacting medications. Accordingly, 4-OH-solanidine/solanidine or SSDA/solanidine ratio has the potential to be particularly useful prior to initiation of tamoxifen or for determining the impact of CYP2D6 drug interactions, as well as prior to switching from an aromatase inhibitor to tamoxifen.

Metabolic activity of CYP2C19 and CYP2D6 on antidepressant response from 13 clinical studies using genotype imputation: a meta-analysis

Cytochrome P450 enzymes including CYP2C19 and CYP2D6 are important for antidepressant metabolism and polymorphisms of these genes have been determined to predict metabolite levels. Nonetheless, more evidence is needed to understand the impact of genetic variations on antidepressant response. In this study, individual clinical and genetic data from 13 studies of European and East Asian ancestry populations were collected. The antidepressant response was clinically assessed as remission and percentage improvement. Imputed genotype was used to translate genetic polymorphisms to metabolic phenotypes (poor, intermediate, normal, and rapid+ultrarapid) of CYP2C19 and CYP2D6. CYP2D6 structural variants cannot be imputed from genotype data, limiting the determination of metabolic phenotypes, and precluding testing for association with response. The association of CYP2C19 metabolic phenotypes with treatment response was examined using normal metabolizers as the reference. Among 5843 depression patients, a higher remission rate was found in CYP2C19 poor metabolizers compared to normal metabolizers at nominal significance but did not survive after multiple testing correction (OR = 1.46, 95% CI [1.03, 2.06], p = 0.033, heterogeneity I2 = 0%, subgroup difference p = 0.72). No metabolic phenotype was associated with percentage improvement from baseline. After stratifying by antidepressants primarily metabolized by CYP2C19, no association was found between metabolic phenotypes and antidepressant response. Metabolic phenotypes showed differences in frequency, but not effect, between European- and East Asian-ancestry studies. In conclusion, metabolic phenotypes imputed from genetic variants using genotype were not associated with antidepressant response. CYP2C19 poor metabolizers could potentially contribute to antidepressant efficacy with more evidence needed. Sequencing and targeted pharmacogenetic testing, alongside information on side effects, antidepressant dosage, depression measures, and diverse ancestry studies, would more fully capture the influence of metabolic phenotypes.

Pharmacogenetics in Italy: current landscape and future prospects

Pharmacogenetics investigates sequence of genes that affect drug response, enabling personalized medication. This approach reduces drug-induced adverse reactions and improves clinical effectiveness, making it a crucial consideration for personalized medical care. Numerous guidelines, drawn by global consortia and scientific organizations, codify genotype-driven administration for over 120 active substances. As the scientific community acknowledges the benefits of genotype-tailored therapy over traditionally agnostic drug administration, the push for its implementation into Italian healthcare system is gaining momentum. This evolution is influenced by several factors, including the improved access to patient genotypes, the sequencing costs decrease, the growing of large-scale genetic studies, the rising popularity of direct-to-consumer pharmacogenetic tests, and the continuous improvement of pharmacogenetic guidelines. Since EMA (European Medicines Agency) and AIFA (Italian Medicines Agency) provide genotype information on drug leaflet without clear and explicit clinical indications for gene testing, the regulation of pharmacogenetic testing is a pressing matter in Italy. In this manuscript, we have reviewed how to overcome the obstacles in implementing pharmacogenetic testing in the clinical practice of the Italian healthcare system. Our particular emphasis has been on germline testing, given the absence of well-defined national directives in contrast to somatic pharmacogenetics.

Overcoming Barriers: Strategies for Implementing Pharmacist-Led Pharmacogenetic Services in Swiss Clinical Practice

There is growing evidence that pharmacogenetic analysis can improve drug therapy for individual patients. In Switzerland, pharmacists are legally authorized to initiate pharmacogenetic tests. However, pharmacogenetic tests are rarely conducted in Swiss pharmacies. Therefore, we aimed to identify implementation strategies that facilitate the integration of a pharmacist-led pharmacogenetic service into clinical practice. To achieve this, we conducted semi-structured interviews with pharmacists and physicians regarding the implementation process of a pharmacist-led pharmacogenetic service. We utilized the Consolidated Framework for Implementation Research (CFIR) to identify potential facilitators and barriers in the implementation process. Additionally, we employed Expert Recommendations for Implementing Change (ERIC) to identify strategies mentioned in the interviews and used the CFIR-ERIC matching tool to identify additional strategies. We obtained interview responses from nine pharmacists and nine physicians. From these responses, we identified 7 CFIR constructs as facilitators and 12 as barriers. Some of the most commonly mentioned barriers included unclear procedures, lack of cost coverage by health care insurance, insufficient pharmacogenetics knowledge, lack of interprofessional collaboration, communication with the patient, and inadequate e-health technologies. Additionally, we identified 23 implementation strategies mentioned by interviewees using ERIC and 45 potential strategies using the CFIR-ERIC matching tool. In summary, we found that significant barriers hinder the implementation process of this new service. We hope that by highlighting potential implementation strategies, we can advance the integration of a pharmacist-led pharmacogenetic service in Switzerland.

Exploring biologically oriented precision mental health initiatives for the care of patients with eating disorders: A narrative review

OBJECTIVE

Eating disorders (EDs) represent a major public health burden. Increasingly, studies suggest mental health (MH) fields are failing to improve the effectiveness of treatments and that alternative models of care must be considered. Precision mental health (PMH) seeks to tailor treatment to individual needs and relies on a comprehensive understanding of the neurobiological and physiological underpinnings of mental illness.

METHODS

In this narrative review, published literature with focus on biological application of PMH strategies for EDs is reviewed and summarised.

RESULTS

A total of 39 articles were retained for the review covering a variety of themes with relevance to PMH. Many studies of biological markers with PMH applicability focused on anorexia nervosa. Although a variety of potential PMH research applications were identified, the review failed to identify any evidence of implementation into routine ED practice.

CONCLUSIONS

Despite the theoretical merit of biological application of PMH in ED treatment, clinical applications for standard practice are lacking. There is a need to invest further in studies that seek to identify biological markers and investigate neurobiological underpinnings of disease in hopes of targeting and developing treatments that can be better tailored to the individualised needs of patients.

Prevalence of CYP2D6 structural variation in large retrospective study

CYP2D6 is a highly polymorphic gene with clinically important structural variations. Commonly, only exon 9 is assayed on clinical pharmacogenomics panels, as it allows for accurate functional characterization even in the presence of a CYP2D6::CYP2D7 conversion. However, this method does not capture CYP2D7::CYP2D6 (CYP2D6*13) conversions, possibly leading to inaccurate phenotype assignment. The study's purpose was to determine the frequency of structural variations in CYP2D6 utilizing multiple copy number variation (CNV) assay locations to quantify the potential impact on clinical phenotype classification. A retrospective analysis was conducted of de-identified pharmacogenomics data submitted through the Translational Software, Inc. platform. Samples with CYP2D6 CNV data for exon 9 and at least one additional CNV location (5'UTR, exon 1, intron 2, exon 5 or intron 6) were included. CYP2D7::CYP2D6 and CYP2D6::CYP2D7 conversions were classified according to PharmVar nomenclature. The CYP2D6 copies were capped at four total copies to account for assay limitations in detecting more than four copies. A total of 106,474 samples were included for analysis. CYP2D7::CYP2D6 conversions were present in approximately 2.44% of samples, and 5.84% of samples had CYP2D6::CYP2D7 conversions. Many samples did not have a CYP2D7 conversion detected (91.5%; 97,462/106,474). A full gene deletion was detected in 0.15%, and 5.98% had a duplication or multiplication present. This retrospective study underscores the importance of testing more than one CNV site for CYP2D6 . Over 2% of patients were found to have a CYP2D7::CYP2D6 conversion. This translates into potentially misclassified phenotype classification and incongruent clinical recommendations.

[Barriers for Implementation of PGx Testing in Psychiatric Hospitals in Germany: Results of the FACT-PGx Study]

OBJECTIVE

The FACT-PGx study was conducted to analyze barriers to implementation of pharmacogenetic testing in psychiatric hospitals in Germany and to propose solutions for its faster and easier implementation in all hospitals.

METHODS

104 patients (50% female) were genotyped and participated in the study. 67 completed a survey. To analyze the correlation between continuous data (age) of the survey, the wilcoxon rank test and for categorial data (education level, history of treatment and episodes), t-test was used.

RESULTS

No patient declined to be genotyped. 99% believed that genotyping could help to shorten their hospital stay. Patients >40 years of age and with higher educational levels were willing to pay for the PGx (p=0.009). On average, patients were willing to pay 117.42€ +/-140.49€ and to wait 15.83+/- 8.92 days for the results. Processes differed significantly between routine laboratory screening and PGx testing which could be a barrier for implementation.

CONCLUSION

Patients are not barriers to but enablers of an implementation of PGx. New process flows can be barriers, but can be overcome by optimization.

Precision dosing for patients on tricyclic antidepressants

OBJECTIVE

We aim to develop a personalized dosing tool for tricyclic antidepressants (TCAs) that integrates CYP2D6 and CYP2C19 gene variants and their effects while also considering the polypharmacy effect.

METHODS

The study first adopted a scoring system that assigns weights to each genetic variant. A formula was then developed to compute the effect of both genes' variants on drug dosing. The output of the formula was assessed by a comparison with the clinical pharmacogenetics implementation consortium recommendation. The study also accounts for the effect of the co-administration of inhibitors and inducers on drug metabolism. Accordingly, a user-friendly tool, Clinical Dosing Tool ver.2, was created to assist clinicians in dosing patients on TCAs.

RESULTS

The study provides a comprehensive list of all alleles with corresponding activity values and phenotypes for both enzymes. The tool calculated an updated area under the curve ratio that utilizes the effects of both enzymes' variants for dose adjustment. The tool provided a more accurate individualized dosing that also integrates the polypharmacy effect.

CONCLUSION

To the best of our knowledge, the literature misses such a tool that provides a numerical adjusted dose based on continuous numerical activity scores for the considered patients' alleles and phenoconversion.

Association of CYP2D6 and CYP2C19 metabolizer status with switching and discontinuing antidepressant drugs: an exploratory study

BACKGROUND

Tailoring antidepressant drugs (AD) to patients' genetic drug-metabolism profile is promising. However, literature regarding associations of ADs' treatment effect and/or side effects with drug metabolizing genes CYP2D6 and CYP2C19 has yielded inconsistent results. Therefore, our aim was to longitudinally investigate associations between CYP2D6 (poor, intermediate, and normal) and CYP2C19 (poor, intermediate, normal, and ultrarapid) metabolizer-status, and switching/discontinuing of ADs. Next, we investigated whether the number of perceived side effects differed between metabolizer statuses.

METHODS

Data came from the multi-site naturalistic longitudinal cohort Netherlands Study of Depression and Anxiety (NESDA). We selected depression- and/or anxiety patients, who used AD at some point in the course of the 9 years follow-up period (n = 928). Medication use was followed to assess patterns of AD switching/discontinuation over time. CYP2D6 and CYP2C19 alleles were derived using genome-wide data of the NESDA samples and haplotype data from the PharmGKB database. Logistic regression analyses were conducted to investigate the association of metabolizer status with switching/discontinuing ADs. Mann-Whitney U-tests were conducted to compare the number of patient-perceived side effects between metabolizer statuses.

RESULTS

No significant associations were observed of CYP metabolizer status with switching/discontinuing ADs, nor with the number of perceived side effects.

CONCLUSIONS

We found no evidence for associations between CYP metabolizer statuses and switching/discontinuing AD, nor with side effects of ADs, suggesting that metabolizer status only plays a limited role in switching/discontinuing ADs. Additional studies with larger numbers of PM and UM patients are needed to further determine the potential added value of pharmacogenetics to guide pharmacotherapy.

Pharmacogenomic insights in psychiatric care: uncovering novel actionability, allele-specific CYP2D6 copy number variation, and phenoconversion in 15,000 patients

Pharmacogenomic testing has emerged as an aid in clinical decision making for psychiatric providers, but more data is needed regarding its utility in clinical practice and potential impact on patient care. In this cross-sectional study, we determined the real-world prevalence of pharmacogenomic actionability in patients receiving psychiatric care. Potential actionability was based on the prevalence of CYP2C19 and CYP2D6 phenotypes, including CYP2D6 allele-specific copy number variations (CNVs). Combined actionability additionally incorporated CYP2D6 phenoconversion and the novel CYP2C-TG haplotype in patients with available medication data. Across 15,000 patients receiving clinical pharmacogenomic testing, 65% had potentially actionable CYP2D6 and CYP2C19 phenotypes, and phenotype assignment was impacted by CYP2D6 allele-specific CNVs in 2% of all patients. Of 4114 patients with medication data, 42% had CYP2D6 phenoconversion from drug interactions and 20% carried a novel CYP2C haplotype potentially altering actionability. A total of 87% had some form of potential actionability from genetic findings and/or phenoconversion. Genetic variation detected via next-generation sequencing led to phenotype reassignment in 22% of individuals overall (2% in CYP2D6 and 20% in CYP2C19). Ultimately, pharmacogenomic testing using next-generation sequencing identified potential actionability in most patients receiving psychiatric care. Early pharmacogenomic testing may provide actionable insights to aid clinicians in drug prescribing to optimize psychiatric care.

Genetic diversity of cytochrome P450 in patients receiving psychiatric care in Greece: a step towards clinical implementation

Aim: We herein inferred the genetic diversity of CYP450 isoenzymes to predict the percentage of patients who need dose adjustment in drugs used in psychiatry.Materials & methods: Data of 784 Greek patients receiving psychiatric care who were genotyped for CYP2D6, CYP2C19, CYP1A2, CYP3A5 and CYP2C9 isoenzymes were inferred to gene-drug pairs according to the US FDA, Clinical Pharmacogenetics Implementation Consortium and Dutch Pharmacogenetics Working Group annotations and published literature.Results: Atypical metabolism was found for 36.8% of patients in CYP2D6, 49.2% in CYP2C19, 45% in CYP1A2, 16.7% in CYP3A5 and 41.8% in CYP2C9. Dosage adjustment need was estimated for 10.2% of venlafaxine, 10.0% of paroxetine, 6.4% of sertraline, 30.8% of citalopram, 52.1% of escitalopram, 18.2% of fluvoxamine, 54.1% of tricyclic antidepressants, 16.7% of zuclopenthixol, 10.6% of haloperidol and 13.3% of risperidone treated patients.Conclusion: Clinical psychiatric pharmacogenomic implementation holds promise to improve drug effectiveness and safety.

A Canadian Simulation Model for Major Depressive Disorder: Study Protocol

BACKGROUND

Major depressive disorder (MDD) is a common, often recurrent condition and a significant driver of healthcare costs. People with MDD often receive pharmacological therapy as the first-line treatment, but the majority of people require more than one medication trial to find one that relieves symptoms without causing intolerable side effects. There is an acute need for more effective interventions to improve patients' remission and quality of life and reduce the condition's economic burden on the healthcare system. Pharmacogenomic (PGx) testing could deliver these objectives, using genomic information to guide prescribing decisions. With an already complex and multifaceted care pathway for MDD, future evaluations of new treatment options require a flexible analytic infrastructure encompassing the entire care pathway. Individual-level simulation models are ideally suited for this purpose. We sought to develop an economic simulation model to assess the effectiveness and cost effectiveness of PGx testing for individuals with major depression. Additionally, the model serves as an analytic infrastructure, simulating the entire patient pathway for those with MDD.

METHODS AND ANALYSIS

Key stakeholders, including patient partners, clinical experts, researchers, and modelers, designed and developed a discrete-time microsimulation model of the clinical pathways of adults with MDD in British Columbia (BC), including all publicly-funded treatment options and multiple treatment steps. The Simulation Model of Major Depression (SiMMDep) was coded with a modular approach to enhance flexibility. The model was populated using multiple original data analyses conducted with BC administrative data, a systematic review, and an expert panel. The model accommodates newly diagnosed and prevalent adult patients with MDD in BC, with and without PGx-guided treatment. SiMMDep comprises over 1500 parameters in eight modules: entry cohort, demographics, disease progression, treatment, adverse events, hospitalization, costs and quality-adjusted life-years (payoff), and mortality. The model predicts health outcomes and estimates costs from a health system perspective. In addition, the model can incorporate interactive decision nodes to address different implementation strategies for PGx testing (or other interventions) along the clinical pathway. We conducted various forms of model validation (face, internal, and cross-validity) to ensure the correct functioning and expected results of SiMMDep.

CONCLUSION

SiMMDep is Canada's first medication-specific, discrete-time microsimulation model for the treatment of MDD. With patient partner collaboration guiding its development, it incorporates realistic care journeys. SiMMDep synthesizes existing information and incorporates provincially-specific data to predict the benefits and costs associated with PGx testing. These predictions estimate the effectiveness, cost-effectiveness, resource utilization, and health gains of PGx testing compared with the current standard of care. However, the flexible analytic infrastructure can be adapted to support other policy questions and facilitate the rapid synthesis of new data for a broader search for efficiency improvements in the clinical field of depression.

The Contribution of Genetic Testing in Optimizing Therapy for Patients with Recurrent Depressive Disorder

(1) Background: The aim of this study was to analyze the impact of pharmacogenetic-guided antidepressant therapy on the 12-month evolution of the intensity of depressive symptoms in patients with recurrent depressive disorder (RDD) in comparison to a control group of depressive subjects who were treated conventionally. (2) Methods: This prospective longitudinal study was conducted between 2019 and 2022, and the patients were evaluated by employing the Hamilton Depression Rating Scale (HAM-D), Hamilton Anxiety Rating Scale (HAM-A) and the Clinical Global Impressions Scale: Severity and Improvement. We followed them up at 1, 3, 6, and 12 months. (3) Results: Of the 76 patients with RDD, 37 were tested genetically (Group A) and 39 were not (Group B). Although the patients from Group A had statistically significantly more severe MDD at baseline than those from Group B (p < 0.001), by adjusting their therapy according to the genetic testing, they had a progressive and more substantial reduction in the severity of RDD symptoms [F = 74.334; η2 = 0.674; p < 0.001], indicating a substantial association with the results provided by the genetic testing (67.4%). (4) Conclusions: In patients with RDD and a poor response to antidepressant therapy, pharmacogenetic testing allows for treatment adjustment, resulting in a constant and superior reduction in the intensity of depression and anxiety symptoms.

Study on genotype and phenotype of novel CYP2D6 variants using pharmacokinetic and pharmacodynamic models with metoprolol as a substrate drug

To investigate the pharmacokinetic and pharmacodynamic profiles of volunteers carrying CYP2D6 genotypes with unknow metabolic phenotypes, a total of 22 volunteers were recruited based on the sequencing results. Peripheral blood and urine samples were collected at specific time points after oral administration of metoprolol. A validated high-performance liquid chromatography (HPLC) method was used to determine the concentrations of metoprolol and α-hydroxymetoprolol. Blood pressure and electrocardiogram were also monitored. The results showed that the main pharmacokinetic parameters of metoprolol in CYP2D6*1/*34 carriers are similar to those in CYP2D6*1/*1 carriers. However, in individuals carrying the CYP2D6*10/*87, CYP2D6*10/*95, and CYP2D6*97/*97 genotypes, the area under the curve (AUC) and half-life (t1/2) of metoprolol increased by 2-3 times compared to wild type. The urinary metabolic ratio of metoprolol in these genotypes is consistent with the trends observed in plasma samples. Therefore, CYP2D6*1/*34 can be considered as normal metabolizers, while CYP2D6*10/*87, CYP2D6*10/*95, and CYP2D6*97/*97 are intermediate metabolizers. Although the blood concentration of metoprolol has been found to correlate with CYP2D6 genotype, its blood pressure-lowering effect reaches maximum effectiveness at a reduction of 25 mmHg. Furthermore, P-Q interval prolongation and heart rate reduction are not positively correlated with metoprolol blood exposure. Based on the pharmacokinetic-pharmacodynamic model, this study clarified the properties of metoprolol in subjects with novel CYP2D6 genotypes and provided important fundamental data for the translational medicine of this substrate drug.

Pharmacogenetic Influence on Stereoselective Steady-State Disposition of Bupropion

Bupropion is used for treating depression, obesity, and seasonal affective disorder, and for smoking cessation. Bupropion is commonly prescribed, but has complex pharmacokinetics and interindividual variability in metabolism and bioactivation may influence therapeutic response, tolerability, and safety. Bupropion is extensively and stereoselectively metabolized, the metabolites are pharmacologically active, and allelic variation in cytochrome P450 (CYP) 2B6 affects clinical hydroxylation of single-dose bupropion. Genetic effects on stereoselective disposition of steady-state bupropion are not known. In this preplanned secondary analysis of a prospective, randomized, double-blinded, crossover study which compared brand and generic bupropion XL 300 mg drug products, we measured steady-state enantiomeric plasma and urine parent bupropion and primary and secondary metabolite concentrations. This investigation evaluated the influence of genetic polymorphisms in CYP2B6, CYP2C19, and P450 oxidoreductase on the disposition of Valeant Pharmaceuticals Wellbutrin brand bupropion in 67 participants with major depressive disorder. We found that hydroxylation of both bupropion enantiomers was lower in carriers of the CYP2B6*6 allele and in carriers of the CYP2B6 516G>T variant, with correspondingly greater bupropion and lesser hydroxybupropion plasma concentrations. Hydroxylation was 25-50% lower in CYP2B6*6 carriers and one-third to one-half less in 516T carriers. Hydroxylation of the bupropion enantiomers was comparably affected by CYP2B6 variants. CYP2C19 polymorphisms did not influence bupropion plasma concentrations or hydroxybupropion formation but did influence the minor pathway of 4'-hydroxylation of bupropion and primary metabolites. P450 oxidoreductase variants did not influence bupropion disposition. Results show that CYP2B6 genetic variants affect steady-state metabolism and bioactivation of Valeant brand bupropion, which may influence therapeutic outcomes. SIGNIFICANCE STATEMENT: Bupropion, used for depression, obesity, and smoking cessation, undergoes metabolic bioactivation, with incompletely elucidated interindividual variability. We evaluated cytochrome P450 (CYP) 2B6, CYP2C19 and P450 oxidoreductase genetic variants and steady-state bupropion and metabolite enantiomers disposition. Both enantiomers hydroxylation was lower in CYP2B6*6 and CYP2B6 516G>T carriers, with greater bupropion and lesser hydroxybupropion plasma concentrations. CYP2C19 polymorphisms did not affect bupropion or hydroxybupropion but did influence minor 4'-hydroxylation of bupropion and primary metabolites. CYP2B6 variants affect steady-state bupropion bioactivation, which may influence therapeutic outcomes.

Pharmacogenomic study-A pilot study of the effect of pharmacogenomic phenotypes on the adequate dosing of verapamil for migraine prevention

OBJECTIVE

To investigate factors affecting the efficacy and tolerability of verapamil for migraine prevention using individual pharmacogenomic phenotypes.

BACKGROUND

Verapamil has a wide range of dosing in headache disorders without reliable tools to predict the optimal doses for an individual.

METHODS

This is a retrospective chart review examining adults with existing pharmacogenomic reports at Mayo Clinic who had used verapamil for migraine. Effects of six cytochrome P450 phenotypes on the doses of verapamil for migraine prevention were assessed.

RESULTS

Our final analysis included 33 migraine patients (82% with aura). The mean minimum effective and maximum tolerable doses of verapamil were 178.2(20-320) mg and 227.9(20-480) mg. A variety of CYP2C9, CYP2D6, and CYP3A5 phenotypes were found, without significant association with the verapamil doses after adjusting for age, sex, body mass index, and smoking status.

CONCLUSIONS

We demonstrated a wide range of effective and tolerable verapamil doses used for migraine in a cohort with various pharmacogenomic phenotypes.

Frequencies of CYP2C19 and CYP2D6 gene variants in a German inpatient sample with mood and anxiety disorders

OBJECTIVES

Previous results demonstrated that CYP2D6 and CYP2C19 gene variants affect serum concentrations of antidepressants. We implemented a PGx service determining gene variants in CYP2D6 and CYP2C19 in our clinical routine care and report on our first patient cohort.

METHODS

We analysed CYP2D6 and CYP2C19 allele, genotype, and phenotype frequencies, and actionable pharmacogenetic variants in this German psychiatric inpatient cohort. Two-tailed z-test was used to investigate for differences in CYP2D6 and CYP2C19 phenotypes and actionable/non-actionable genetic variant frequencies between our cohort and reference cohorts.

RESULTS

Out of the 154 patients included, 44.8% of patients were classified as CYP2D6 normal metabolizer, 38.3% as intermediate metabolizers, 8.4% as poor metabolizers, and 2.6% as ultrarapid metabolizers. As for CYP2C19, 40.9% of patients were classified as normal metabolizers, 19.5% as intermediate metabolizers, 2.6% as poor metabolizers, 31.2% as rapid metabolizers, and 5.8% as ultrarapid metabolizers. Approximately, 80% of patients had at least one actionable PGx variant.

CONCLUSION

There is a high prevalence of actionable PGx variants in psychiatric inpatients which may affect treatment response. Physicians should refer to PGx-informed dosing guidelines in carriers of these variants. Pre-emptive PGx testing in general may facilitate precision medicine also for other drugs metabolised by CYP2D6 and/or CYP2C19.

Documentation of results and medication prescribing after combinatorial psychiatric pharmacogenetic testing: A case for discrete results

PURPOSE

Combinatorial pharmacogenetic (PGx) panels intended to aid psychiatric prescribing are available to clinicians. Here, we evaluated the documentation of PGx panel results and subsequent prescribing patterns within a tertiary health care system.

METHODS

We performed a query of psychiatry service note text in our electronic health record using 71 predefined PGx terms. Patients who underwent combinatorial PGx testing were identified, and documentation of test results was analyzed. Prescription data following testing were examined for the frequency of prescriptions influenced by genes on the panel along with the medical specialties involved.

RESULTS

A total of 341 patients received combinatorial PGx testing, and documentation of results was found to be absent or incomplete for 198 patients (58%). The predominant method of documentation was through portable document formats uploaded to the electronic health record's "Media" section. Among patients with at least 1 year of follow-up, a large majority (194/228, 85%) received orders for medications affected by the tested genes, including 132 of 228 (58%) patients receiving at least 1 non-psychiatric medication influenced by the test results.

CONCLUSION

Results from combinatorial PGx testing were poorly documented. Medications affected by these results were often prescribed after testing, highlighting the need for discrete results and clinical decision support.

Physiologically Based Pharmacokinetic Modeling to Unravel the Drug-gene Interactions of Venlafaxine: Based on Activity Score-dependent Metabolism by CYP2D6 and CYP2C19 Polymorphisms

BACKGROUND

Venlafaxine (VEN) is a commonly utilized medication for alleviating depression and anxiety disorders. The presence of genetic polymorphisms gives rise to considerable variations in plasma concentrations across different phenotypes. This divergence in phenotypic responses leads to notable differences in both the efficacy and tolerance of the drug.

PURPOSE

A physiologically based pharmacokinetic (PBPK) model for VEN and its metabolite O-desmethylvenlafaxine (ODV) to predict the impact of CYP2D6 and CYP2C19 gene polymorphisms on VEN pharmacokinetics (PK).

METHODS

The parent-metabolite PBPK models for VEN and ODV were developed using PK-Sim® and MoBi®. Leveraging prior research, derived and implemented CYP2D6 and CYP2C19 activity score (AS)-dependent metabolism to simulate exposure in the drug-gene interactions (DGIs) scenarios. The model's performance was evaluated by comparing predicted and observed values of plasma concentration-time (PCT) curves and PK parameters values.

RESULTS

In the base models, 91.1%, 94.8%, and 94.6% of the predicted plasma concentrations for VEN, ODV, and VEN + ODV, respectively, fell within a twofold error range of the corresponding observed concentrations. For DGI scenarios, these values were 81.4% and 85% for VEN and ODV, respectively. Comparing CYP2D6 AS = 2 (normal metabolizers, NM) populations to AS = 0 (poor metabolizers, PM), 0.25, 0.5, 0.75, 1.0 (intermediate metabolizers, IM), 1.25, 1.5 (NM), and 3.0 (ultrarapid metabolizers, UM) populations in CYP2C19 AS = 2.0 group, the predicted DGI AUC0-96 h ratios for VEN were 3.65, 3.09, 2.60, 2.18, 1.84, 1.56, 1.34, 0.61, and for ODV, they were 0.17, 0.35, 0.51, 0.64, 0.75, 0.83, 0.90, 1.11, and the results were similar in other CYP2C19 groups. It should be noted that PK differences in CYP2C19 phenotypes were not similar across different CYP2D6 groups.

CONCLUSIONS

In clinical practice, the impact of genotyping on the in vivo disposition process of VEN should be considered to ensure the safety and efficacy of treatment.

The therapeutic landscape for COVID-19 and post-COVID-19 medications from genetic profiling of the Vietnamese population and a predictive model of drug-drug interaction for comorbid COVID-19 patients

Despite the raised awareness of the role of pharmacogenomic (PGx) in personalized medicines for COVID-19, data for COVID-19 drugs is extremely scarce and not even a publication on this topic for post-COVID-19 medications to date. In the current study, we investigated the genetic variations associated with COVID-19 and post-COVID-19 therapies by using whole genome sequencing data of the 1000 Vietnamese Genomes Project (1KVG) in comparison with other populations retrieved from the 1000 Genomes Project Phase 3 (1KGP3) and the Genome Aggregation Database (gnomAD). Moreover, we also evaluated the risk of drug interactions in comorbid COVID-19 and post-COVID-19 patients based on pharmacogenomic profiles of drugs using a computational approach. For COVID-19 therapies, variants related to the response of two causal treatment agents (tolicizumab and ritonavir) and antithrombotic drugs are common in the Vietnamese cohort. Regarding post-COVID-19, drugs for mental manipulations possess the highest number of clinical annotated variants carried by Vietnamese individuals. Among the superpopulations, East Asian populations shared the most similar genetic structure with the Vietnamese population, whereas the African population showed the most difference. Comorbid patients are at an increased drug-drug interaction (DDI) risk when suffering from COVID-19 and after recovering as well due to a large number of potential DDIs which have been identified. Our results presented the population-specific understanding of the pharmacogenomic aspect of COVID-19 and post-COVID-19 therapy to optimize therapeutic outcomes and promote personalized medicine strategy. We also partly clarified the higher risk in COVID-19 patients with underlying conditions by assessing the potential drug interactions.

Pharmacogenomics - a minor rather than major force in clinical medicine

INTRODUCTION

Pharmacogenomics (PGx) is touted as essential for the future of precision medicine. But the opportunity cost of PGx from the prescribers' perspective is rarely considered. The aim of this article is to critique PGx-guided prescribing using clinical pharmacology principles so that important cases for PGx testing are not missed by doctors responsible for therapeutic decision making.

AREAS COVERED

Three categories of PGx and their limitations are outlined - exposure PGx, response PGx, and immune-mediated safety PGx. Clinical pharmacology reasons are given for the narrow scope of PGx-guided prescribing apart from a few medical specialties. Clinical problems for doctors that may arise from PGx are then explained, including mismatch between patients' expectations of PGx testing and the benefits or answers it provides.

EXPERT OPINION

Contrary to popular opinion, PGx is unlikely to become the cornerstone of precision medicine. Sound clinical pharmacology reasons explain why PGx-guided prescribing is unnecessary for most drugs. Pharmacogenomics is important for niche areas of prescribing but has limited clinical utility more broadly. The opportunity cost of PGx-guided prescribing is currently too great for most doctors.

The Relevance of Integrating CYP2C19 Phenoconversion Effects into Clinical Pharmacogenetics

INTRODUCTION

CYP2D6 and CYP2C19 functional status as defined by genotype is modulated by phenoconversion (PC) due to pharmacokinetic interactions. As of today, there is no data on the effect size of PC for CYP2C19 functional status. The primary aim of this study was to investigate the impact of PC on CYP2C19 functional status.

METHODS

Two patient cohorts (total n=316; 44.2±15.4 years) were investigated for the functional enzyme status of CYP2C19 applying two different correction methods (PCBousman, PCHahn&Roll) as well as serum concentration and metabolite-to-parent ratio of venlafaxine, amitriptyline, mirtazapine, sertraline, escitalopram, risperidone, and quetiapine.

RESULTS

There was a decrease in the number of normal metabolizers of CYP2C19 and an increase in the number of poor metabolizers. When controlled for age, sex, and, in the case of amitriptyline, venlafaxine, and risperidone, CYP2D6 functional enzyme status, an association was observed between the CYP2C19 phenotype/functional enzyme status and serum concentration of amitriptyline, sertraline, and escitalopram.

DISCUSSION

PC of CYP2C19 changes phenotypes but does not improve correlations with serum concentrations. However, only a limited number of patients received perturbators of CYP2C19. Studies with large numbers of patients are still lacking, and thus, it cannot be decided if there are minor differences and which method of correction to use. For the time being, PC is relevant in individual patients treated with CYP2C19-affecting drugs, for example, esomeprazole. To ensure adequate serum concentrations in these patients, this study suggests the use of therapeutic drug monitoring.

Leveraging in Vitro Models for Clinically Relevant Rare CYP2D6 Variants in Pharmacogenomics

Cytochrome P450 2D6 (CYP2D6) is responsible for the metabolism of up to 20% of small-molecule drugs and therefore, may impact the safety and efficacy of medicines in broad therapeutic areas. CYP2D6 is highly polymorphic, and the frequency of variants can differ across racial and ethnic populations, significantly affecting enzymatic function and drug metabolism. However, rare variants of CYP2D6 present a unique challenge for academia, industry, and regulatory agencies alike due to the lack of feasibility of characterizing their clinical relevance in clinical trials, particularly in variants that exhibit population-specific frequencies in racial and ethnic groups that are poorly represented in clinical trials. Despite significant advancement in pharmacogenomics, the substrate specificity and related clinical relevance of these CYP2D6 rare variants remain largely unclear, and further efforts are warranted to characterize the burden of these variants on adverse drug reactions and drug efficacy. Thus, cell-based in vitro systems can be used to inform substrate-specific effects and the overall relevance of a rare variant. Liver microsomes, cell-based expression systems, ex vivo primary samples, and purified variant protein have all been used with various substrates to potentially predict the clinical impact of new substrates. In this review, we identify rare variants of CYP2D6 that demonstrate differences across races in prevalence and thus are often unassessed in clinical trials. Accordingly, we examine current pharmacogenomic in vitro models used to analyze the functional impact of these rare variants in a substrate-specific manner. SIGNIFICANCE STATEMENT: Variants of CYP2D6 play a clinically relevant role in drug metabolism, leading to potential safety and efficacy concerns. Although the influence of prevalent variants is often well characterized, rare variants are traditionally not included in clinical trials. This review captures the clinical relevance of rare variants in CYP2D6 by highlighting in vitro models that analyze their impact on the metabolism of CYP2D6 substrates.

Clinical Utility and Implementation of Pharmacogenomics for the Personalisation of Antipsychotic Treatments

Decades of pharmacogenetic research have revealed genetic biomarkers of clinical response to antipsychotics. Genetic variants in antipsychotic targets, dopamine and serotonin receptors in particular, and in metabolic enzymes have been associated with the efficacy and toxicity of antipsychotic treatments. However, genetic prediction of antipsychotic response based on these biomarkers is far from accurate. Despite the clinical validity of these findings, the clinical utility remains unclear. Nevertheless, genetic information on CYP metabolic enzymes responsible for the biotransformation of most commercially available antipsychotics has proven to be effective for the personalisation of clinical dosing, resulting in a reduction of induced side effects and in an increase in efficacy. However, pharmacogenetic information is rarely used in psychiatric settings as a prescription aid. Lack of studies on cost-effectiveness, absence of clinical guidelines based on pharmacogenetic biomarkers for several commonly used antipsychotics, the cost of genetic testing and the delay in results delivery hamper the implementation of pharmacogenetic interventions in clinical settings. This narrative review will comment on the existing pharmacogenetic information, the clinical utility of pharmacogenetic findings, and their current and future implementations.

Impact of Cytochrome P450 Genetic Variation on Patient-Reported Symptom Improvement and Side Effects Among Children and Adolescents Treated with Fluoxetine

Background: Clinical practice guidelines recommend the use of fluoxetine, a selective serotonin reuptake inhibitor (SSRI), as a first-line pharmacotherapy for major depressive disorder (MDD) and obsessive compulsive disorder (OCD) in children and adolescents. However, response and tolerability to fluoxetine varies from child to child, which may in part, be a result of interindividual differences in fluoxetine metabolism. In this study, we examined whether genotype-predicted activity scores of cytochrome P450 enzymes were associated with patient-reported symptom improvement and side effects in children and adolescents treated with fluoxetine. Methods: Ninety children and adolescents aged 7-18 with a MDD or OCD diagnosis and a history of fluoxetine treatment were recruited from Western Canada. For each participant, fluoxetine dose and duration information were collected, as well as questions about adherence, side effects, and symptom improvement. DNA was extracted from a saliva sample and genotyped for CYP2D6, CYP2C19, CYP2C9, CYP3A4, and CYP3A5. Logistic regression models were fitted to assess the impact of activity scores on symptom improvement and side effects. Results: Increased CYP2D6 activity score was significantly associated with reduced odds of symptom improvement (odds ratio [OR] = 0.46, 95% confidence interval [CI] = 0.23-0.91, p = 0.028) as well as a trend association with reduced side effects (OR = 0.49, 95% CI = 0.22-1.07, p = 0.072), after adjusting for age, sex, diagnosis, dose, duration, adherence, and activity scores of the other assessed CYP enzymes. No associations with symptom improvement or side effects were detected for the other CYP enzymes examined. Conclusions: Our results suggest that an increase in the genotype-predicted CYP2D6 activity score was associated with a decrease in the odds of reporting symptom improvement among children and adolescents treated with fluoxetine. These findings will contribute to future updates of pharmacogenetic-based SSRI prescribing guidelines and if replicated, could inform fluoxetine treatment in children and adolescents with MDD or OCD. Clinical Trial Registration: NCT04797364.

Pharmacogenetics in Child and Adolescent Psychiatry: Background and Evidence-Based Clinical Applications

The efficacy and tolerability of psychotropic medications can vary significantly among children and adolescents, and some of this variability relates to pharmacogenetic factors. Pharmacogenetics (PGx) in child and adolescent psychiatry can potentially improve treatment outcomes and minimize adverse drug reactions. This article reviews key pharmacokinetic and pharmacodynamic genes and principles of pharmacogenetic testing and discusses the evidence base for clinical decision-making concerning PGx testing. This article reviews current guidelines from the United States Food and Drug Administration (FDA), the Clinical Pharmacogenetics Implementation Consortium (CPIC), and the Dutch Pharmacogenetics Working Group (DPWG) and explores potential future directions. This review discusses key clinical considerations for clinicians prescribing psychotropic medications in children and adolescents, focusing on antidepressants, antipsychotics, stimulants, norepinephrine reuptake inhibitors, and alpha-2 agonists. Finally, this review synthesizes the practical use of pharmacogenetic testing and clinical decision support systems.

Impact of Pharmacogenomics on Pediatric Psychotropic Medication Prescribing in an Ambulatory Care Setting

Objective: Evidence for pharmacogenomic (PGx) guided treatment in child and adolescent psychiatry is growing. This study evaluated the impact of PGx testing on psychotropic medication prescribing in an ambulatory child and adolescent psychiatry and a developmental pediatrics clinic. Methods: This was a single-center, retrospective, descriptive analysis of patients who underwent PGx testing between January 2015 and October 2022 at a child and adolescent psychiatry clinic or developmental pediatrics clinic. The primary outcome was the proportion of patients with at least one psychotropic medication modification made 6-month posttesting that could be attributed to CYP2C19, CYP2D6, HLA-B*15:02, or HLA-A*31:01. Secondary outcomes included reason for testing, types of therapeutic modifications made, and whether the therapeutic modifications concorded with PGx guidelines. Results: A total of 193 patients were analyzed. The average age was 10 ± 4 years old, 60% were male, 78% were Caucasian. Sixty-eight percent had a primary diagnosis of a neurodevelopmental disorder, namely autism spectrum disorder (51%), and attention-deficit/hyperactivity disorder (14%). The reasons for PGx testing included medication inefficacy (34%), medication intolerance (20%), and family request (19%). At the time of PGx testing, 37% of patients were taking ≥1 psychotropic medication with PGx annotation. Overall, 35 PGx-related therapeutic modifications were made in 32 (17%) patients. These included continuing current PGx medication (6.2%) and starting PGx medication (5.2%). These modifications mainly involved antidepressants. Out of these 35 PGx-related therapeutic modifications, 94% were concordant with PGx guidelines. Among 29 patients who were prescribed at least one CYP2D6 inhibitor, 25 (86%) underwent CYP2D6 phenoconversion. Conclusions: It is critical to apply pediatric age-specific considerations when utilizing PGx testing in child and adolescent psychiatry. PGx testing stewardship could provide a framework to guide the clinical utility of PGx in a pediatric population with mental health conditions, including neurodevelopmental disorders.

A New Intervention for Implementation of Pharmacogenetics in Psychiatry: A Description of the PSY-PGx Clinical Study

(1) Background Pharmacological treatment for psychiatric disorders has shown to only be effective in about one-third of patients, as it is associated with frequent treatment failure, often because of side effects, and a long process of trial-and-error pharmacotherapy until an effective and tolerable treatment is found. This notion emphasizes the urgency for a personalized medicine approach in psychiatry. (2) Methods This prospective patient- and rater-blinded, randomized, controlled study will investigate the effect of dose-adjustment of antidepressants escitalopram and sertraline or antipsychotics risperidone and aripiprazole according to the latest state-of-the-art international dosing recommendations for CYP2C19 and CYP2D6 metabolizer status in patients with mood, anxiety, and psychotic disorders. A total sample of N = 2500 will be recruited at nine sites in seven countries (expected drop-out rate of 30%). Patients will be randomized to a pharmacogenetic group or a dosing-as-usual group and treated over a 24-week period with four study visits. The primary outcome is personal recovery using the Recovery Assessment Scale as assessed by the patient (RAS-DS), with secondary outcomes including clinical effects (response or symptomatic remission), side effects, general well-being, digital phenotyping, and psychosocial functioning. (3) Conclusions This is, to our knowledge, the first international, multi-center, non-industry-sponsored randomized controlled trial (RCT) that may provide insights into the effectiveness and utility of implementing pharmacogenetic-guided treatment of psychiatric disorders, and as such, results will be incorporated in already available dosing guidelines.

Circulating Biomarkers Instead of Genotyping to Establish Metabolizer Phenotypes

Pharmacogenomics (PGx) enables personalized treatment for the prediction of drug response and to avoid adverse drug reactions. Currently, PGx mainly relies on the genetic information of absorption, distribution, metabolism, and excretion (ADME) targets such as drug-metabolizing enzymes or transporters to predict differences in the patient's phenotype. However, there is evidence that the phenotype-genotype concordance is limited. Thus, we discuss different phenotyping strategies using exogenous xenobiotics (e.g., drug cocktails) or endogenous compounds for phenotype prediction. In particular, minimally invasive approaches focusing on liquid biopsies offer great potential to preemptively determine metabolic and transport capacities. Early studies indicate that ADME phenotyping using exosomes released from the liver is reliable. In addition, pharmacometric modeling and artificial intelligence improve phenotype prediction. However, further prospective studies are needed to demonstrate the clinical utility of individualized treatment based on phenotyping strategies, not only relying on genetics. The present review summarizes current knowledge and limitations.

The Case for Pre-Emptive Pharmacogenetic Screening in South Africa

Lack of equitable representation of global genetic diversity has hampered the implementation of genomic medicine in under-represented populations, including those on the African continent. Data from the multi-national Pre-emptive Pharmacogenomic Testing for Preventing Adverse Drug Reactions (PREPARE) study suggest that genotype guidance for prescriptions reduced the incidence of clinically relevant adverse drug reactions (ADRs) by 30%. In this study, hospital dispensary trends from a tertiary South African (SA) hospital (Steve Biko Academic Hospital; SBAH) were compared with the drugs monitored in the PREPARE study. Dispensary data on 29 drugs from the PREPARE study accounted for ~10% of total prescriptions and ~9% of the total expenditure at SBAH. VigiLyze data from the South African Health Products Regulatory Authority were interrogated for local ADRs related to these drugs; 27 were listed as being suspected, concomitant, or interacting in ADR reports. Furthermore, a comparison of pharmacogene allele frequencies between African and European populations was used to frame the potential impact of pre-emptive pharmacogenetic screening in SA. Enumerating the benefit of pre-emptive pharmacogenetic screening in SA will only be possible once we initiate its full application. However, regional genomic diversity, disease burden, and first-line treatment options could be harnessed to target stratified PGx today.

Sudden-Onset Acute Obsessive-Compulsive Disorder Associated with Streptococcus and Brain MRI Hyperintensity in a Young Adult

BACKGROUND

Pediatric autoimmune neuropsychiatric disorders associated with streptococcal (strep) infections (PANDAS) are a recognized medical entity among children. But evidence for strep-mediated sudden-onset obsessive-compulsive disorder (OCD) in young adults is very limited. Delayed strep assessment and treatment may negatively impact clinical outcomes.

METHODS

We describe a young adult with acute sudden-onset OCD (age 24), treated unsuccessfully with medication and therapy for 3 years. At age 27, antistreptolysin-O (ASO) was tested, based on extensive pediatric history of strep infections. Antibiotic treatment was initiated.

RESULTS

Magnetic resonance imaging (MRI) identified a new temporal lobe hyperintensity at OCD onset (age 24), which persisted at ages 25 and 30. ASO titers were elevated from age 27 through 29. Following Amoxicillin treatment, ASO initially increased. Subsequent Amoxicillin + Clavulin treatment produced improved OCD symptoms and treatment response, with no adverse effects.

CONCLUSION

These results strongly suggest an association among strep infection, neuro-inflammation and sudden-onset OCD in this young adult whose response to medication and therapy was successful only after high-dose antibiotic intervention. Greater OCD remission potential may be possible with earlier identification and antibiotic treatment than 3 years post OCD onset. These findings add to the limited literature on strep as an etiology of the sudden-onset of OCD in young adults. They also lend urgency to increased frontline awareness for early strep and ASO assessment in sudden-onset acute OCD among young adults.

Novel Independent Trans- and Cis-Genetic Variants Associated with CYP2D6 Expression and Activity in Human Livers

Cytochrome P450 2D6 (CYP2D6) is a critical hepatic drug-metabolizing enzyme in humans, responsible for metabolizing approximately 20%-25% of commonly used medications such as codeine, desipramine, fluvoxamine, paroxetine, and tamoxifen. The CYP2D6 gene is highly polymorphic, resulting in substantial interindividual variability in its catalytic function and the pharmacokinetics and therapeutic outcomes of its substrate drugs. Although many functional CYP2D6 variants have been discovered and validated, a significant portion of the variability in the expression and activity of CYP2D6 remains unexplained. In this study, we performed a genome-wide association study (GWAS) to identify novel variants associated with CYP2D6 protein expression in individual human livers, followed by a conditional analysis to control for the effect of functional CYP2D6 star alleles. We also examined their impact on hepatic CYP2D6 activity. Genotyping on a genome-wide scale was achieved using the Illumina Multi-Ethnic Genotyping Array (MEGA). A data-independent acquisition (DIA)-based proteomics method was used to quantify CYP2D6 protein concentrations. CYP2D6 activity was determined by measuring the dextromethorphan O-demethylation in individual human liver s9 fractions. The GWAS identified 44 single nuclear polymorphisms (SNPs) that are significantly associated with CYP2D6 protein expressions with a P value threshold of 5.0 × 10-7 After the conditional analysis, five SNPs, including the cis-variants rs1807493 and rs1062753 and the trans-variants rs4073010, rs729559, and rs80274432, emerged as independent variants significantly correlated with hepatic CYP2D6 protein expressions. Notably, four of these SNPs, except for rs80274432, also exhibited a significant association with CYP2D6 activities in human livers, suggesting their potential as novel and independent cis- and trans-variants regulating CYP2D6. SIGNIFICANT STATEMENT: Using individual human livers, we identified four novel cis- and trans-pQTLs/aQTLs (protein quantitative trait loci/activity quantitative trait loci) of Cytochrome P450 2D6 (CYP2D6) that are independent from known functional CYP2D6 star alleles. This study connects the CYP2D6 gene expression and activity, enhancing our understanding of the genetic variants associated with CYP2D6 protein expression and activity, potentially advancing our insight into the interindividual variability in CYP2D6 substrate medication response.

Navigating the Intersection of Technology and Depression Precision Medicine

This chapter primarily focuses on the progress in depression precision medicine with specific emphasis on the integrative approaches that include artificial intelligence and other data, tools, and technologies. After the description of the concept of precision medicine and a comparative introduction to depression precision medicine with cancer and epilepsy, new avenues of depression precision medicine derived from integrated artificial intelligence and other sources will be presented. Additionally, less advanced areas, such as comorbidity between depression and cancer, will be examined.

Effectiveness of pharmacogenomics on the response and remission of treatment-resistant depression: a meta-analysis of randomised controlled trials

Background

Pharmacogenomics (PGx) is a promising tool to realise tailored drug therapy for depression.

Aims

To investigate the treatment efficacy of PGx for treatment-resistant depression (TRD) compared with treatment as usual.

Methods

A systematic search was conducted in PubMed, Embase, the Cochrane Library, Web of Science and PsycINFO to identify relevant studies published from inception to 15 April 2023. Two-arm randomised controlled trials (RCTs) exploring the efficacy of PGx-guided versus unguided treatment for TRD were included. The risk of bias in the included studies was evaluated using the Cochrane risk of bias assessment tool. The overall quality of evidence was assessed using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach.

Results

Seven RCTs (n=3003) comparing PGx-guided (n=1492) and unguided (n=1511) groups were identified and analysed. PGx-guided treatment was superior to treatment as usual in response (relative risk (RR)=1.31; 95% confidence interval (95% CI): 1.15 to 1.49; p<0.001) and remission (RR=1.40; 95% CI: 1.09 to 1.80; p=0.009) improvements. Effect sizes for acceptability (RR=0.90; 95% CI: 0.80 to 1.02; p=0.100) and side effect burden (RR=0.58; 95% CI: 0.29 to 1.15; p=0.120) between the two groups were not statistically different. The overall quality of evidence was rated from 'very low' (25%) to 'low' (75%) based on the GRADE criteria.

Conclusions

PGx-guided treatment has shown a small overall effect in improving the response and remission rates for patients with TRD. However, these results should be interpreted cautiously because of the few included studies and the low quality of evidence. Further high-quality clinical trials are warranted to confirm the findings.

PROSPERO registration number

CRD42022340182.

Meta-analysis of CYP2C19 and CYP2D6 metabolic activity on antidepressant response from 13 clinical studies using genotype imputation

Cytochrome P450 enzymes including CYP2C19 and CYP2D6 are important for antidepressant metabolism and polymorphisms of these genes have been determined to predict metabolite levels. Nonetheless, more evidence is needed to understand the impact of genetic variations on antidepressant response. In this study, individual clinical and genetic data from 13 studies of European and East Asian ancestry populations were collected. The antidepressant response was clinically assessed as remission and percentage improvement. Imputed genotype was used to translate genetic polymorphisms to metabolic phenotypes (poor, intermediate, normal, and rapid+ultrarapid) of CYP2C19 and CYP2D6. The association of CYP2C19 and CYP2D6 metabolic phenotypes with treatment response was examined using normal metabolizers as the reference. Among 5843 depression patients, a higher remission rate was found in CYP2C19 poor metabolizers compared to normal metabolizers at nominal significance but did not survive after multiple testing correction (OR=1.46, 95% CI [1.03, 2.06], p=0.033, heterogeneity I2=0%, subgroup difference p=0.72). No metabolic phenotype was associated with percentage improvement from baseline. After stratifying by antidepressants primarily metabolized by CYP2C19 and CYP2D6, no association was found between metabolic phenotypes and antidepressant response. Metabolic phenotypes showed differences in frequency, but not effect, between European- and East Asian-ancestry studies. In conclusion, metabolic phenotypes imputed from genetic variants using genotype were not associated with antidepressant response. CYP2C19 poor metabolizers could potentially contribute to antidepressant efficacy with more evidence needed. CYP2D6 structural variants cannot be imputed from genotype data, limiting inference of pharmacogenetic effects. Sequencing and targeted pharmacogenetic testing, alongside information on side effects, antidepressant dosage, depression measures, and diverse ancestry studies, would more fully capture the influence of metabolic phenotypes.

CYP2D6-guided opioid therapy for adults with cancer pain: A randomized implementation clinical trial

INTRODUCTION

The CYP2D6 enzyme metabolizes opioids commonly prescribed for cancer-related pain, and CYP2D6 polymorphisms may contribute to variability in opioid response. We evaluated the feasibility of implementing CYP2D6-guided opioid prescribing for patients with cancer and reported pilot outcome data.

METHODS

Adult patients from two cancer centers were prospectively enrolled into a hybrid implementation-effectiveness clinical trial and randomized to CYP2D6-genotype-guided opioid selection, with clinical recommendations, or usual care. Implementation metrics, including provider response, medication changes consistent with recommendations, and patient-reported pain and symptom scores at baseline and up to 8 weeks, were assessed.

RESULTS

Most (87/114, 76%) patients approached for the study agreed to participate. Of 85 patients randomized, 71% were prescribed oxycodone at baseline. The median (range) time to receive CYP2D6 test results was 10 (3-37) days; 24% of patients had physicians acknowledge genotype results in a clinic note. Among patients with CYP2D6-genotype-guided recommendations to change therapy (n = 11), 18% had a change congruent with recommendations. Among patients who completed baseline and follow-up questionnaires (n = 48), there was no difference in change in mean composite pain score (-1.01 ± 2.1 vs. -0.41 ± 2.5; p = 0.19) or symptom severity at last follow-up (3.96 ± 2.18 vs. 3.47 ± 1.78; p = 0.63) between the usual care arm (n = 26) and genotype-guided arm (n = 22), respectively.

CONCLUSION

Our study revealed high acceptance of pharmacogenetic testing as part of a clinical trial among patients with cancer pain. However, provider response to genotype-guided recommendations was low, impacting assessment of pain-related outcomes. Addressing barriers to utility of pharmacogenetics results and clinical recommendations will be critical for implementation success.

Ethnopsychopharmacology: Clinical and scientific writing pearls

The concept of ethnopsychopharmacology aims to predict or explain the pharmacologic response to psychiatric medications based on the influence of biologic and nonbiologic factors. Interactions involving these factors are complex and influence patient outcomes in health care. Pharmacists and other clinicians working in patient care environments, research, or medical education should engage in lifelong learning to enhance ethnopsychopharmacologic knowledge gaps, which ultimately may improve and individualize care across diverse populations. Through two cases, this paper provides pearls on how biogeographical ancestry and cytochrome P450 status may influence pharmacotherapy selection, dosing, or response. A third scenario highlights a publication, like many other published works, with deficiencies in how data on ancestry, race, and ethnicity are collected or reported. Current recommendations on the use of inclusive language in scientific writing are reviewed, with attention to specific examples.