Dutch Pharmacogenetics Working Group (DPWG) guideline for the gene-drug interaction between CYP2D6, CYP2C19 and non-SSRI/non-TCA antidepressants.

The Dutch Pharmacogenetics Working Group (DPWG) aims to facilitate pharmacogenetics implementation in clinical practice by developing evidence-based guidelines to optimize pharmacotherapy based on pharmacogenetic test results. The current guideline describes the gene-drug interaction between CYP2D6 and venlafaxine, mirtazapine and duloxetine. In addition, the interaction between CYP2C19 and mirtazapine and moclobemide is presented. The DPWG identified a gene-drug interaction that requires therapy adjustment for CYP2D6 and venlafaxine. However, as the side effects do not appear to be related to plasma concentrations, it is not possible to offer a substantiated advice for dose reduction. Therefore, the DPWG recommends avoiding venlafaxine for CYP2D6 poor and intermediate metabolisers. Instead, an alternative antidepressant, which is not, or to a lesser extent, metabolized by CYP2D6 is recommended. When it is not possible to avoid venlafaxine and side effects occur, it is recommended to reduce the dose and monitor the effect and side effects or plasma concentrations. No action is required for ultra-rapid metabolisers as kinetic effects are minimal and no clinical effect has been demonstrated. In addition, a gene-drug interaction was identified for CYP2D6 and mirtazapine and CYP2C19 and moclobemide, but no therapy adjustment is required as no effect regarding effectiveness or side effects has been demonstrated for these gene-drug interactions. Finally, no gene-drug interaction and need for therapy adjustment between CYP2C19 and mirtazapine and CYP2D6 and duloxetine were identified. The DPWG classifies CYP2D6 genotyping as being "potentially beneficial" for venlafaxine, indicating that genotyping prior to treatment can be considered on an individual patient basis.

Minimising Adverse Drug Reactions and Verifying Economic Legitimacy-Pharmacogenomics Implementation in Children (MARVEL- PIC): protocol for a national randomised controlled trial of pharmacogenomics implementation.

INTRODUCTION: DNA-informed prescribing (termed pharmacogenomics, PGx) is the epitome of personalised medicine. Despite international guidelines existing, its implementation in paediatric oncology remains sparse. METHODS AND ANALYSIS: Minimising Adverse Drug Reactions and Verifying Economic Legitimacy-Pharmacogenomics Implementation in Children is a national prospective, multicentre, randomised controlled trial assessing the impact of pre-emptive PGx testing for actionable PGx variants on adverse drug reaction (ADR) incidence in patients with a new cancer diagnosis or proceeding to haematopoetic stem cell transplant. All ADRs will be prospectively collected by surveys completed by parents/patients using the National Cancer Institute Pediatric Patient Reported [Ped-PRO]-Common Terminology Criteria for Adverse Events (CTCAE) (weeks 1, 6 and 12). Pharmacist will assess for causality and severity in semistructured interviews using the CTCAE and Liverpool Causality Assessment Tool. The primary outcome is a reduction in ADRs among patients with actionable PGx variants, where an ADR will be considered as any CTCAE grade 2 and above for non-haematological toxicities and any CTCAE grade 3 and above for haematological toxicities Cost-effectiveness of pre-emptive PGx (secondary outcome) will be compared with standard of care using hospital inpatient and outpatient data along with the validated Childhood Health Utility 9D Instrument. Power and statistics considerations: A sample size of 440 patients (220 per arm) will provide 80% power to detect a 24% relative risk reduction in the primary endpoint of ADRs (two-sided α=5%, 80% vs 61%), allowing for 10% drop-out. ETHICS AND DISSEMINATION: The ethics approval of the trial has been obtained from the Royal Children's Hospital Ethics Committee (HREC/89083/RCHM-2022). The ethics committee of each participating centres nationally has undertaken an assessment of the protocol and governance submission. TRIAL REGISTRATION NUMBER: NCT05667766.

Genetic polymorphisms and major bleeding risk during vitamin K antagonists treatment: The BLEEDS case-cohort.

BACKGROUND: Major bleeding occurs annually in 1%-3% of patients on vitamin K antagonists (VKAs), despite close monitoring. Genetic variants in proteins involved in VKA response may affect this risk. AIM: To determine the association of genetic variants (cytochrome P450 enzymes 2C9 [CYP2C9] and 4F2 [CYP4F2], gamma-glutamyl carboxylase [GGCX]) with major bleeding in VKA users, separately and combined, including vitamin K epoxide reductase complex subunit-1 (VKORC1). METHODS: A case-cohort study was established within the BLEEDS cohort, which includes 16,570 patients who initiated VKAs between 2012 and 2014. We selected all 326 major bleeding cases that occurred during 17,613 years of follow-up and a random subcohort of 978 patients. We determined variants in CYP2C9, CYP4F2, GGCX, VKORC1 and evaluated the interaction between variant genotypes. Hazard ratios for major bleeding with 95% confidence intervals (95% CI) were estimated by weighted Cox regression. RESULTS: Genotype was determined in 256 cases and 783 subcohort members. Phenprocoumon was the most prescribed VKA for both cases and the subcohort (78% and 75%, respectively). Patients with major bleeding were slightly older than subcohort patients. CYP4F2-TT carriership was associated with a 1.6-fold (95% CI 0.9-2.8) increased risk of major bleeding compared with CC-alleles, albeit not statistically significant. For the CYP2C9 and GGCX variants instead, the major bleeding risk was around unity. Carrying at least two variant genotypes in CYP2C9 (poor metabolizer), CYP4F2-TT, and VKORC1-AA was associated with a 4.0-fold (95%CI 1.4-11.4) increased risk, while carriers of both CYP4F2-TT and VKORC1-AA had a particularly increased major bleeding risk (hazard ratio 6.7, 95% CI 1.5-29.8) compared with carriers of CC alleles in CYP4F2 and GG in VKORC1. However, the number of major bleeding cases in carriers of multiple variants was few (8 and 5 patients, respectively). CONCLUSIONS: CYP4F2 polymorphism was associated with major bleeding, especially in combination with VKORC1 genetic variants. These variants could be considered to further personalize anticoagulant treatment.

Dutch Pharmacogenetics Working Group (DPWG) guideline for the gene-drug interaction of CYP2C9, HLA-A and HLA-B with anti-epileptic drugs.

By developing evidence-based pharmacogenetics guidelines to optimize pharmacotherapy, the Dutch Pharmacogenetics Working Group (DPWG) aims to advance the implementation of pharmacogenetics (PGx). This guideline outlines the gene-drug interaction of CYP2C9 and HLA-B with phenytoin, HLA-A and HLA-B with carbamazepine and HLA-B with oxcarbazepine and lamotrigine. A systematic review was performed and pharmacotherapeutic recommendations were developed. For CYP2C9 intermediate and poor metabolisers, the DPWG recommends lowering the daily dose of phenytoin and adjust based on effect and serum concentration after 7-10 days. For HLA-B*15:02 carriers, the risk of severe cutaneous adverse events associated with phenytoin, carbamazepine, oxcarbazepine, and lamotrigine is strongly increased. For carbamazepine, this risk is also increased in HLA-B*15:11 and HLA-A*31:01 carriers. For HLA-B*15:02, HLA-B*15:11 and HLA-A*31:01 positive patients, the DPWG recommends choosing an alternative anti-epileptic drug. If not possible, it is recommended to advise the patient to report any rash while using carbamazepine, lamotrigine, oxcarbazepine or phenytoin immediately. Carbamazepine should not be used in an HLA-B*15:02 positive patient. DPWG considers CYP2C9 genotyping before the start of phenytoin "essential" for toxicity prevention. For patients with an ancestry in which the abovementioned HLA-alleles are prevalent, the DPWG considers HLA-B*15:02 genotyping before the start of carbamazepine, phenytoin, oxcarbazepine, and lamotrigine "beneficial", as well as genotyping for HLA-B*15:11 and HLA-A*31:01 before initiating carbamazepine.

A Genome-Wide Association Study of Endoxifen Serum Concentrations and Adjuvant Tamoxifen Efficacy in Early-Stage Breast Cancer Patients.

Tamoxifen is part of the standard of care of endocrine therapy for adjuvant treatment of breast cancer. However, survival outcomes with tamoxifen are highly variable. The concentration of endoxifen, the 30-100 times more potent metabolite of tamoxifen and bioactivated by the CYP2D6 enzyme, has been described as the most relevant metabolite of tamoxifen metabolism. A genome-wide association study (GWAS) was performed with the objective to identify genetic polymorphisms associated with endoxifen serum concentration levels and clinical outcome in early-stage breast cancer patients receiving tamoxifen. A GWAS was conducted in 608 women of the CYPTAM study (NTR1509/PMID: 30120701). Germline DNA and clinical and survival characteristics were readily available. Genotyping was performed on Infinium Global Screening Array (686,082 markers) and single nucleotide polymorphism (SNP) imputation by using 1000 Genomes. Relapse-free survival during tamoxifen (RFSt) was defined the primary clinical outcome. Endoxifen serum concentration was analyzed as a continuous variable. Several genetic variants reached genome-wide significance (P value: ≤5 × 10-8). Endoxifen concentrations analysis identified 430 variants, located in TCF20 and WBP2NL genes (chromosome 22), which are in strong linkage disequilibrium with CYP2D6 variants. In the RFSt analysis, several SNP were identified (LPP gene: rs77693286, HR 18.3, 95% CI: 15.2-21.1; rs6790761, OR 18.2, 95% CI: 15.5-21.1). Endoxifen concentrations have a strong association with the chromosome 22, which contains the CYP2D6 gene.

Nonlinear Mixed-Effects Model of Z-Endoxifen Concentrations in Tamoxifen-Treated Patients from the CEPAM Cohort.

Tamoxifen is widely used in patients with hormone receptor-positive breast cancer. The polymorphic enzyme CYP2D6 is primarily responsible for metabolic activation of tamoxifen, resulting in substantial interindividual variability of plasma concentrations of its most important metabolite, Z-endoxifen. The Z-endoxifen concentration thresholds below which tamoxifen treatment is less efficacious have been proposed but not validated, and prospective trials of individualized tamoxifen treatment to achieve Z-endoxifen concentration thresholds are considered infeasible. Therefore, we aim to validate the association between Z-endoxifen concentration and tamoxifen treatment outcomes, and identify a Z-endoxifen concentration threshold of tamoxifen efficacy, using pharmacometric modeling and simulation. As a first step, the CYP2D6 Endoxifen Percentage Activity Model (CEPAM) cohort was created by pooling data from 28 clinical studies (> 7,000 patients) with measured endoxifen plasma concentrations. After cleaning, data from 6,083 patients were used to develop a nonlinear mixed-effect (NLME) model for tamoxifen and Z-endoxifen pharmacokinetics that includes a conversion factor to allow inclusion of studies that measured total endoxifen but not Z-endoxifen. The final parent-metabolite NLME model confirmed the primary role of CYP2D6, and contributions from body weight, CYP2C9 phenotype, and co-medication with CYP2D6 inhibitors, on Z-endoxifen pharmacokinetics. Future work will use the model to simulate Z-endoxifen concentrations in patients receiving single agent tamoxifen treatment within large prospective clinical trials with long-term survival to identify the Z-endoxifen concentration threshold below which tamoxifen is less efficacious. Identification of this concentration threshold would allow personalized tamoxifen treatment to improve outcomes in patients with hormone receptor-positive breast cancer.

The effect of genetic variants in the transcription factor TSPYL family on the CYP3A4 mediated cyclosporine metabolism in kidney transplant patients.

CYP3A4 activity shows considerable interindividual variability. Although studies indicate 60%-80% is heritable, common single nucleotide variants (SNVs) in CYP3A4 together only explain ~10%. Transcriptional factors, such as the testis-specific Y-encoded-like proteins (TSPYLs) family, have been reported to regulate the expression of CYP enzymes including CYP3A4 in vitro. Here, we investigated the effect of genetic variants in TSPYL on CYP3A4 activity using data from a clinical study and a human liver bank. Five SNVs (rs3828743, rs10223646, rs6909133, rs1204807, and rs1204811) in TSPYL were selected because of a reported effect on CYP3A4 expression in vitro or suggested clinical effect. For the clinical study, whole blood concentrations, clinical data, and DNA were available from 295 kidney transplant recipients participating in the prospective MECANO study. A multivariate pharmacokinetic model adjusted for body weight, steroid treatment, and CYP3A4 genotype was used to assess the effect of the genetic variants on cyclosporine clearance. In multivariate analysis, homozygous carriers of rs3828743 had a 18% lower cyclosporin clearance compared to the wild-type and heterozygous patients (28.72 vs. 35.03 L/h, p = 0.018) indicating a lower CYP3A4 activity and an opposite direction of effect compared to the previously reported increased CYP3A4 expression. To validate, we tested associations between rs3828743 and CYP3A4 mRNA and protein expression as well as enzyme activity with data from a liver bank (n = 150). No association with any of these end points was observed. In conclusion, the totality of evidence is not in support of a significant role for TSPYL SNV rs3828743 in explaining variability in CYP3A4 activity.

Personalized Chronomodulated 5-Fluorouracil Treatment: A Physiologically-Based Pharmacokinetic Precision Dosing Approach for Optimizing Cancer Therapy.

The discovery of circadian clock genes greatly amplified the study of diurnal variations impacting cancer therapy, transforming it into a rapidly growing field of research. Especially, use of chronomodulated treatment with 5-fluorouracil (5-FU) has gained significance. Studies indicate high interindividual variability (IIV) in diurnal variations in dihydropyrimidine dehydrogenase (DPD) activity - a key enzyme for 5-FU metabolism. However, the influence of individual DPD chronotypes on chronomodulated therapy remains unclear and warrants further investigation. To optimize precision dosing of chronomodulated 5-FU, this study aims to: (i) build physiologically-based pharmacokinetic (PBPK) models for 5-FU, uracil, and their metabolites, (ii) assess the impact of diurnal variation on DPD activity, (iii) estimate individual DPD chronotypes, and (iv) personalize chronomodulated 5-FU infusion rates based on a patient's DPD chronotype. Whole-body PBPK models were developed with PK-Sim(R) and MoBi(R). Sinusoidal functions were used to incorporate variations in enzyme activity and chronomodulated infusion rates as well as to estimate individual DPD chronotypes from DPYD mRNA expression or DPD enzymatic activity. Four whole-body PBPK models for 5-FU, uracil, and their metabolites were established utilizing data from 41 5-FU and 10 publicly available uracil studies. IIV in DPD chronotypes was assessed and personalized chronomodulated administrations were developed to achieve (i) comparable 5-FU peak plasma concentrations, (ii) comparable 5-FU exposure, and (iii) constant 5-FU plasma levels via "noise cancellation" chronomodulated infusion. The developed PBPK models capture the extent of diurnal variations in DPD activity and can help investigate individualized chronomodulated 5-FU therapy through testing alternative personalized dosing strategies.

Dutch Pharmacogenetics Working Group (DPWG) guideline for the gene-drug interaction between CYP2D6, CYP3A4 and CYP1A2 and antipsychotics.

The Dutch Pharmacogenetics Working Group (DPWG) aims to facilitate pharmacogenetics implementation in clinical practice by developing evidence-based guidelines to optimize pharmacotherapy. A guideline describing the gene-drug interaction between the genes CYP2D6, CYP3A4 and CYP1A2 and antipsychotics is presented here. The DPWG identified gene-drug interactions that require therapy adjustments when respective genotype is known for CYP2D6 with aripiprazole, brexpiprazole, haloperidol, pimozide, risperidone and zuclopenthixol, and for CYP3A4 with quetiapine. Evidence-based dose recommendations were obtained based on a systematic review of published literature. Reduction of the normal dose is recommended for aripiprazole, brexpiprazole, haloperidol, pimozide, risperidone and zuclopenthixol for CYP2D6-predicted PMs, and for pimozide and zuclopenthixol also for CYP2D6 IMs. For CYP2D6 UMs, a dose increase or an alternative drug is recommended for haloperidol and an alternative drug or titration of the dose for risperidone. In addition, in case of no or limited clinical effect, a dose increase is recommended for zuclopenthixol for CYP2D6 UMs. Even though evidence is limited, the DPWG recommends choosing an alternative drug to treat symptoms of depression or a dose reduction for other indications for quetiapine and CYP3A4 PMs. No therapy adjustments are recommended for the other CYP2D6 and CYP3A4 predicted phenotypes. In addition, no action is required for the gene-drug combinations CYP2D6 and clozapine, flupentixol, olanzapine or quetiapine and also not for CYP1A2 and clozapine or olanzapine. For identified gene-drug interactions requiring therapy adjustments, genotyping of CYP2D6 or CYP3A4 prior to treatment should not be considered for all patients, but on an individual patient basis only.

IGF1 and Insulin Receptor Single Nucleotide Variants Associated with Response in HER2-Negative Breast Cancer Patients Treated with Neoadjuvant Chemotherapy with or without a Fasting Mimicking Diet (BOOG 2013-04 DIRECT Trial).

AIM: We aimed to investigate associations between IGF1R and INSR single nucleotide variants (SNVs) and clinical response in patients with breast cancer treated with neoadjuvant chemotherapy with or without a fasting mimicking diet (FMD) from the DIRECT trial (NCT02126449), since insulin-like growth factor 1 (IGF1) and the insulin pathway are heavily involved in tumor growth and progression. METHODS: Germline DNA from 113 patients was tested for 17 systematically selected candidate SNVs in IGF1R and INSR with pathological and radiological response. RESULTS: IGF1R variants A > G (rs3743259) and G > A (rs3743258) are associated with worse pathological response compared to reference alleles p = 0.002, OR = 0.42 (95%CI: 0.24; 0.73); p = 0.0016; OR = 0.40 (95%CI: 0.23; 0.70). INSR T > C (rs1051690) may be associated with worse radiological response p = 0.02, OR = 2.92 (95%CI: 1.16; 7.36), although not significant after Bonferroni correction. Exploratory interaction analysis suggests that IGF1R SNVs rs2684787 and rs2654980 interact negatively with the FMD group regarding radiological response p = 0.036, OR = 5.13 (95%CI: 1.12; 23.63); p = 0.024, OR = 5.71 (95%CI: 1.26; 25.85). CONCLUSIONS: The IGF1R variants rs3743259 and rs3743258 are negatively associated with pathological response in this cohort, suggesting potential relevance as a predictive biomarker. Further research is needed to validate these findings and elucidate the underlying mechanisms and interaction with FMD.

Study protocol of the HD-MED study aiming to personalize drug treatment in Huntington's disease: a longitudinal, observational study to assess medication use and efficacy in relation to pharmacogenetics.

Background: Huntington's disease (HD) is a hereditary, neurodegenerative disorder characterized by motor, cognitive, and psychiatric symptoms. Currently, HD can only be managed symptomatically, including a large variety of prescribed drugs. Many HD patients experience negative medication effects (e.g. side effects or non-response). Pharmacogenetic (PGx) studies show how genetic variation affects both medication efficacy and toxicity and holds the potential to improve these outcomes of drug treatment. Primary objective: To classify the effect of the PGx profile of CYP2C19 and CYP2D6 in HD gene expansion carriers on negative medication effects of HD-related medication. Design: Multicenter, observational study with 1-year follow-up. Adult HD gene expansion carriers who use one or more HD-related medications are eligible to participate. Methods and analysis: A detailed overview of medication use, medication efficacy, and side effects is retrospectively and prospectively collected via medication diaries, questionnaires, phone calls, and pharmacy medication verification schemes. PGx analysis on whole blood-extracted DNA is performed with Agena Bioscience VeriDose® Core Panel and long-range polymerase chain reaction copy number variation analysis. Per the study protocol-defined negative medication effects in HD gene expansion carriers with a genotype predicted poor or ultrarapid metabolizer phenotype will be compared with HD gene expansion carriers with a predicted intermediate and normal metabolizer phenotype. Frequencies will be analyzed via χ2 and logistic multivariate regression analysis. In addition, we summarize in this manuscript HD-relevant PGx prescription recommendations to improve drug therapy. Ethics: The original study protocol was approved by the medical research ethics committee Leiden Den Haag Delft on 26 November 2019. Discussion: HD-MED is a low-risk study that will generate personalized PGx results that can immediately be implemented in clinical practice, thus potentially improving pharmacovigilance and patients' quality of life. Registration: This study is registered in the International Clinical Trial Registry Platform under registration number NL8251, URL https://trialsearch.who.int/Trial2.aspx?TrialID=NL8251.

Implementation of pre-emptive testing of a pharmacogenomic panel in clinical practice: Where do we stand?

Adverse drug reactions (ADRs) account for a large proportion of hospitalizations among adults and are more common in multimorbid patients, worsening clinical outcomes and burdening healthcare resources. Over the past decade, pharmacogenomics has been developed as a practical tool for optimizing treatment outcomes by mitigating the risk of ADRs. Some single-gene reactive tests are already used in clinical practice, including the DPYD test for fluoropyrimidines, which demonstrates how integrating pharmacogenomic data into routine care can improve patient safety in a cost-effective manner. The evolution from reactive single-gene testing to comprehensive pre-emptive genotyping panels holds great potential for refining drug prescribing practices. Several implementation projects have been conducted to test the feasibility of applying different genetic panels in clinical practice. Recently, the results of a large prospective randomized trial in Europe (the PREPARE study by Ubiquitous Pharmacogenomics consortium) have provided the first evidence that prospective application of a pre-emptive pharmacogenomic test panel in clinical practice, in seven European healthcare systems, is feasible and yielded a 30% reduction in the risk of developing clinically relevant toxicities. Nevertheless, some important questions remain unanswered and will hopefully be addressed by future dedicated studies. These issues include the cost-effectiveness of applying a pre-emptive genotyping panel, the role of multiple co-medications, the transferability of currently tested pharmacogenetic guidelines among patients of non-European origin and the impact of rare pharmacogenetic variants that are not detected by currently used genotyping approaches.

Survival of Patients With Cancer With DPYD Variant Alleles and Dose-Individualized Fluoropyrimidine Therapy-A Matched-Pair Analysis.

PURPOSE: DPYD-guided fluoropyrimidine dosing improves patient safety in carriers of DPYD variant alleles. However, the impact on treatment outcome in these patients is largely unknown. Therefore, progression-free survival (PFS) and overall survival (OS) were compared between DPYD variant carriers treated with a reduced dose and DPYD wild-type controls receiving a full fluoropyrimidine dose in a retrospective matched-pair survival analysis. METHODS: Data from a prospective multicenter study (ClinicalTrials.gov identifier: NCT02324452) in which DPYD variant carriers received a 25% (c.1236G>A and c.2846A>T) or 50% (DPYD*2A and c.1679T>G) reduced dose and data from DPYD variant carriers treated with a similarly reduced dose of fluoropyrimidines identified during routine clinical care were obtained. Each DPYD variant carrier was matched to three DPYD wild-type controls treated with a standard dose. Survival analyses were performed using Kaplan-Meier estimates and Cox regression. RESULTS: In total, 156 DPYD variant carriers and 775 DPYD wild-type controls were available for analysis. Sixty-one c.1236G>A, 25 DPYD*2A, 13 c.2846A>T, and-when pooled-93 DPYD variant carriers could each be matched to three unique DPYD wild-type controls. For pooled DPYD variant carriers, PFS (hazard ratio [HR], 1.23; 95% CI, 1.00 to 1.51; P = .053) and OS (HR, 0.95; 95% CI, 0.75 to 1.51; P = .698) were not negatively affected by DPYD-guided dose individualization. In the subgroup analyses, a shorter PFS (HR, 1.43; 95% CI, 1.10 to 1.86; P = .007) was found in c.1236G>A variant carriers, whereas no differences were found for DPYD*2A and c.2846A>T carriers. CONCLUSION: In this exploratory analysis, DPYD-guided fluoropyrimidine dosing does not negatively affect PFS and OS in pooled DPYD variant carriers. Close monitoring with early dose modifications based on toxicity is recommended, especially for c.1236G>A carriers receiving a reduced starting dose.

UGT1A1 genotype-guided dosing of irinotecan: time to prioritize patient safety.

Tweetable abstract Pretreatment UGT1A1 genotyping and a 70% irinotecan dose intensity in poor metabolizers is safe, feasible, cost-effective and essential for safe irinotecan treatment in cancer patients. It is time to update guidelines to swiftly enable the implementation of UGT1A1 genotype-guided irinotecan dosing in routine oncology care.

Pharmacokinetic profile of irinotecan in patients with chronic kidney disease: Two cases and literature review.

AIMS: There are limited pharmacokinetic data on the use of irinotecan in patients with reduced glomerular filtration rate (GFR) and no haemodialysis. In this case report, we present 2 cases and review the current literature. METHODS: The dose of irinotecan in both patients was reduced pre-emptively due to reduced GFR. The first patient had her irinotecan dose reduced to 50%, but was nevertheless admitted to hospital because of irinotecan-induced toxicity, including gastrointestinal toxicity and neutropenic fever. The dose was reduced further to 40% for the second cycle; however, the patient was again admitted to the hospital, and irinotecan was stopped indefinitely. The second patient also had his irinotecan dose reduced to 50% and was admitted to the emergency department for gastrointestinal toxicity after the first cycle. However, irinotecan could be administered in the same dose in later cycles. RESULTS: The area under the curve to infinity of irinotecan and SN-38 in the first patient were comparable to those of an individual receiving 100% dose intensity. The area under the curve to infinity of irinotecan and SN-38 in patient 2 in both cycles were slightly less than reference values. Furthermore, clearance values of irinotecan and SN-38 in our patients were comparable to those without renal impairment. CONCLUSION: Our case report suggests that reduced GFR may not significantly affect the clearance of irinotecan and SN-38, but can still result in clinical toxicity. Reduced initial dosing seems indicated in this patient population. Further research is needed to fully understand the relationship between reduced GFR, pharmacokinetics, and toxicity of irinotecan and SN-38.

Economic evaluation of pharmacogenomic-guided antiplatelet treatment in Spanish patients suffering from acute coronary syndrome participating in the U-PGx PREPARE study.

BACKGROUND: Cardiovascular diseases and especially Acute Coronary Syndrome (ACS) constitute a major health issue impacting millions of patients worldwide. Being a leading cause of death and hospital admissions in many European countries including Spain, it accounts for enormous amounts of healthcare expenditures for its management. Clopidogrel is one of the oldest antiplatelet medications used as standard of care in ACS. METHODS: In this study, we performed an economic evaluation study to estimate whether a genome-guided clopidogrel treatment is cost-effective compared to conventional one in a large cohort of 243 individuals of Spanish origin suffering from ACS and treated with clopidogrel. Data were derived from the U-PGx PREPARE clinical trial. Effectiveness was measured as survival of individuals while study data on safety and efficacy, as well as on resource utilization associated with each adverse drug reaction were used to measure costs to treat these adverse drug reactions. A generalized linear regression model was used to estimate cost differences for both study groups. RESULTS: Based on our findings, PGx-guided treatment group is cost-effective. PGx-guided treatment demonstrated to have 50% less hospital admissions, reduced emergency visits and almost 13% less ADRs compared to the non-PGx approach with mean QALY 1.07 (95% CI, 1.04-1.10) versus 1.06 (95% CI, 1.03-1.09) for the control group, while life years for both groups were 1.24 (95% CI, 1.20-1.26) and 1.23 (95% CI, 1.19-1.26), respectively. The mean total cost of PGx-guided treatment was 50% less expensive than conventional therapy with clopidogrel [€883 (95% UI, €316-€1582), compared to €1,755 (95% UI, €765-€2949)]. CONCLUSION: These findings suggest that PGx-guided clopidogrel treatment represents a cost-effective option for patients suffering from ACS in the Spanish healthcare setting.

The impact of CYP2C19 genotype on phenoconversion by concomitant medication.

Introduction: Pharmacogenetics-informed drug prescribing is increasingly applied in clinical practice. Typically, drug metabolizing phenotypes are determined based on genetic test results, whereupon dosage or drugs are adjusted. Drug-drug-interactions (DDIs) caused by concomitant medication can however cause mismatches between predicted and observed phenotypes (phenoconversion). Here we investigated the impact of CYP2C19 genotype on the outcome of CYP2C19-dependent DDIs in human liver microsomes. Methods: Liver samples from 40 patients were included, and genotyped for CYP2C19*2, *3 and *17 variants. S-mephenytoin metabolism in microsomal fractions was used as proxy for CYP2C19 activity, and concordance between genotype-predicted and observed CYP2C19 phenotype was examined. Individual microsomes were subsequently co-exposed to fluvoxamine, voriconazole, omeprazole or pantoprazole to simulate DDIs. Results: Maximal CYP2C19 activity (Vmax) in genotype-predicted intermediate metabolizers (IMs; *1/*2 or *2/*17), rapid metabolizers (RMs; *1/*17) and ultrarapid metabolizers (UMs; *17/*17) was not different from Vmax of predicted normal metabolizers (NMs; *1/*1). Conversely, CYP2C19*2/*2 genotyped-donors exhibited Vmax rates ∼9% of NMs, confirming the genotype-predicted poor metabolizer (PM) phenotype. Categorizing CYP2C19 activity, we found a 40% concordance between genetically-predicted CYP2C19 phenotypes and measured phenotypes, indicating substantial phenoconversion. Eight patients (20%) exhibited CYP2C19 IM/PM phenotypes that were not predicted by their CYP2C19 genotype, of which six could be linked to the presence of diabetes or liver disease. In subsequent DDI experiments, CYP2C19 activity was inhibited by omeprazole (-37% ± 8%), voriconazole (-59% ± 4%) and fluvoxamine (-85% ± 2%), but not by pantoprazole (-2 ± 4%). The strength of CYP2C19 inhibitors remained unaffected by CYP2C19 genotype, as similar percental declines in CYP2C19 activity and comparable metabolism-dependent inhibitory constants (Kinact/KI) of omeprazole were observed between CYP2C19 genotypes. However, the consequences of CYP2C19 inhibitor-mediated phenoconversion were different between CYP2C19 genotypes. In example, voriconazole converted 50% of *1/*1 donors to a IM/PM phenotype, but only 14% of *1/*17 donors. Fluvoxamine converted all donors to phenotypic IMs/PMs, but *1/*17 (14%) were less likely to become PMs than *1/*1 (50%) or *1/*2 and *2/*17 (57%). Conclusion: This study suggests that the differential outcome of CYP2C19-mediated DDIs between genotypes are primarily dictated by basal CYP2C19 activity, that may in part be predicted by CYP2C19 genotype but likely also depends on disease-related factors.

Physiologically-based pharmacokinetic modeling of quinidine to establish a CYP3A4, P-gp, and CYP2D6 drug-drug-gene interaction network.

The antiarrhythmic agent quinidine is a potent inhibitor of cytochrome P450 (CYP) 2D6 and P-glycoprotein (P-gp) and is therefore recommended for use in clinical drug-drug interaction (DDI) studies. However, as quinidine is also a substrate of CYP3A4 and P-gp, it is susceptible to DDIs involving these proteins. Physiologically-based pharmacokinetic (PBPK) modeling can help to mechanistically assess the absorption, distribution, metabolism, and excretion processes of a drug and has proven its usefulness in predicting even complex interaction scenarios. The objectives of the presented work were to develop a PBPK model of quinidine and to integrate the model into a comprehensive drug-drug(-gene) interaction (DD(G)I) network with a diverse set of CYP3A4 and P-gp perpetrators as well as CYP2D6 and P-gp victims. The quinidine parent-metabolite model including 3-hydroxyquinidine was developed using pharmacokinetic profiles from clinical studies after intravenous and oral administration covering a broad dosing range (0.1-600 mg). The model covers efflux transport via P-gp and metabolic transformation to either 3-hydroxyquinidine or unspecified metabolites via CYP3A4. The 3-hydroxyquinidine model includes further metabolism by CYP3A4 as well as an unspecific hepatic clearance. Model performance was assessed graphically and quantitatively with greater than 90% of predicted pharmacokinetic parameters within two-fold of corresponding observed values. The model was successfully used to simulate various DD(G)I scenarios with greater than 90% of predicted DD(G)I pharmacokinetic parameter ratios within two-fold prediction success limits. The presented network will be provided to the research community and can be extended to include further perpetrators, victims, and targets, to support investigations of DD(G)Is.