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The in vitro diagnostic medical devices regulation (IVDR) will take effect in May 2022. This regulation has a large impact on both the manufacturers of in vitro diagnostic medical devices (IVD) and clinical laboratories. For clinical laboratories, the IVDR poses restrictions on the use of laboratory developed tests (LDTs). To provide a uniform interpretation of the IVDR for colleagues in clinical practice, the IVDR Task Force was created by the scientific societies of laboratory specialties in the Netherlands. A guidance document with explanations and interpretations of relevant passages of the IVDR was drafted to help laboratories prepare for the impact of this new legislation. Feedback from interested parties and stakeholders was collected and used to further improve the document. Here we would like to present our approach to our European colleagues and inform them about the impact of the IVDR and, importantly we would like to present potentially useful approaches to fulfill the requirements of the IVDR for LDTs.

Pharmacogenomic drug labels in the Summary of Product Characteristics (SmPC) provide an instrument for clinical implementation of pharmacogenomics. We compared pharmacogenomic guidance by Clinical Pharmacogenetics Implementation Consortium (CPIC), Dutch Pharmacogenetics Working Group (DPWG), the US Food and Drug Administration (FDA), and by the European agencies the European Medicines Agency (EMA), College ter Beoordeling van Geneesmiddelen Medicines Evaluation Board (CBG-MEB), and Federal Institute for Drugs and Medical Devices (FIDMD), collectively assigned as EMA/FIDMD+MEB shortened as EMA/FM. Of 54 drugs with an actionable gene-drug interaction in the CPIC and DPWG guidelines, only 50% had actionable pharmacogenomic information in the SmPCs and the agencies were in agreement in only 18% of the cases. We further compared 450 additional drugs, lacking CPIC or DPWG guidance, and found 126 actionable gene-drug labels by the FDA and/or the EMA/FM. Based on these 126 drugs in addition to the 54 above, the consensus of actionable pharmacogenomic labeling between the FDA and the EMA/FM was only 54%. In conclusion, guidelines provided by CPIC/DPWG are only partly implemented into the SmPCs and the implementation of pharmacogenomic drug labels into the clinics would strongly gain from a higher extent of consensus between agencies.

Immunosuppressive therapy is pivotal for sustained allograft and patient survival after renal transplantation. However, optimally balanced immunosuppressive therapy is challenged by between-patient and within-patient pharmacokinetic (PK) variability. This could warrant the application of personalised dosing strategies to optimise individual patient outcomes. Pharmacometrics, the science that investigates the xenobiotic-biotic interplay using computer-aided mathematical modelling, provides options to describe and quantify this PK variability and enables identification of patient characteristics affecting immunosuppressant PK and treatment outcomes. Here, we review and critically appraise the available pharmacometric model-informed dosing solutions for the typical immunosuppressants in modern renal transplantation, to guide their initial and subsequent dosing.

Pharmacogenomics is a key component of personalized medicine that promises safer and more effective drug treatment by individualizing drug choice and dose based on genetic profiles. In clinical practice, genetic biomarkers are used to categorize patients into *-alleles to predict CYP450 enzyme activity and adjust drug dosages accordingly. However, this approach leaves a large part of variability in drug response unexplained. Here, we present a proof-of-concept approach that uses continuous-scale (instead of categorical) assignments to predict enzyme activity. We used full CYP2D6 gene sequences obtained with long-read amplicon-based sequencing and cytochrome P450 (CYP) 2D6-mediated tamoxifen metabolism data from a prospective study of 561 patients with breast cancer to train a neural network. The model explained 79% of interindividual variability in CYP2D6 activity compared to 54% with the conventional *-allele approach, assigned enzyme activities to known alleles with previously reported effects, and predicted the activity of previously uncharacterized combinations of variants. The results were replicated in an independent cohort of tamoxifen-treated patients (model R-2 adjusted = 0.66 versus *-allele R-2 adjusted = 0.35) and a cohort of patients treated with the CYP2D6 substrate venlafaxine (model R2 adjusted = 0.64 versus *-allele R-2 adjusted = 0.55). Human embryonic kidney cells were used to confirm the effect of five genetic variants on metabolism of the CYP2D6 substrate bufuralol in vitro. These results demonstrate the advantage of a continuous scale and a completely phased genotype for prediction of CYP2D6 enzyme activity and could potentially enable more accurate prediction of individual drug response.

Imatinib has a mild toxicity profile, although severe adverse events may develop. In this pharmacogenetic pathway analysis the need for dose reduction and cessation of therapy was tested for an association with single nucleotide polymorphisms (SNPs) in genes related to imatinib pharmacology. Retrospective data from 315 patients with a gastrointestinal stromal tumor who received imatinib 400 mg o.d. was associated with 36 SNPs. SNPs that showed a trend in univariate testing were tested in a multivariate model with clinical factors and correction for multiple testing was performed. Dose reduction was associated with carriership of the A-allele in rs2231137 in ABCG2 (OR 7.35, p = 0.0002) and two C-alleles in rs762551 in CYP1A2 (OR 7.12, p = 0.001). Results remained significant after correction for multiple testing. Therapy cessation did not show an association with any of the tested SNPs. These results may help identifying patients at increased risk for toxicity who could benefit from intensified follow-up.

Introduction: Tamoxifen dominates the anti-estrogenic therapy in the early and metastatic breast cancer setting. Tamoxifen has a complex metabolism, being mainly metabolized by CYP2D6 into its 30-100 times more potent metabolite, endoxifen. Recently, a phase I study in which endoxifen as an orally z-endoxifen hydrochloride has been successfully evaluated. Areas covered: the principal pharmacogenetic and non-genetic differences in the pharmacology of tamoxifen and endoxifen are evaluated. To this end, references from PubMed, Embase or Web of Science, among others, were reviewed As non-genetic factors, important differences and similarities such age, or adherence to tamoxifen therapy are comprehensively illustrated. Additionally, since CYP2D6 genotypes are considered the main limitation of tamoxifen, many studies have investigated the association between the worsened clinical outcomes in patients with non-functional CYP2D6 genotypes. In this review, an overview of the research on this field is presented. Also, a summary describing the literature about individualizing tamoxifen therapy with endoxifen concentrations and its limitations is listed. Expert opinion: z-endoxifen hydrochloride is only investigated in the metastatic setting, still more research is required before its place in therapeutics is known. Similarly, monitoring tamoxifen efficacy based on endoxifen concentrations might not be overall recommended due to the limited evidence available.

Aim: To study the performance of a clinical pharmacogenetic model for the prediction of nonresponse in rheumatoid arthritis (RA) patients treated with methotrexate (MTX) in combination with other synthetic or biologic disease-modifying anti-rheumatic drugs . This prediction model includes gender, smoking status, rheumatoid factor positivity and four genetic variants in AMPD1 (rs17602729), ATIC (rs2372536), ITPA (rs1127354) and MTHFD1 (rs17850560). Methods: A total of 314 RA patients from three Dutch studies were retrospectively included. Eligible patients were adults diagnosed with RA and had a treatment duration with MTX and follow-up for at least two study evaluation visits. Prediction model risk scores at the first and second evaluation were calculated and compared with the actual nonresponse (disease activity score >2.4). Regression and receiver operating characteristic curve analyses of the prediction model were performed. Also, the sensitivity, specificity and the positive and negative predictive values (PPV and NPV) were determined. Results: The receiver operating characteristic area under the curve was 75% at first and 70% after second evaluation. At the second evaluation, prediction nonresponse had a sensitivity of 67% (CI: 54–78%), specificity of 69% (CI: 60–77%), PPV of 52% (CI: 45–60%) and NPV of 80% (CI: 73–85%). Conclusions: This study demonstrates that the clinical pharmacogenetic model has an inadequate performance for the prediction of nonresponse to MTX in RA patients treated with combination therapies.

Aims Meltdose tacrolimus (Envarsus) is marketed as a formulation with a more consistent exposure. Due to the narrow therapeutic window, therapeutic drug monitoring is essential to maintain adequate exposure. The primary objective of this study was to develop a population pharmacokinetic (PK) model of Envarsus among liver transplant patients and select a limited sampling strategy (LSS) for AUC estimation. The secondary objective was to investigate potential covariates including CYP3A/IL genotype suitable for initial dose optimization when converting to Envarsus. Methods Adult liver transplant patients were converted from prolonged release tacrolimus (Advagraf) to Envarsus and blood samples were obtained using whole blood and dried blood spot sampling. Subsequently the population PK parameters were estimated using nonlinear‐mixed effect modelling. Demographic factors, and recipient and donor CYP3A4, CYP3A5, IL‐6, ‐10 and ‐18 genotype were tested as potential covariates to explain interindividual variability. Results Fifty‐five patients were included. A 2‐compartment model with delayed absorption was the most suitable to describe population PK parameters. The population PK parameters were as follows: clearance, 3.27 L/h; intercompartmental clearance, 9.6 L/h; volume of distribution of compartments 1 and 2, 95 and 500 L, respectively. No covariates were found to significantly decrease interindividual variability. The best 3‐point LSS was t = 0,4,8 with a median bias of 1.8% (−12.5–12.5). Conclusions The LSS can be used to adequately predict the AUC. No clinically relevant covariates known to influence the PK of Envarsus, including CYP3A status, were identified and therefore do not seem useful for initial dose optimization.

Background Iohexol plasma clearance-based glomerular filtration rate (GFR) determination provides an accurate method for renal function evaluation. This technique is increasingly advocated for clinical situations that dictate highly accurate renal function assessment, as an alternative to conventional serum creatinine-based methods with limited accuracy or poor feasibility. In the renal transplantation setting, this particularly applies to living renal transplant donor eligibility screening, renal transplant function monitoring and research purposes. The dependency of current iohexol GFR estimation techniques on extensive sampling, however, has limited its clinical application. We developed a population pharmacokinetic model and limited sampling schedules, implemented in the online InsightRX precision dosing platform, to facilitate pragmatic iohexol GFR assessment. Methods Iohexol concentrations (n = 587) drawn 5 min to 4 h after administration were available from 67 renal transplant recipients and 41 living renal transplant donor candidates with measured iohexol GFRs of 27–117 mL/min/1.73 m2. These were split into a model development (n = 72) cohort and an internal validation (n = 36) cohort. External validation was performed with 1040 iohexol concentrations from 268 renal transplant recipients drawn between 5 min and 4 h after administration, and extended iohexol curves up to 24 h from 11 random patients with impaired renal function. Limited sampling schedules based on one to four blood draws within 4 h after iohexol administration were evaluated in terms of bias and imprecision, using the mean relative prediction error and mean absolute relative prediction error. The total deviation index and percentage of limited sampling schedule-based GFR predictions within ± 10% of those of the full model (P10) were assessed to aid interpretation. Results Iohexol pharmacokinetics was best described with a two-compartmental first-order elimination model, allometrically scaled to fat-free mass, with patient type as a covariate on clearance and the central distribution volume. Model validity was confirmed during the internal and external validation. Various limited sampling schedules based on three to four blood draws within 4 h showed excellent predictive performance (mean relative prediction error < ± 0.5%, mean absolute relative prediction error < 3.5%, total deviation index < 5.5%, P10 > 97%). The best limited sampling schedules based on three to four blood draws within 3 h showed reduced predictive performance (mean relative prediction error < ± 0.75%, mean absolute relative prediction error < 5.5%, total deviation index < 9.5%, P10 ≥ 85%), but may be considered for their enhanced clinical feasibility when deemed justified. Conclusions Our online pharmacometric tool provides an accurate, pragmatic, and ready-to-use technique for measured GFR-based renal function evaluation for clinical situations where conventional methods lack accuracy or show limited feasibility. Additional adaptation and validation of our model and limited sampling schedules for renal transplant recipients with GFRs below 30 mL/min is warranted before considering this technique in these patients. Supplementary Information The online version contains supplementary material available at 10.1007/s40262-021-00998-z.

Background Mitotane is the only approved treatment for patients with adrenocortical carcinoma (ACC). A better explanation for the variability in the pharmacokinetics (PK) of mitotane, and the optimization and individualization of mitotane treatment, is desirable for patients. Objectives This study aims to develop a population PK (PopPK) model to characterize and predict the PK profiles of mitotane in patients with ACC, as well as to explore the effect of genetic variation on mitotane clearance. Ultimately, we aimed to facilitate mitotane dose optimization and individualization for patients with ACC. Methods Mitotane concentration and dosing data were collected retrospectively from the medical records of patients with ACC taking mitotane orally and participating in the Dutch Adrenal Network. PopPK modelling analysis was performed using NONMEM (version 7.4.1). Genotypes of drug enzymes and transporters, patient demographic information, and clinical characteristics were investigated as covariates. Subsequently, simulations were performed for optimizing treatment regimens. Results A two-compartment model with first-order absorption and elimination best described the PK data of mitotane collected from 48 patients. Lean body weight (LBW) and genotypes of CYP2C19*2 (rs4244285), SLCO1B3 699A>G (rs7311358) and SLCO1B1 571T>C (rs4149057) were found to significantly affect mitotane clearance (CL/F), which decreased the coefficient of variation (CV%) of the random inter-individual variability of CL/F from 67.0 to 43.0%. Fat amount (i.e. body weight − LBW) was found to significantly affect the central distribution volume. Simulation results indicated that determining the starting dose using the developed model is beneficial in terms of shortening the period to reach the therapeutic target and limit the risk of toxicity. A regimen that can effectively maintain mitotane concentration within 14–20 mg/L was established. Conclusions A two-compartment PopPK model well-characterized mitotane PK profiles in patients with ACC. The CYP2C19 enzyme and SLCO1B1 and SLCO1B3 transporters may play roles in mitotane disposition. The developed model is beneficial in terms of optimizing mitotane treatment schedules and individualizing the initial dose for patients with ACC. Further validation of these findings is still required. Electronic supplementary material The online version of this article (10.1007/s40262-020-00913-y) contains supplementary material, which is available to authorized users.

When mycophenolic acid (MPA) was originally marketed for immunosuppressive therapy, fixed doses were recommended by the manufacturer. Awareness of the potential for a more personalized dosing has led to development of methods to estimate MPA area under the curve based on the measurement of drug concentrations in only a few samples. This approach is feasible in the clinical routine and has proven successful in terms of correlation with outcome. However, the search for superior correlates has continued, and numerous studies in search of biomarkers that could better predict the perfect dosage for the individual patient have been published. As it was considered timely for an updated and comprehensive presentation of consensus on the status for personalized treatment with MPA, this report was prepared following an initiative from members of the International Association of Therapeutic Drug Monitoring and Clinical Toxicology (IATDMCT). Topics included are the criteria for analytics, methods to estimate exposure including pharmacometrics, the potential influence of pharmacogenetics, development of biomarkers, and the practical aspects of implementation of target concentration intervention. For selected topics with sufficient evidence, such as the application of limited sampling strategies for MPA area under the curve, graded recommendations on target ranges are presented. To provide a comprehensive review, this report also includes updates on the status of potential biomarkers including those which may be promising but with a low level of evidence. In view of the fact that there are very few new immunosuppressive drugs under development for the transplant field, it is likely that MPA will continue to be prescribed on a large scale in the upcoming years. Discontinuation of therapy due to adverse effects is relatively common, increasing the risk for late rejections, which may contribute to graft loss. Therefore, the continued search for innovative methods to better personalize MPA dosage is warranted. Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved

The continuous development of new genotyping technologies requires awareness of their potential advantages and limitations concerning utility for pharmacogenomics (PGx). In this review, we provide an overview of technologies that can be applied in PGx research and clinical practice. Most commonly used are single nucleotide variant (SNV) panels which contain a pre-selected panel of genetic variants. SNV panels offer a short turnaround time and straightforward interpretation, making them suitable for clinical practice. However, they are limited in their ability to assess rare and structural variants. Next-generation sequencing (NGS) and long-read sequencing are promising technologies for the field of PGx research. Both NGS and long-read sequencing often provide more data and more options with regard to deciphering structural and rare variants compared to SNV panels—in particular, in regard to the number of variants that can be identified, as well as the option for haplotype phasing. Nonetheless, while useful for research, not all sequencing data can be applied to clinical practice yet. Ultimately, selecting the right technology is not a matter of fact but a matter of choosing the right technique for the right problem.

Phenoconversion is the mismatch between the individual’s genotype-based prediction of drug metabolism and the true capacity to metabolize drugs due to nongenetic factors. While the concept of phenoconversion has been described in narrative reviews, no systematic review is available. A systematic review was conducted to investigate factors contributing to phenoconversion and the impact on cytochrome P450 metabolism. Twenty-seven studies met the inclusion criteria and were incorporated in this review, of which 14 demonstrate phenoconversion for a specific genotype group. Phenoconversion into a lower metabolizer phenotype was reported for concomitant use of CYP450-inhibiting drugs, increasing age, cancer, and inflammation. Phenoconversion into a higher metabolizer phenotype was reported for concomitant use of CYP450 inducers and smoking. Moreover, alcohol, pregnancy, and vitamin D exposure are factors where study data suggested phenoconversion. The studies reported genotype–phenotype discrepancies, but the impact of phenoconversion on the effectiveness and toxicity in the clinical setting remains unclear. In conclusion, phenoconversion is caused by both extrinsic factors and patient- and disease-related factors. The mechanism(s) behind and the extent to which CYP450 metabolism is affected remain unexplored. If studied more comprehensively, accounting for phenoconversion may help to improve our ability to predict the individual CYP450 metabolism and personalize drug treatment.

Tacrolimus is metabolized by CYP3A4 and CYP3A5 enzymes. Patients expressing CYP3A5 (in Caucasian patients about 15% of the population but more frequent in African Americans and Asians) have a dose requirement that is around 50% higher than non-expressers to reach the target concentration. CYP3A5 expressers can be considered fast metabolizers. The trough concentration/dose (C-0/D) ratio of tacrolimus has recently been proposed as a prognostic marker for poor outcome after kidney transplantation. Patients with a low C-0/D ratio (also referred to as fast metabolizers) seem to have more tacrolimus-related nephrotoxicity, more BK-viremia, and a lower graft survival. At first sight, the expression of CYP3A5 and a low C-0/D ratio seem to be overlapping factors, both pointing towards patients in whom a higher tacrolimus dose is needed to reach the tacrolimus target concentration. However, there are important differences, and these differences may explain why the impact of the C-0/D ratio on long term outcome is stronger than for CYP3A5 genotype status. Patients with a low C-0/D ratio require a high tacrolimus dose and are exposed to high tacrolimus peak concentrations. The higher peak exposure to tacrolimus (and/or its metabolites) may explain the higher incidence of nephrotoxicity, BK-viremia and graft loss. A potential confounder is the concurrent maintenance treatment of corticosteroids, as steroids are sometimes continued in patients at high immunological risk. Steroids induce the metabolism of tacrolimusviapregnane X receptor mediated increased CYP3A4 expression, resulting in lower tacrolimus C-0/D ratio in high risk patients. Also non-adherence may result in lower C-0/D ratio which is also associated with poor outcome. The C-0/D ratio of tacrolimus does seem to identify a group of patients with increased risk of poor outcome after kidney transplantation. Our recommendation is to monitor tacrolimus peak concentrations in these patients, and if these are high then target slightly lower pre-dose concentrations. Another possibility would be to switch to a prolonged release formulation or to dose the drug more frequently, in smaller doses, to avoid high peak concentrations.

Multiple pharmacogenetic studies investigated the effectiveness of methotrexate. However, due to the use of nonvalidated outcomes, lack of validation or conflicting results it remains unclear if genetic markers can help to predict response to MTX treatment. Therefore, a systematic review was performed. PubMed was searched for articles reporting potential pharmacogenetic biomarkers associated (p < 0.05) with MTX efficacy using the validated endpoints DAS(28), EULAR, or ACR response criteria. The PICO method was used for study selection, and PRISMA guidelines to prepare the report. Thirty-five studies met the inclusion criteria, providing 39 potential genetic biomarkers in 19 genes. After Bonferroni correction, six genetic biomarkers were associated with the efficacy of MTX: ATIC rs7563206; SLC19A1 rs1051266; DHFR rs836788; TYMS rs2244500, rs2847153, and rs3786362 in at least one study. Only SLC19A1 rs1051266 was replicated in an independent cohort and promising for predicting methotrexate efficacy.

Pharmacogenomics is a key component of personalized medicine. It promises a safer and more effective drug treatment by individualizing the choice of drug and dose based on an individual’s genetic profile1,2. The majority of commonly prescribed drugs are metabolized by a small set of Cytochrome P450 (CYP) enzymes3. In clinical practice, genetic biomarkers are being used to categorize patients into predefined *-alleles to predict CYP450 enzyme activity and adjust drug dosages accordingly. Yet, this approach has important limitations as it leaves a large part of variability in drug response unexplained4,5. Here, we present a novel approach and introduce a continuous scale (instead of categorical) assignments to predict metabolic enzyme activity. The proposed strategy uses full gene sequencing data, a neural network model and CYP2D6 mediated tamoxifen metabolism from a prospective study of 561 breast cancer patients. The model explains 79% of the interindividual variability in CYP2D6 activity compared to 54% with the conventional approach. It is capable of assigning accurate enzyme activity to alleles containing previously uncharacterized combinations of variants and were replicated in an independent cohort of tamoxifen treated patients, a cohort of Venlafaxine users as well as in vitro functional assays using HEK cells. These results demonstrate the advantage of a continuous scale and a completely phased genotype for prediction of CYP450 enzyme activity and thereby enables more accurate prediction of individual drug response.

Despite overcoming many implementation barriers, pharmacogenomic (PGx) panel-testing is not routine practice in the Netherlands. Therefore, we aim to study pharmacists’ perceived enablers and barriers for PGx panel-testing among pharmacists participating in a PGx implementation study. Here, pharmacists identify primary care patients, initiating one of 39 drugs with a Dutch Pharmacogenetic Working Group (DPWG) recommendation and subsequently utilizing the results of a 12 gene PGx panel test to guide dose and drug selection. Pharmacists were invited for a general survey and a semi-structured interview based on the Tailored Implementation for Chronic Diseases (TICD) framework, aiming to identify implementation enablers and barriers, if they had managed at least two patients with actionable PGx results. In total, 15 semi-structured interviews were performed before saturation point was reached. Of these, five barrier themes emerged: (1) unclear procedures, (2) undetermined reimbursement for PGx test and consult, (3) insufficient evidence of clinical utility for PGx panel-testing, (4) infrastructure inefficiencies, and (5) HCP PGx knowledge and awareness; and two enabler themes: (1) pharmacist perceived role in delivering PGx, and (2) believed clinical utility of PGx. Despite a strong belief in the beneficial effects of PGx, pharmacists’ barriers remain, an these hinder implementation in primary care.

Introduction: HLA variants have been shown to be associated with an increased risk of hypersensitivity reactions to specific drugs. Both the Clinical Pharmacogenetics Implementation Consortium (CPIC) and the Dutch Pharmacogenetics Working Group (DPWG) have issued actionable HLA gene – drug interaction guidelines but diagnostic test criteria remain largely unknown. We present an overview of the diagnostic test criteria of the actionable HLA – drug pairs. Methods: A systematic literature search was conducted in PubMed, Embase, Web of Science and Cochrane Library. Original case-control and cohort studies were selected and sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and number needed to genotype (NNG) were calculated for the actionable HLA-drug pairs. Results: In general, the HLA tests show high specificity and NPV for predicting hypersensitivity reactions. The sensitivity of HLA tests shows a wide range, from 0-33% for HLA-B*1502 testing to predict lamotrigine induced SJS/TEN up to 100% for HLA-B*5701 to predict immunologically confirmed abacavir hypersensitivity syndrome (ABC-HSR). PPV is low for all tests except for HLA-B*5701 and ABC-HSR which is approximately 50%. HLA-B*5701 to predict ABC-HSR shows the lowest NNG followed by HLA-B*5801 for allopurinol induced severe cutaneous adverse drug reactions and HLA-B*1502 for carbamazepine induced SJS/TEN. Discussion: This is the first overview of diagnostic test criteria for actionable HLA-drug pairs. Studies researching HLA genes and hypersensitivity are scarce for some of the HLA-drug pairs and patient numbers in available studies are small. Therefore more research is necessary to calculate the diagnostic criteria more accurately.

Contains fulltext : 229047.pdf (Publisher’s version ) (Open Access) For ~ 80 drugs, widely recognized pharmacogenetics dosing guidelines are available. However, the use of these guidelines in clinical practice remains limited as only a fraction of patients is subjected to pharmacogenetic screening. We investigated the feasibility of repurposing whole exome sequencing (WES) data for a panel of 42 variants in 11 pharmacogenes to provide a pharmacogenomic profile. Existing diagnostic WES-data from child-parent trios totaling 1,583 individuals were used. Results were successfully extracted for 39 variants. No information could be extracted for three variants, located in CYP2C19, UGT1A1, and CYP3A5, and for CYP2D6 copy number. At least one actionable phenotype was present in 86% of the individuals. Haplotype phasing proved relevant for CYP2B6 assignments as 1.5% of the phenotypes were corrected after phasing. In conclusion, repurposing WES-data can yield meaningful pharmacogenetic profiles for 7 of 11 important pharmacogenes, which can be used to guide drug treatment.

Aims Tacrolimus and mycophenolic acid dosing after renal transplantation is individualized through therapeutic drug monitoring (TDM). Home-based dried blood spot (DBS) sampling has the potential to replace conventional TDM sampling at the clinic. A liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay was developed to quantify tacrolimus and mycophenolic acid in DBS and clinically validated for abbreviated area under the concentration-time curve (AUC) monitoring using an innovative volumetric DBS sampling device. Methods Clinical validation was performed by direct comparison of paired DBS and whole blood (WB) (tacrolimus) and plasma (mycophenolic acid) concentrations and AUCs. Agreement was evaluated using Passing-Bablok regression, Bland-Altman analysis and DBS-to-WB predictive performance. TDM dosing recommendations based on both methods were compared to assess clinical impact. Results Paired tacrolimus (n = 200) and mycophenolic acid (n = 192) DBS and WB samples were collected from 65 kidney(-pancreas) transplant recipients. Differences for tacrolimus and mycophenolic acid were within ±20% for 84.5% and 76.6% of concentrations and 90.5% and 90.7% of AUCs, respectively. Tacrolimus and mycophenolic acid dosing recommendation differences occurred on 44.4% and 4.7% of occasions. Tacrolimus DBS dosing recommendations were 0.35 ± 0.14 mg higher than for WB and 8 ± 3% of the initial dose. Mycophenolic acid DBS dosing recommendations were 23.3 ± 31.9 mg lower than for plasma and 2 ± 3.5% of the initial dose. Conclusions Tacrolimus and mycophenolic acid TDM for outpatient renal transplant recipients, based on abbreviated AUC collected with a DBS sampling device, is comparable to conventional TDM based on WB sampling. Patient training and guidance on good blood-spotting practices is essential to ensure method feasibility.

Introduction: Mitomycin C (MMC) is commonly used in patients with colorectal peritoneal metastases (CPM) treated with cytoreductive surgery plus hyperthermic intraperitoneal chemotherapy (CRS + HIPEC). MMC requires metabolic activation prior to exert its cytotoxic effect of which the main activating enzymes are NQO1 and POR. However, not all patients are able to activate MMC for example due to polymorphisms in the genes encoding these enzymes. The aim of this study was to investigate the association of NQO1*2, NQO1*3, and POR*28 with the efficacy of CRS + HIPEC with MMC in patients with CPM.Method: A retrospective follow-up design was used to study genetic association in patients with histologically proven CPM treated with CRS + HIPEC with MMC with respect to peritoneal recurrence rate after 3 months (primary endpoint), after 6 months, disease-free survival and overall survival. Genetic polymorphisms NQO1*2, NQO1*3, and POR*28 were tested for association.Results: A total of 253 patients were included. In NQO1*3 carriers the peritoneal recurrence rate 3 and 6 months after HIPEC was significantly higher than in wild type patients, respectively 30.0% vs 3.8% (p = 0.009) and 40.0% vs 12.1% (p = 0.031). In line with these results, NQO1*3 was associated with a shorter disease-free survival (HR 2.04, 95% CI [1.03-4.03]). There was no significant association with overall survival (HR 1.42, 95% CI [0.66-3.07]).Conclusion: Carriership of the NQO1*3 allele is associated with worse peritoneal recurrence rate and disease-free survival. These results suggest that individualization of patients treated with CRS + HIPEC based upon pharmacogenetics may be beneficial. (C) 2020 Elsevier Ltd, BASO similar to The Association for Cancer Surgery, and the European Society of Surgical Oncology. All rights reserved.

Purpose Tamoxifen has a wide inter-variability. Recently, two SNPs in the 3′-untranslated region (UTR) of the SULT1A1 gene, rs6839 and rs1042157, have been associated with decreased SULT1A1 activity. The aim of this study is to investigate the role of the rs6839 and rs1042157 on tamoxifen metabolism and relapse-free survival (RFS) in women diagnosed with early-breast cancer receiving tamoxifen. Methods Samples from 667 patients collected in the CYPTAM study (NTR1509) were used for genotyping (CYP2D6, SULT1A1 rs6839 and rs1042157) and measurements of tamoxifen and metabolites. Patients were categorized in three groups depending on the decreased SULT1A1 activity due to rs6839 and rs1042157: low activity group (rs6839 (GG) and rs1042157 (TT)); high activity group (rs6839 (AA) and rs1042157 (CC)); and medium activity group (all the other combinations of rs6839 and rs1042157). Associations between SULT1A1 phenotypes and clinical outcome (RFS) were explored. Results In the low SULT1A1 activity group, higher endoxifen and 4-hydroxy-tamoxifen concentrations were found, compared to the medium and high activity group (endoxifen: 31.23 vs. 30.51 vs. 27.00, p value: 0.016; 4-hydroxy-tamoxifen: 5.55 vs. 5.27 vs. 4.94, p value:0.05). In terms of relapse, the low activity group had a borderline better outcome compared to the medium and high SULT1A1 activity group (adjusted Hazard ratio: 0.297; 95% CI 0.088–1.000; p value: 0.05). Conclusion Our results suggested that rs6839 and rs1042157 SNPs have a minor effect on the concentrations and metabolic ratios of tamoxifen and its metabolites, and RFS in women receiving adjuvant tamoxifen. Electronic supplementary material The online version of this article (10.1007/s10549-018-4923-7) contains supplementary material, which is available to authorized users.

Aim: To benchmark knowledge and attitude of pharmacy students toward pharmacogenetics (PGx) and PGx testing and compare the results with practicing colleagues. Methods: All pharmacy students in The Netherlands were invited to participate in a web-based survey consisting of 28 questions. Out of the 824 invited students, 148 individuals (18.0%) completed the questionnaire. All responders believed in the concept of PGx and had high expectations toward PGx. The majority (96.6%) had received some form of education on PGx, but only 12.8% felt adequately informed. Results: When compared with practicing pharmacists, differences were observed in the use of information and feeling qualified to recommend PGx testing. Conclusion: More education on PGx is required in the curriculum to fill the perceived knowledge gap among future pharmacists.

This study aimed to identify single-nucleotide polymorphisms (SNPs) that are associated with outcome to treatment with sunitinib in patients with advanced gastrointestinal stromal tumors (GIST). Forty-nine SNPS involved in the pharmacokinetic and pharmacodynamic pathway of sunitinib were associated with progression-free survival (PFS) and overall survival (OS) in 127 patients with advanced GIST who have been treated with sunitinib. PFS was significantly longer in carriers of the TT genotype in POR rs1056878 (hazards ratio (HR) 4.310, 95% confidence interval (CI): 1.457-12.746, P = 0.008). The presence of the T-allele in SLCO1B3 rs4149117 (HR 2.024, 95% CI: 1.013-4.044, P = 0.046), the CCC-CCC alleles in SLC22A5 haplotype (HR 2.603, 95% CI: 1.2165.573, P = 0.014), and the GC-GC alleles in the IL4 R haplotype (HR 7.131, 95% CI: 1.518-33.496, P = 0.013) were predictive for OS. This shows that polymorphisms in the pharmacokinetic and pharmacodynamic pathways of sunitinib are associated with survival in GIST. This may help to identify patients that benefit more from treatment with sunitinib.

The tyrosine kinase inhibitor sunitinib is used as first-line therapy in patients with metastasized renal cell carcinoma (mRCC), given in fixed-dose regimens despite its high variability in pharmacokinetics (PKs). Interindividual variability of drug exposure may be responsible for differences in response. Therefore, dosing strategies based on pharmacokinetic/pharmacodynamic (PK/PD) models may be useful to optimize treatment. Plasma concentrations of sunitinib, its active metabolite SU12662, and the soluble vascular endothelial growth factor receptors sVEGFR-2 and sVEGFR-3, were measured in 26 patients with mRCC within the EuroTARGET project and 21 patients with metastasized colorectal cancer (mCRC) from the C-II-005 study. Based on these observations, PK/PD models with potential influence of genetic predictors were developed and linked to time-to-event (TTE) models. Baseline sVEGFR-2 levels were associated with clinical outcome in patients with mRCC, whereas active drug PKs seemed to be more predictive in patients with mCRC. The models provide the basis of PK/PD-guided strategies for the individualization of anti-angiogenic therapies.

Imatinib trough levels have been associated with its clinical effects. During chronic use of imatinib, CYP2C8 becomes an important metabolizing enzyme because of cytochrome P450 3A4 (CYP3A4) autoinhibition. Single nucleotide polymorphisms (SNPs) in CYP2C8 may affect imatinib trough levels. This study investigates the effect of common CYP2C8 polymorphisms [*1B (rs7909236), *1C (rs17110453), *3 (rs11572080 and rs10509681), and *4 (rs1058930)] on steady-state trough levels imatinib during chronic imatinib use in 43 patients with chronic myeloid leukemia or gastrointestinal stromal tumors. Standardized imatinib trough levels did not show a significant difference between wild-type and variant groups for any of the tested SNPs, but an association with age was found, with older patients having higher trough levels. This suggests that common CYP2C8 SNPs have no effect on the pharmacokinetics of imatinib.

The identification of biomarkers able to predict clinical benefit from vascular endothelial growth factor receptor (VEGFR) tyrosine kinase inhibitors is urgently needed. Recently, Maitland and colleagues described an association between KDR-rs34231037 and soluble VEGFR2 levels as well as pazopanib pharmacodynamics. We investigated in a well-characterized series of metastatic clear cell renal cell carcinoma patients whether rs34231037 could influence sunitinib response. Clinical data and DNA were available from an international series of 276 patients. KDR-rs34231037 association with sunitinib response, clinical benefit, and progression-free survival was analyzed using logistic and Cox regression analyses. We found that G-allele carriers were over-represented among patients with clinical benefit during sunitinib treatment compared with those refractory to the treatment (odds ratio: 3.78; 95% confidence interval: 1.02-14.06; P=0.047, multivariable analysis). In conclusion, rs34231037 variant carriers seemed to have better sunitinib response than wild-type patients. Moreover, the association with tumor size reduction suggests that this single nucleotide polymorphism might also identify patients with successful tumor downsizing under anti-VEGFR therapy.

Cytochrome P450 2D6 (CYP2D6) is among the most important genes involved in drug metabolism. Specific variants are associated with changes in the enzyme's amount and activity. Multiple technologies exist to determine these variants, like the AmpliChip CYP450 test, Taqman qPCR, or Second‐Generation Sequencing, however, sequence homology between cytochrome P450 genes and pseudogene CYP2D7 impairs reliable CYP2D6 genotyping, and variant phasing cannot accurately be determined using these assays. To circumvent this, we sequenced CYP2D6 using the Pacific Biosciences RSII and obtained high‐quality, full‐length, phased CYP2D6 sequences, enabling accurate variant calling and haplotyping of the entire gene‐locus including exonic, intronic, and upstream and downstream regions. Unphased diplotypes (Roche AmpliChip CYP450 test) were confirmed for 24 of the 25 samples, including gene duplications. Cases with gene deletions required additional specific assays to resolve. In total, 61 unique variants were detected, including variants that had not previously been associated with specific haplotypes. To further aid genomic analysis using standard reference sequences, we have established an LOVD‐powered CYP2D6 gene‐variant database, and added all reference haplotypes and data reported here. We conclude that our CYP2D6 genotyping approach produces reliable CYP2D6 diplotypes and reveals information about additional variants, including phasing and copy‐number variation.

Translating CYP2D6 genotype to metabolizer phenotype is not standardized across clinical laboratories offering pharmacogenetic (PGx) testing and PGx clinical practice guidelines, such as the Clinical Pharmacogenetics Implementation Consortium (CPIC) and the Dutch Pharmacogenetics Working Group (DPWG). The genotype to phenotype translation discordance between laboratories and guidelines can cause discordant cytochrome P450 2D6 (CYP2D6) phenotype assignments and, thus lead to inconsistent therapeutic recommendations and confusion among patients and clinicians. A modified-Delphi method was used to obtain consensus for a uniform system for translating CYP2D6 genotype to phenotype among a panel of international CYP2D6 experts. Experts with diverse involvement in CYP2D6 interpretation (clinicians, researchers, genetic testing laboratorians, and PGx implementers; n = 37) participated in conference calls and surveys. After completion of 7 surveys, a consensus (> 70%) was reached with 82% of the CYP2D6 experts agreeing to the final CYP2D6 genotype to phenotype translation method. Broad adoption of the proposed CYP2D6 genotype to phenotype translation method by guideline developers, such as CPIC and DPWG, and clinical laboratories as well as researchers will result in more consistent interpretation of CYP2D6 genotype.

Clinical pharmacology & therapeutics : CPT 106(2), 313-316 (2019). doi:10.1002/cpt.1471 special issue: "Pharmacogenetics Pharmacogenomics", Published by Wiley-Blackwell, Hoboken, NJ

Background Pharmacogenetics (PGx) is currently implemented in hospitals to optimize therapy with high-risk drugs. However, many drugs with dosing recommendations from the Dutch Pharmacogenetics Working Group and the Clinical Pharmacogenetics Implementation Consortium are used in primary care. Actionable phenotypes for the genes covered in these guidelines are common with estimates ranging from 85 to 95% of the population carrying at least one actionable phenotype. The goal of this study was to estimate the clinical impact of implementation of an upfront panel-based pharmacogenetic screening for eight genes related to drugs used in primary care for 2016. Methods For this study, dispensing data concerning first prescription for the period January 1–December 31, 2016, were combined with frequency data obtained in the “Implementation of Pharmacogenetics into Primary Care Project” (IP3) study to estimate the occurrence of actionable gene-drug pairs in daily practice in community pharmacies. Results In 23.6% of all new prescriptions of 45 drugs (n = 856,002 new prescriptions/year), an actionable gene-drug interaction (GDI) was present according to the guidelines of the Dutch Pharmacogenetics Working Group. More importantly, these GDIs would result in a dose adjustment or switch to another drug in 5.4% of all new prescriptions. Conclusions Consequently, with an anticipated near future where healthcare professionals will be regularly confronted with PGx test results, adjusting pharmacotherapy based on this information will become a routine task in healthcare. Electronic supplementary material The online version of this article (10.1186/s12916-019-1342-5) contains supplementary material, which is available to authorized users.

PURPOSE Tamoxifen is widely prescribed as adjuvant therapy in patients with early-stage breast cancer. It has been postulated that concentrations of endoxifen, the active metabolite of tamoxifen, are a better predictor of tamoxifen efficacy than CYP2D6 genotypes. Although in a retrospective study, an endoxifen threshold of 5.9 ng/mL for efficacy was described, confirmation based on prospective studies is lacking. The objective of the prospective CYPTAM (The Netherlands National Trial Register: NTR1509) study was to associate endoxifen concentrations and CYP2D6 genotypes with clinical outcome in patients with early-stage breast cancer receiving tamoxifen. PATIENTS AND METHODS From February 2008 to December 2010, patients with breast cancer treated with adjuvant tamoxifen were included. Patients could be enrolled up to a maximum of 12 months after tamoxifen initiation. Blood samples were retrieved for CYP2D6 genotyping and endoxifen measurements by Amplichip (Roche Diagnostics, Indianapolis, IN) and high-performance liquid chromatography–tandem mass spectrometry, respectively. Endoxifen concentrations were analyzed as a continuous variable, classifying patients into quartiles and using an endoxifen threshold of 5.9 ng/mL. Endoxifen concentrations and CYP2D6 genotypes were associated with relapse-free survival (censored at the time of tamoxifen discontinuation; RFSt) by Cox regression analysis. RESULTS A total of 667 pre- and postmenopausal patients were enrolled and had received tamoxifen for a median time of 0.37 years (range, 0.23 to 0.6 years) before study entry. No association was found between endoxifen concentrations and RFSt (adjusted hazard ratio, 0.991; 95% CI, 0.946 to 1.038; P = .691). Also, neither categorizing endoxifen concentrations into quartiles nor using 5.9 ng/mL as threshold altered these results. In addition, no association was found between CYP2D6 genotype and RFSt (adjusted hazard ratio, 0.929; 95% CI, 0.525 to 1.642; P = .799). CONCLUSION This prospective clinical study shows no association between endoxifen concentrations or CYP2D6 genotypes and clinical outcome in patients with early-stage breast cancer receiving adjuvant tamoxifen.

Background: Fluoropyrimidine therapy including capecitabine or 5-fluorouracil can result in severe treatment-related toxicity in up to 30% of patients. Toxicity is often related to reduced activity of dihydropyrimidine dehydrogenase, the main metabolic fluoropyrimidine enzyme, primarily caused by genetic DPYD polymorphisms. In a large prospective study, it was concluded that upfront DPYD-guided dose individualisation is able to improve safety of fluoropyrimidine-based therapy. In our current analysis, we evaluated whether this strategy is cost saving.Methods: A cost-minimisation analysis from a health-care payer perspective was performed as part of the prospective clinical trial (NCT02324452) in which patients prior to start of fluoropyrimidine-based therapy were screened for the DPYD variants DPYD*2A, c.2846A>T, c.1679T>G and c.1236G>A and received an initial dose reduction of 25% (c.2846A>T, c.1236G>A) or 50% (DPYD*2A, c.1679T>G). Data on treatment, toxicity, hospitalisation and other toxicity-related interventions were collected. The model compared prospective screening for these DPYD variants with no DPYD screening. One-way and probabilistic sensitivity analyses were also performed.Results: Expected total costs of the screening strategy were (sic)2599 per patient compared with (sic)2650 for non-screening, resulting in a net cost saving of (sic)51 per patient. Results of the probabilistic sensitivity and one-way sensitivity analysis demonstrated that the screening strategy was very likely to be cost saving or worst case cost-neutral.Conclusions: Upfront DPYD-guided dose individualisation, improving patient safety, is cost saving or cost-neutral but is not expected to yield additional costs. These results endorse implementing DPYD screening before start of fluoropyrimidine treatment as standard of care. (C) 2018 Elsevier Ltd. All rights reserved.

Personalized medicine strives to optimize drug treatment for the individual patient by taking into account both genetic and non-genetic factors for drug response. Inflammation is one of the non-genetic factors that has been shown to greatly affect the metabolism of drugs—primarily through inhibition of cytochrome P450 (CYP450) drug-metabolizing enzymes—and hence contribute to the mismatch between the genotype predicted drug response and the actual phenotype, a phenomenon called phenoconversion. This review focuses on inflammation-induced drug metabolism alterations. In particular, we discuss the evidence assembled through human in-vitro models on the effect of inflammatory mediators on clinically relevant CYP450 isoform levels and their metabolizing capacity. We also present an overview of the current understanding of the mechanistic pathways via which inflammation in hepatocytes may modulate hepatic functions that are critical for drug metabolism. Furthermore, since large inter-individual variability in response to inflammation is observed in human in-vitro models and clinical studies, we evaluate the potential role of pharmacogenetic variability in the inflammatory signaling cascade and how this can modulate the outcome of inflammation on drug metabolism and response.

Contains fulltext : 229533.pdf (Publisher’s version ) (Open Access) One application of personalized medicine is the tailoring of medication to the individual, so that the medication will have the highest chance of success. In order to individualize medication, one must have a complete inventory of all current pharmaceutical compounds (a detailed formulary) combined with pharmacogenetic datasets, the genetic makeup of the patient, their (medical) family history and other health-related data. For healthcare professionals to make the best use of this information, it must be visualized in a way that makes the most medically relevant data accessible for their decision-making. Similarly, to enable bioinformatics analysis of these data, it must be prepared and provided through an interface for controlled computational analysis. Due to the high degree of personal information gathered for such initiatives, privacy-sensitive implementation choices and ethical standards are paramount. The Personal Genetic Locker project provides an approach to enable the use of personal genomic data in primary care. In this paper, we provide a description of the Personal Genetic Locker project and show its utility through a use case based on open standards, which is illustrated by the 4MedBox system.

Tacrolimus-modified release formulations allow for once-daily dosing, and adherence is better compared to the twice-daily immediate release formulation. When patients are switched from one formulation to another, variable changes in drug concentrations are observed. Current data suggest that the changes in drug exposure are larger in patients who express the CYP3A5 enzyme (CYP3A5 *1/*3 or *1/*1) compared to nonexpressers (CYP3A5*3/*3). Possibly, these differences are due to the fact that in the upper region of the small intestine CYP3A activity is higher, and that this expression of CYP3A decreases towards the more distal parts of the gut. Modified release formulations may therefore be subject to a less presystemic metabolism. However, the full implications of pharmacogenetic variants affecting the expression and function of drug transporters in the gut wall and of enzymes involved in phase I and phase II metabolism on the different formulations are incompletely understood, and additional studies are required. Conclusions: In all patients in whom the formulation of tacrolimus is changed, drug levels need to be checked to avoid clinically relevant under- or overexposure. In patients with the CYP3A5 expresser genotype, this recommendation is even more important, as changes in drug exposure can be expected.

Background Fluoropyrimidine treatment can result in severe toxicity in up to 30% of patients and is often the result of reduced activity of the key metabolic enzyme dihydropyrimidine dehydrogenase (DPD), mostly caused by genetic variants in the gene encoding DPD (DPYD). We assessed the effect of prospective screening for the four most relevant DPYD variants (DPYD*2A [rs3918290, c.1905+1G>A, IVS14+1G>A], c.2846A>T [rs67376798, D949V], c.1679T>G [rs55886062, DPYD*13, I560S], and c.1236G>A [rs56038477, E412E, in haplotype B3]) on patient safety and subsequent DPYD genotype-guided dose individualisation in daily clinical care. Methods In this prospective, multicentre, safety analysis in 17 hospitals in the Netherlands, the study population consisted of adult patients (>= 18 years) with cancer who were intended to start on a fluoropyrimidine-based anticancer therapy (capecitabine or fluorouracil as single agent or in combination with other chemotherapeutic agents or radiotherapy). Patients with all tumour types for which fluoropyrimidine-based therapy was considered in their best interest were eligible. We did prospective genotyping for DPYD*2A, c.2846A>T, c.1679T>G, and c.1236G>A. Heterozygous DPYD variant allele carriers received an initial dose reduction of 25% (c.2846A>T and c.1236G>A) or 50% (DPYD*2A and c.1679T>G), and DPYD wild-type patients were treated according to the current standard of care. The primary endpoint of the study was the frequency of severe (National Cancer Institute Common Terminology Criteria for Adverse Events version 4.03 grade >= 3) overall fluoropyrimidine-related toxicity across the entire treatment duration. We compared toxicity incidence between DPYD variant allele carriers and DPYD wild-type patients on an intention-to-treat basis, and relative risks (RRs) for severe toxicity were compared between the current study and a historical cohort of DPYD variant allele carriers treated with full dose fluoropyrimidine-based therapy (derived from a previously published meta-analysis). This trial is registered with ClinicalTrials.gov, number NCT02324452, and is complete. Findings Between April 30, 2015, and Dec 21, 2017, we enrolled 1181 patients. 78 patients were considered non-evaluable, because they were retrospectively identified as not meeting inclusion criteria, did not start fluoropyrimidine-based treatment, or were homozygous or compound heterozygous DPYD variant allele carriers. Of 1103 evaluable patients, 85 (8%) were heterozygous DPYD variant allele carriers, and 1018 (92%) were DPYD wild-type patients. Overall, fluoropyrimidine-related severe toxicity was higher in DPYD variant carriers (33 [39%] of 85 patients) than in wild-type patients (231 [23%] of 1018 patients; p=0.0013). The RR for severe fluoropyrimidine-related toxicity was 1.31 (95% CI 0.63-2.73) for genotype-guided dosing compared with 2.87 (2.14-3.86) in the historical cohort for DPYD*2A carriers, no toxicity compared with 4.30 (2.10-8.80) in c.1679T>G carriers, 2.00 (1.19-3.34) compared with 3.11 (2.25-4.28) for c.2846A>T carriers, and 1.69 (1.18-2.42) compared with 1.72 (1.22-2.42) for c.1236G>A carriers. Interpretation Prospective DPYD genotyping was feasible in routine clinical practice, and DPYD genotype-based dose reductions improved patient safety of fluoropyrimidine treatment. For DPYD*2A and c.1679T>G carriers, a 50% initial dose reduction was adequate. For c.1236G>A and c.2846A>T carriers, a larger dose reduction of 50% (instead of 25%) requires investigation. Since fluoropyrimidines are among the most commonly used anticancer agents, these findings suggest that implementation of DPYD genotype-guided individualised dosing should be a new standard of care. Copyright (C) 2018 Elsevier Ltd. All rights reserved.

DPYD genotyping prior to fluoropyrimidine treatment is increasingly implemented in clinical care. Without phasing information (i.e., allelic location of variants), current genotype-based dosing guidelines cannot be applied to patients carrying multiple DPYD variants. The primary aim of this study is to examine diagnostic and therapeutic strategies for fluoropyrimidine treatment of patients carrying multiple DPYD variants. A case series of patients carrying multiple DPYD variants is presented. Different genotyping techniques were used to determine phasing information. Phenotyping was performed by dihydropyrimidine dehydrogenase (DPD) enzyme activity measurements. Publicly available databases were queried to explore the frequency and phasing of variants of patients carrying multiple DPYD variants. Four out of seven patients carrying multiple DPYD variants received a full dose of fluoropyrimidines and experienced severe toxicity. Phasing information could be retrieved for four patients. In three patients, variants were located on two different alleles, i.e., in trans. Recommended dose reductions based on the phased genotype differed from the phenotype-derived dose reductions in three out of four cases. Data from publicly available databases show that the frequency of patients carrying multiple DPYD variants is low (&lt, 0.2%), but higher than the frequency of the commonly tested DPYD*13 variant (0.1%). Patients carrying multiple DPYD variants are at high risk of developing severe toxicity. Additional analyses are required to determine the correct dose of fluoropyrimidine treatment. In patients carrying multiple DPYD variants, we recommend that a DPD phenotyping assay be carried out to determine a safe starting dose.

Clinical pharmacogenomics (PGx) has the potential to make pharmacotherapy safer and more effective by utilizing genetic patient data for drug dosing and selection. However, widespread adoption of PGx depends on its successful integration into routine clinical care through clinical decision support tools, which is often hampered by insufficient or fragmented infrastructures. This paper describes the setup and implementation of a unique multimodal, multilingual clinical decision support intervention consisting of digital, paper-, and mobile-based tools that are deployed across implementation sites in seven European countries participating in the Ubiquitous PGx (U-PGx) project.

Aim: A third of rheumatoid arthritis patients discontinue methotrexate treatment due to inefficacy or toxic side effects. Recently, an association between SLC04A1 rs2236553, SLC22A2 rs624249 and rs316019, and SLC28A2 rs10519020 and rs1060896 with the efficacy and toxicity of methotrexate was reported. This study aims to replicate these findings in an independent cohort (n = 324). Methods: Regression analyses tested the associations between genotype and methotrexate response or toxicity. Results: In the discovery study, there was a significant association between toxicity and rs624249, and rs1060896. These associations were not replicated in the independent cohort. Neither study observed an association between methotrexate efficacy and SLC04A1, SLC22A2 or SLC28A2 variants. Conclusion: Current evidence does not support associations between variants in SLC04A1, SLC22A2 and SLC28A2 with methotrexate efficacy or toxicity.

Purpose: The survival of patients with clear cell metastatic renal cell carcinoma (cc-mRCC) has improved substantially since the introduction of tyrosine kinase inhibitors (TKI). With the fact that TKIs interact with immune responses, we investigated whether polymorphisms of genes involved in immune checkpoints are related to the clinical outcome of cc-mRCC patients treated with sunitinib as first TKI. Experimental Design: Twenty-seven single-nucleotide polymorphisms (SNP) in CD274 (PD-L1), PDCD1 (PD-1), and CTLA-4 were tested for a possible association with progression-free survival (PFS) and overall survival (OS) in a discovery cohort of 550 sunitinib-treated cc-mRCC patients. SNPs with a significant association (P < 0.05) were tested in an independent validation cohort of 138 sunitinib-treated cc-mRCC patients. Finally, data of the discovery and validation cohort were pooled for meta-analysis. Results: CTLA-4 rs231775 and CD274 rs7866740 showed significant associations with OS in the discovery cohort after correction for age, gender, and Heng prognostic risk group [HR, 0.84; 95% confidence interval (CI), 0.72–0.98; P = 0.028, and HR, 0.73; 95% CI, 0.54–0.99; P = 0.047, respectively]. In the validation cohort, the associations of both SNPs with OS did not meet the significance threshold of P < 0.05. After meta-analysis, CTLA-4 rs231775 showed a significant association with OS (HR, 0.83; 95% CI, 0.72–0.95; P = 0.008). Patients with the GG genotype had longer OS (35.1 months) compared with patients with an AG (30.3 months) or AA genotype (24.3 months). No significant associations with PFS were found. Conclusions: The G-allele of rs231775 in the CTLA-4 gene is associated with an improved OS in sunitinib-treated cc-mRCC patients and could potentially be used as a prognostic biomarker. Clin Cancer Res; 24(10); 2350–6. ©2018 AACR.

Currently, germline pharmacogenomics (PGx) is successfully implemented within certain specialties in clinical care. With the integration of PGx in pharmacotherapy multiple stakeholders are involved, which are identified in this chapter. Clinically relevant pharmacogenes with their related PGx test are discussed, along with diagnostic test criteria to guide clinicians and policy makers in PGx test selection. The chapter further reviews the similarities and the differences between the guidelines of the Dutch Pharmacogenetics Working Group and the Clinical Pharmacogenetics Implementation Consortium which both support healthcare professionals in understanding PGx test results and help guiding pharmacotherapy by providing evidence-based dosing recommendations. Finally, clinical studies which provide scientific evidence and information on cost-effectiveness supporting clinical implementation of PGx in clinical care are discussed along with the remaining barriers for adoption of PGx testing by healthcare professionals.

An increasing number of studies have reported ethnic differences in sunitinib outcome in metastatic renal cell carcinoma (mRCC) patients. However, a comprehensive analysis is still lacking. Therefore, we systematically collected available published data and performed a meta-analysis to compare sunitinib efficacy and toxicity in Asian and Caucasian mRCC patients.Data were extracted from published results from clinical trials, expanded access program and real-world clinical practice. Progression-free survival (or time to tumor progression), overall survival, objective response rate and adverse events were used as endpoints to evaluate the differences of sunitinib outcome between the two ethnicities. For adverse events, we focused the following clinically relevant side effects: diarrhea, fatigue, mucositis/stomatitis, hand-foot syndrome, hypertension, leukopenia, neutropenia and thrombocytopenia.A total of 33 publications including 9977 patients were available for meta-analysis. The efficacy of sunitinib in Asian patients was similar to that in Caucasian patients. However, Asian patients showed a higher incidence of all grades toxicity of hand-foot syndrome, grade 2 fatigue, grade 2 hand-foot syndrome and grade 2 thrombocytopenia.Ethnic differences in adverse events of sunitinib in mRCC patients existed and dose adjustment in Asian patients may be considered.

Background Tamoxifen is one of the cornerstones of endocrine therapy for breast cancer. Recently, the decreased activity CYP3A4*22 allele and the loss of function CYP3A5*3 allele have been described as potential factors that could help to explain the inter-patient variability in tamoxifen metabolism. The aim of this study is to investigate the effect of CYP3A4*22, CYP3A5*3, and CYP3A combined genotypes on tamoxifen metabolism. Methods DNA from 667 women enrolled in the CYPTAM study (NTR1509) was genotyped (CYP2D6, CYP3A4*22, and CYP3A5*3). Tamoxifen and metabolite concentrations were measured in serum, and metabolic ratios were calculated. The effect of the CYP3A4*22, CYP3A5*3, and CYP3A combined genotypes in addition to the CYP2D6 genotypes was examined by multiple linear regression analysis. Results CYP3A4*22 carriers reached significant higher concentrations of tamoxifen, N-desmethyl-tamoxifen, and 4-hydroxy-tamoxifen compared to non-carriers, whereas a tendency toward increased endoxifen levels was observed (p = 0.088). The metabolic ratio tamoxifen/N-desmethyl-tamoxifen was significantly higher in CYP3A4*22 individuals (0.59 vs. 0.52, p

Purpose The once daily formulation of tacrolimus is an important immunosuppressive drug. Interpatient variability in metabolism has been related to genetic variation in CYP3A4 and CYP3A5. However, in liver transplantation, both donor and recipient genotypes may affect pharmacokinetics. The primary objective of this study was to investigate the effect of CYP3A4*22 and CYP3A5*3 of both donor and recipient on once daily tacrolimus pharmacokinetics. The secondary objective was to develop a limited sampling model able to accurately predict exposure. Methods Stable liver transplant patients receiving once daily tacrolimus (N = 66) were included. Population pharmacokinetic analysis was performed with patients of whom DNA was available (N = 49), and demographic factors, CYP3A4*22 and CYP3A5*3, were tested as covariates. Moreover, a limited sampling model was developed using data of 66 patients. Results Pharmacokinetics was best described by a two-compartment model with delayed absorption. CYP3A5*1 carrying recipients engrafted with a CYP3A5*1 carrying liver had an average 1.7-fold higher clearance compared to non-carriers. CYP3A5*1 carrying recipients engrafted with a CYP3A5*1 non-carrying liver or vice versa showed an average 1.3-fold higher clearance compared with non-carriers. CYP3A4*22 was not significantly associated with once daily tacrolimus pharmacokinetics. Using 0, 2, and 3 h postdose as limited sampling model resulted in significantly improved prediction of tacrolimus exposure compared with trough concentration. Conclusions Both donor and recipient CYP3A5 genotype significantly influences tacrolimus once daily pharmacokinetics. In contrast, CYP3A4*22 appears not suitable as biomarker. The developed limited sampling model can be used to accurately estimate tacrolimus once daily exposure. Electronic supplementary material The online version of this article (doi:10.1007/s00228-015-1963-3) contains supplementary material, which is available to authorized users.

Background: Imatinib 400 mg per day is first-line therapy for patients with gastrointestinal stromal tumours (GISTs). Although clinical benefit is high, progression-free survival (PFS) is variable. This study explores the relationship of single nucleotide polymorphisms (SNPs) in genes related to imatinib pharmacokinetics and pharmacodynamics and PFS in imatinib-treated patients with advanced GIST.Methods: In 227 patients a pharmacogenetic pathway analysis was performed. Genotype data from 36 SNPs in 18 genes were tested in univariate analyses to investigate their relationship with PFS. Genetic variables which showed a trend (p Results: In univariate analyses, PFS was associated with synchronous metastases (p=0.0008) and the mutational status (p = 0.004). Associations with rs1870377 in KDR (additive model, p = 0.0009), rs1570360 in VEGFA (additive model, p = 0.053) and rs4149117 in SLCO1B3 mutant dominant model, 0.027) were also found. In the multivariate model, significant associations and trends with shorter PFS were found for synchronous metastases (HR 1.94, p = 0.002), KIT exon 9 mutation (HR 2.45, p = 0.002) and the SNPs rs1870377 (AA genotype, HR 2.61, p = 0.015), rs1570360 (AA genotype, HR 2.02, p = 0.037) and rs4149117 (T allele, HR 0.62, p = 0.083).Conclusion: In addition to KIT exon 9 mutation and synchronous metastases, SNPs in KDR, VEGFA and SLCO1B3 appear to be associated with PFS in patients with advanced GIST receiving 400-mg imatinib. If validated, specific SNPs may serve as predictive biomarkers to identify patients with an increased risk for progressive disease during imatinib therapy.

Administration of azole antifungals to tacrolimus-treated solid organ recipients results in a major drug-drug interaction characterized by increased exposure to tacrolimus. The magnitude of this interaction is highly variable but cannot currently be predicted. We performed a retrospective analysis of 126 solid organ recipients (95 lung, 31 kidney) co-treated with tacrolimus and voriconazole (n=100) or posaconazole (n=26). Predictors of the change in tacrolimus dose-corrected trough concentrations (C/D) between baseline and tacrolimus - azole co-therapy were assessed using linear mixed modeling. Patients were genotyped for relevant polymorphisms in CYP3A4, CYP3A5, MDR1, CYP2C19, POR and UGT1A4. Tacrolimus C/D increased by a factor 5.0 ± 2.7 (range 1.0-20.2) for voriconazole and 4.4 ± 2.6 (range 0.9-18.0) for posaconazole, suggesting that a 66% dose reduction is insufficient for the majority of patients. Change in C/D was blunted in CYP3A5 expressors (estimated effect: -43%, P=0.017) and affected by hematocrit (+8% per %, P=0.004), baseline C/D (-14% per 100% increase, P

Aim: CYP2D6*2 is considered fully active, but it has been suggested that it only happens in the presence of rs5758550. This study aims to elucidate the impact of this enhancer. Materials & methods: DNA and blood samples from women enrolled in the CYPTAM study (NTR1509) were analyzed. Fourteen CYP2D6*2 carriers without the enhancer were reclassified. The relationship of CYP2D6 phenotypes and drug levels was studied. Results: After correction for the absence of the enhancer, the correlation between CYP2D6 phenotypes and endoxifen did not improve (R2: 0.290 vs 0.279). No difference was observed in mean concentrations between CYP2D6*2 individuals with and without the enhancer. Conclusion: The rs5758550 enhancer does not lead to improved prediction of endoxifen levels in breast cancer patients.

Aim: About 30% of rheumatoid arthritis patients have no clinical benefit from TNF inhibitors. Genome-wide association (GWA) and candidate gene studies tested several putative genetic variants for TNF inhibitor efficacy with inconclusive results. Therefore, this study applied a systematic pathway analysis. Patients & methods: A total of 325 rheumatoid arthritis patients treated with adalimumab were genotyped for 223 SNPs. We tested the association between SNPs and European League Against Rheumatism response and remission at 14 weeks under the additive genetic model using logistic regression. Results: A total of 3 SNPs located in CD40LG (rs1126535), TANK (rs1267067) and VEGFA (rs25648) showed association with both end points. TNFAIP3 (rs2230926) had the strongest effect related to European League Against Rheumatism response. Conclusion: This exploratory study suggests that TNFAIP3, CD40LG, TANK and VEGFA play a role in the response to adalimumab treatment.

CYP2D6 and CYP2C19 polymorphisms affect the exposure, efficacy and safety of tricyclic antidepressants (TCAs), with some drugs being affected by CYP2D6 only (e.g., nortriptyline and desipramine) and others by both polymorphic enzymes (e.g., amitriptyline, clomipramine, doxepin, imipramine, and trimipramine). Evidence is presented for CYP2D6 and CYP2C19 genotype-directed dosing of TCAs. This document is an update to the 2012 Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline for CYP2D6 and CYP2C19 Genotypes and Dosing of Tricyclic Antidepressants.