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On 8–9 November 2022, the European Society of Pharmacogenomics and Personalised Therapy organized its sixth biennial congress, in Belgrade, Serbia (congress website: www.sspt.rs ). The congress aimed to address the current status and future perspectives of pharmacogenomics, share latest knowledge in the field of precision medicine and showcase the implementation of clinical applications in pharmacogenomics/pharmacogenetics. The 2 day congress consisted of 17 lectures given by key-opinion leaders and included a poster session plus discussions. The meeting was a great success by generating an informal environment and enabling the exchange of information between 162 participants from 16 different countries.

Pharmacogenomics (PGx) utilizes an individual’s germline genetic profile to identify those who are at higher risk for ADRs or lack of efficacy. This information can be used by healthcare professionals (HCPs) to guide dose and drug selection before drug initiation in an effort to optimize drug therapy through precision medicine. Despite both the promise of and the progress in the field of PGx to achieve precision medicine, it is still not routinely applied in patient care. As such, a number of barriers preventing implementation have been identified. These include the undetermined model for delivering PGx, the lack of evidence supporting a PGx panel approach and the lack of tools supporting implementation. Therefore, the work of this thesis aims to support the implementation of precision medicine using PGx panel testing. It reports on generating evidence for PGx panel testing (Part I) and the development of tools facilitating implementation (Part II), evaluates the implementation process utilizing these tools (Part III) and quantifies the impact of PGx implementation on patient outcomes and cost-effectiveness (Part IV).

This pilot study is aimed at implementing an approach for comprehensive clinical pharmacogenomics (PGx) profiling. Fifty patients with cardiovascular diseases and 50 healthy individuals underwent whole-exome sequencing. Data on 1800 PGx genes were extracted and analyzed through deep filtration separately. Theoretical drug induced phenoconversion was assessed for the patients, using sequence2script. In total, 4539 rare variants (including 115 damaging non-synonymous) were identified. Four publicly available PGx bioinformatics algorithms to assign PGx haplotypes were applied to nine selected very important pharmacogenes (VIP) and revealed a 45–70% concordance rate. To ensure availability of the results at point-of-care, actionable variants were stored in a web-hosted database and PGx-cards were developed for quick access and handed to the study subjects. While a comprehensive clinical PGx profile could be successfully extracted from WES data, available tools to interpret these data demonstrated inconsistencies that complicate clinical application.

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.

Supplementary Table S1 Selected tagging SNPs Supplementary Figure S1 Kaplan-Meier plot for overall survival by genotype of CTLA-4 rs231775 in discovery cohort (A), validation cohort (B) and combined cohort (C). Supplementary Figure S2 The association of CTLA-4 rs231775 with CTLA-4 gene expression in multiple tissues (A) and in testis tissue (B, p=1.0Ã-10-7) using data from the Genotype-Tissue Expression (GTEx) dataset. Supplementary Figure S3 The survival curve shows the association of CTLA-4 gene expression with overall survival in patients with clear cell renal cell carcinoma (p=0.00255) through OncoLnc, which links The Cancer Genome Atlas (TCGA) survival data to mRNA expression levels (23). (low: lower 50 percentile, high: upper 50 percentile).

Personalized medicine is currently hampered by the lack of flexible drug formulations. Especially for pediatric patients, manual compounding of personalized drug formulations by pharmacists is required. Three-Dimensional (3D) printing of medicines, which enables small-scale manufacturing at the point-of-care, can fulfill this unmet clinical need. This study investigates the feasibility of developing a 3D-printed tablet formulation at the point-of-care which complies to quality requirements for clinical practice, including bioequivalence. Development, manufacturing, and quality control of the 3D-printed tablets was performed at the manufacturing facility and laboratory of the department of Clinical Pharmacy and Toxicology at Leiden University Medical Center. Sildenafil was used as a model drug for the tablet formulation. Along with the 3D-printed tablets a randomized, an open-label, 2-period, crossover, single-dose clinical trial to assess bioequivalence was performed in healthy adults. Bioequivalence was established if areas under the plasma concentration curve from administration to the time of the last quantifiable concentration (AUC0-t) and maximum plasma concentration (Cmax) ratios were within the limits of 80.00–125.00%. The manufacturing process provided reproducible 3D-printed tablets that adhered to quality control requirements and were consequently used in the clinical trial. The clinical trial was conducted in 12 healthy volunteers. The 90% confidence intervals (CIs) of both AUC0-t and Cmax ratios were within bioequivalence limits (AUC0-t 90% CI: 87.28–104.14; Cmax 90% CI: 80.23–109.58). For the first time, we demonstrate the development of a 3D-printed tablet formulation at the point-of-care that is bioequivalent to its marketed originator. The 3D printing of personalized formulations is a disruptive technology for compounding, bridging the gap toward personalized medicine.

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.

Tailoring antiplatelet therapy based on CYP2C19 pharmacogenetic (PGx) testing can improve cardiovascular outcomes and potentially reduce healthcare costs in patients on a P2Y12-inhibitor regime with prasugrel or ticagrelor. However, ubiquitous adoption—particularly in an outpatient setting—remains limited. We conducted a proof-of-concept study to evaluate the feasibility of CYP2C19-guided de-escalation of prasugrel/ticagrelor to clopidogrel through point-of-care (POC) PGx testing in the community pharmacy. Multiple feasibility outcomes were assessed. Overall, 144 patients underwent CYP2C19 PGx testing in 27 community pharmacies. Successful test results were obtained in 142 patients (98.6%). De-escalation to clopidogrel occurred in 19 patients (20%) out of 95 (67%) eligible for therapy de-escalation, which was mainly due to PGx testing not being included in cardiology guidelines. Out of the 119 patients (84%) and 14 pharmacists (100%) surveyed, 109 patients (92%) found the community pharmacy a suitable location for PGx testing, and the majority of pharmacists (86%) thought it has added value. Net costs due to PGx testing were estimated at €43 per patient, which could be reduced by earlier testing and could turn into savings if de-escalation would double to 40%. Although the observed de-escalation rate was low, POC CYP2C19-guided de-escalation to clopidogrel appears feasible in a community pharmacy setting.

Aim: To determine the safety, feasibility, pharmacokinetics, and cost of UGT1A1 genotype-guided dosing of irinotecan.Patients and methods: In this prospective, multicentre, non-randomised study, patients intended for treatment with irinotecan were pre-therapeutically genotyped for UGT1A1*28 and UGT1A1)93. Homozygous variant carriers (UGT1A1 poor metabolisers; PMs) received an initial 30% dose reduction. The primary endpoint was incidence of febrile neutropenia in the first two cycles of treatment. Toxicity in UGT1A1 PMs was compared to a historical cohort of UGT1A1 PMs treated with full dose therapy, and to UGT1A1 non-PMs treated with full dose therapy in the current study. Secondary endpoints were pharmacokinetics, feasi- bility, and costs.Results: Of the 350 evaluable patients, 31 (8.9%) patients were UGT1A1 PM and received a median 30% dose reduction. The incidence of febrile neutropenia in this group was 6.5% compared to 24% in historical UGT1A1 PMs (P = 0.04) and was comparable to the incidence in UGT1A1 non-PMs treated with full dose therapy. Systemic exposure of SN-38 of reduced dosing in UGT1A1 PMs was still slightly higher compared to a standard-dosed irinotecan patient cohort (difference: thorn 32%). Cost analysis showed that genotype-guided dosing was cost-saving with a cost reduction of V183 per patient.Conclusion: UGT1A1 genotype-guided dosing significantly reduces the incidence of febrile neutropenia in UGT1A1 PM patients treated with irinotecan, results in a therapeutically effec- tive systemic drug exposure, and is cost-saving. Therefore, UGT1A1 genotype-guided dosing of irinotecan should be considered standard of care in order to improve individual patient safety. (C) 2022 The Authors. Published by Elsevier Ltd.

Pharmacogenomic testing is a method to prevent adverse drug reactions. Pharmacogenomics could be relevant to optimize statin treatment, by identifying patients at high risk for adverse drug reactions. We aim to investigate the clinical validity and utility of pre-emptive pharmacogenomics screening in primary care, with SLCO1B1 c.521T>C as a risk factor for statin-induced adverse drug reactions. The focus was on changes in therapy as a proxy for adverse drug reactions observed in statin-users in a population-based Dutch cohort. In total, 1136 statin users were retrospectively genotyped for the SLCO1B1 c.521T>C polymorphism (rs4149056) and information on their statin dispensing was evaluated as cross-sectional research. Approximately half of the included participants discontinued or switched their statin treatment within three years. In our analyses, we could not confirm an association between the SLCO1B1 c.521T>C genotype and any change in statin therapy or arriving at a stable dose sooner in primary care. To be able to evaluate the predictive values of SLCO1B1 c.521T>C genotype on adverse drug reactions from statins, prospective data collection of actual adverse drug reactions and reasons to change statin treatment should be facilitated.

Contains fulltext : 290958.pdf (Publisher’s version ) (Open Access) Hepatotoxicity is a serious adverse drug reaction related to methotrexate (MTX). However, the cause of drug-induced liver injury (DILI) is still unclear and unpredictable. Genetic risk factors may predispose for MTX-DILI. Therefore, we conducted a nested case-control genome-wide association study to explore genetic risk factors associated with MTX-DILI. Seven international groups contributed blood samples and data of patients with rheumatoid arthritis who used MTX. MTX-DILI was defined as an alanine aminotransferase (ALT) level of at least three times the upper limit of normal (ULN), to increase contrast controls ALT levels did not raise above two times the ULN. Per study site, control subjects and patients with MTX-DILI (ratio 3:1) were matched for age, gender, and duration of MTX use. Patients were genotyped using Illumina GSA MD-24v1-0 and data were imputed using the 1000 Genomes reference panel. Single-nucleotide polymorphisms (SNPs) were analyzed using an additive genetic model, corrected for sex, country, and age. A P-value of ≤ 5 × 10(-8) was considered significant, whereas a P-value of ≤ 5 × 10(-6) was considered suggestive. A total of 108 MTX-DILI cases and 311 controls were included for association analysis. None of the SNPs were significantly associated with MTX-DILI. However, we found seven suggestive genetic variants associated with MTX-DILI (P-values 7.43 × 10(-8) to 4.86 × 10(-6) ). Of those, five SNPs were in the intronic protein-coding regions of FTCDNL1, BCOR, FGF14, RBMS3, and PFDN4/DOK5. Investigation of candidates SPATA9 (rs72783407), PLCG2 (rs60427389), RAVER2 (rs72675408), JAK1 (rs72675451), PTPN2 (rs2476601), MTHFR C677T (rs1801133), and into the HLA region did not show significant findings. No genetic variants associated with MTX-DILI were found, whereas suggestive SNPs need further investigation. 01 april 2023

Pharmacogenetics (PGx) studies the effect of heritable genetic variation on drug response. Clinical adoption of PGx has remained limited, despite progress in the field. To promote implementation, the Dutch Pharmacogenetics Working Group (DPWG) develops evidence-based guidelines on how to optimize pharmacotherapy based on PGx test results. This guideline describes optimization of atomoxetine therapy based on genetic variation in the CYP2D6 gene. The CYP2D6 enzyme is involved in conversion of atomoxetine into the metabolite 4-hydroxyatomoxetine. With decreasing CYP2D6 enzyme activity, the exposure to atomoxetine and the risk of atomoxetine induced side effects increases. So, for patients with genetically absent CYP2D6 enzyme activity (CYP2D6 poor metabolisers), the DPWG recommends to start with the normal initial dose, bearing in mind that increasing this dose probably will not be required. In case of side effects and/or a late response, the DPWG recommends to reduce the dose and check for sustained effectiveness for both poor metabolisers and patients with genetically reduced CYP2D6 enzyme activity (CYP2D6 intermediate metabolisers). Extra vigilance for ineffectiveness is required in patients with genetically increased CYP2D6 enzyme activity (CYP2D6 ultra-rapid metabolisers). No interaction was found between the CYP2D6 and COMT genes and methylphenidate. In addition, no interaction was found between CYP2D6 and clonidine, confirming the suitability of clonidine as a possible alternative for atomoxetine in variant CYP2D6 metabolisers. The DPWG classifies CYP2D6 genotyping as being "potentially beneficial " for atomoxetine. CYP2D6 testing prior to treatment can be considered on an individual patient basis.

Aim: Use of immunomodulating therapeutics for immune-mediated inflammatory diseases may cause disease-drug-drug interactions (DDDIs) by reversing inflammation-driven alterations in the metabolic capacity of cytochrome P450 enzymes. European Medicine Agency (EMA) and US Food and Drug Administration (FDA) guidelines from 2007 recommend that the DDDI potential of therapeutic proteins should be assessed. This systematic analysis aimed to characterize the available DDDI trials with immunomodulatory drugs, experimental evidence for a DDDI risk and reported DDDI risk information in FDA/EMA approved drug labelling. Method: For this systematic review, the EMA list of European Public Assessment Reports of human medicine was used to select immunomodulating monoclonal antibodies (mAbs) and tyrosine kinase inhibitors (TKIs) marketed after 2007 at risk for a DDDI. Selected drugs were included in PubMed and Embase searches to extract reported interaction studies. The Summary of Product Characteristics (SPCs) and the United States Prescribing Information (USPIs) were subsequently used for analysis of DDDI risk descriptions. Results: Clinical interaction studies to evaluate DDDI risks were performed for 12 of the 24 mAbs (50%) and for none of the TKIs. Four studies identified a DDDI risk, of which three were studies with interleukin-6 (IL-6) neutralizing mAbs. Based on (non)clinical data, a DDDI risk was reported in 32% of the SPCs and in 60% of the USPIs. The EMA/FDA documentation aligned with the DDDI risk potential in 35% of the 20 cases. Conclusion: This systematic review reinforces that the risk for DDDI by immunomodulating drugs is target- and disease-specific. Drug labelling information designates the greatest DDDI risk to mAbs that neutralize the effects of IL-6, Tumor Necrosis Factor alfa (TNF-alpha) and interleukin-1 beta (IL-1 beta) in diseases with systemic inflammation.

The Dutch Pharmacogenetics Working Group (DPWG) aims to facilitate PGx implementation by developing evidence-based pharmacogenetics guidelines to optimize pharmacotherapy. This guideline describes the starting dose optimization of the anti-cancer drug irinotecan to decrease the risk of severe toxicity, such as (febrile) neutropenia or diarrhoea. Uridine diphosphate glucuronosyl transferase 1A1 (UGT1A1 encoded by the UGT1A1 gene) enzyme deficiency increases risk of irinotecan-induced toxicity. Gene variants leading to UGT1A1 enzyme deficiency (e.g. UGT1A1*6, *28 and *37) can be used to optimize an individual's starting dose thereby preventing carriers from toxicity. Homozygous or compound heterozygous carriers of these allele variants are defined as UGT1A1 poor metabolisers (PM). DPWG recommends a 70% starting dose in PM patients and no dose reduction in IM patients who start treatment with irinotecan. Based on the DPWG clinical implication score, UGT1A1 genotyping is considered "essential", indicating that UGT1A1 testing must be performed prior to initiating irinotecan treatment.

Pharmacogenomics (PGx)-guided drug treatment is one of the cornerstones of personalized medicine. However, the genes involved in drug response are highly complex and known to carry many (rare) variants. Current technologies (short-read sequencing and SNP panels) are limited in their ability to resolve these genes and characterize all variants. Moreover, these technologies cannot always phase variants to their allele of origin. Recent advance in long-read sequencing technologies have shown promise in resolving these problems. Here we present a long-read sequencing panel-based approach for PGx using PacBio HiFi sequencing.A capture based approach was developed using a custom panel of clinically-relevant pharmacogenes including up- and downstream regions. A total of 27 samples were sequenced and panel accuracy was determined using benchmarking variant calls for 3 Genome in a Bottle samples and GeT-RM star(*)-allele calls for 21 samples..The coverage was uniform for all samples with an average of 94% of bases covered at >30×. When compared to benchmarking results, accuracy was high with an average F1 score of 0.89 for INDELs and 0.98 for SNPs. Phasing was good with an average of 68% the target region phased (compared to ~20% for short-reads) and an average phased haploblock size of 6.6kbp. Using Aldy 4, we compared our variant calls to GeT-RM data for 8 genes (CYP2B6, CYP2C19, CYP2C9, CYP2D6, CYP3A4, CYP3A5, SLCO1B1, TPMT), and observed highly accurate star(*)-allele calling with 98.2% concordance (165/168 calls), with only one discordance inCYP2C9leading to a different predicted phenotype.We have shown that our long-read panel-based approach results in high accuracy and target phasing for SNVs as well as for clinical star(*)-alleles.

Pharmacogenetics (PGx) studies the effect of heritable genetic variation on drug response. Clinical adoption of PGx has remained limited, despite progress in the field. To promote implementation, the Dutch Pharmacogenetics Working Group (DPWG) develops evidence-based guidelines on how to optimize pharmacotherapy based on PGx test results. This guideline describes optimization of atomoxetine therapy based on genetic variation in the CYP2D6 gene. The CYP2D6 enzyme is involved in conversion of atomoxetine into the metabolite 4-hydroxyatomoxetine. With decreasing CYP2D6 enzyme activity, the exposure to atomoxetine and the risk of atomoxetine induced side effects increases. So, for patients with genetically absent CYP2D6 enzyme activity (CYP2D6 poor metabolisers), the DPWG recommends to start with the normal initial dose, bearing in mind that increasing this dose probably will not be required. In case of side effects and/or a late response, the DPWG recommends to reduce the dose and check for sustained effectiveness for both poor metabolisers and patients with genetically reduced CYP2D6 enzyme activity (CYP2D6 intermediate metabolisers). Extra vigilance for ineffectiveness is required in patients with genetically increased CYP2D6 enzyme activity (CYP2D6 ultra-rapid metabolisers). No interaction was found between the CYP2D6 and COMT genes and methylphenidate. In addition, no interaction was found between CYP2D6 and clonidine, confirming the suitability of clonidine as a possible alternative for atomoxetine in variant CYP2D6 metabolisers. The DPWG classifies CYP2D6 genotyping as being "potentially beneficial" for atomoxetine. CYP2D6 testing prior to treatment can be considered on an individual patient basis.

The Dutch Pharmacogenetics Working Group (DPWG) aims to facilitate PGx implementation by developing evidence-based pharmacogenetics guidelines to optimize pharmacotherapy. This guideline describes the gene-drug interaction of ABCG2 with allopurinol, HLA-B with allopurinol, MTHFR with folic acid, and MTHFR with methotrexate, relevant for the treatment of gout, cancer, and rheumatoid arthritis. A systematic review was performed based on which pharmacotherapeutic recommendations were developed. Allopurinol is less effective in patients with the ABCG2 p.(Gln141Lys) variant. In HLA-B*58:01 carriers, the risk of severe cutaneous adverse events associated with allopurinol is strongly increased. The DPWG recommends using a higher allopurinol dose in patients with the ABCG2 p.(Gln141Lys) variant. For HLA-B*58:01 positive patients the DPWG recommends choosing an alternative (for instance febuxostat). The DPWG indicates that another option would be to precede treatment with allopurinol tolerance induction. Genotyping of ABCG2 in patients starting on allopurinol was judged to be 'potentially beneficial' for drug effectiveness, meaning genotyping can be considered on an individual patient basis. Genotyping for HLA-B*58:01 in patients starting on allopurinol was judged to be 'beneficial' for drug safety, meaning it is advised to consider genotyping the patient before (or directly after) drug therapy has been initiated. For MTHFR-folic acid there is evidence for a gene-drug interaction, but there is insufficient evidence for a clinical effect that makes therapy adjustment useful. Finally, for MTHFR-methotrexate there is insufficient evidence for a gene-drug interaction.

Individual response to sunitinib in metastatic renal cell carcinoma (mRCC) patients is highly variable. Earlier, sunitinib outcome was related to single nucleotide polymorphisms (SNPs) in

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.

Pharmacogenomics (PGx) relates to the study of genetic factors determining variability in drug response. Implementing PGx testing in paediatric patients can enhance drug safety, helping to improve drug efficacy or reduce the risk of toxicity. Despite its clinical relevance, the implementation of PGx testing in paediatric practice to date has been variable and limited. As with most paediatric pharmacological studies, there are well-recognised barriers to obtaining high-quality PGx evidence, particularly when patient numbers may be small, and off-label or unlicensed prescribing remains widespread. Furthermore, trials enrolling small numbers of children can rarely, in isolation, provide sufficient PGx evidence to change clinical practice, so extrapolation from larger PGx studies in adult patients, where scientifically sound, is essential. This review paper discusses the relevance of PGx to paediatrics and considers implementation strategies from a child health perspective. Examples are provided from Canada, the Netherlands and the UK, with consideration of the different healthcare systems and their distinct approaches to implementation, followed by future recommendations based on these cumulative experiences. Improving the evidence base demonstrating the clinical utility and cost-effectiveness of paediatric PGx testing will be critical to drive implementation forwards. International, interdisciplinary collaborations will enhance paediatric data collation, interpretation and evidence curation, while also supporting dedicated paediatric PGx educational initiatives. PGx consortia and paediatric clinical research networks will continue to play a central role in the streamlined development of effective PGx implementation strategies to help optimise paediatric pharmacotherapy.

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.

Contains fulltext : 286842.pdf (Publisher’s version ) (Closed access) The Dutch Pharmacogenetics Working Group (DPWG) guideline presented here, presents the gene-drug interaction between the genes CYP2C19 and CYP2D6 and antidepressants of the selective serotonin reuptake inhibitor type (SSRIs). Both genes' genotypes are translated into predicted normal metabolizer (NM), intermediate metabolizer (IM), poor metabolizer (PM), or ultra-rapid metabolizer (UM). Evidence-based dose recommendations were obtained, based on a structured analysis of published literature. In CYP2C19 PM patients, escitalopram dose should not exceed 50% of the normal maximum dose. In CYP2C19 IM patients, this is 75% of the normal maximum dose. Escitalopram should be avoided in UM patients. In CYP2C19 PM patients, citalopram dose should not exceed 50% of the normal maximum dose. In CYP2C19 IM patients, this is 70% (65-75%) of the normal maximum dose. In contrast to escitalopram, no action is needed for CYP2C19 UM patients. In CYP2C19 PM patients, sertraline dose should not exceed 37.5% of the normal maximum dose. No action is needed for CYP2C19 IM and UM patients. In CYP2D6 UM patients, paroxetine should be avoided. No action is needed for CYP2D6 PM and IM patients. In addition, no action is needed for the other gene-drug combinations. Clinical effects (increase in adverse events or decrease in efficacy) were lacking for these other gene-drug combinations. DPWG classifies CYP2C19 genotyping before the start of escitalopram, citalopram, and sertraline, and CYP2D6 genotyping before the start of paroxetine as "potentially beneficial" for toxicity/effectivity predictions. This indicates that genotyping prior to treatment can be considered on an individual patient basis.

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.

Background and Objective In the randomized controlled trial REMAP-CAP, it was shown that next to dexamethasone, the interleukin (IL)-6 receptor antagonist tocilizumab improves outcome, including survival in intensive care unit (ICU)-admitted coronavirus disease 2019 (COVID)-19 patients. Therefore tocilizumab has been added to many COVID-19 treatment guidelines. Because obesity is a risk factor for the development of severe COVID-19, concerns have been raised about overtreatment, as well as undertreatment, through weight-based dosing of tocilizumab. The currently applied dose of 8 mg/kg is based on the use of this drug for other indications, however it has not formally been investigated for COVID-19. In this study, the pharmacokinetics and pharmacodynamics of tocilizumab were investigated in ICU-admitted COVID-19 patients. Methods This was an open-label, single-centre, observational population pharmacokinetic and descriptive pharmacodynamic evaluation study. Enrolled patients, with polymerase chain reaction-confirmed COVID-19 were admitted to the ICU for mechanical ventilation or high flow nasal canula oxygen support. All patients were 18 years of age or older and received intravenous tocilizumab 8 mg/kg (maximum 800 mg) within 24 h after admission to the ICU and received dexamethasone 6 mg daily as concomitant therapy. For evaluation of the pharmacokinetics and pharmacodynamics of tocilizumab, all time points from day 0 to 20 days after dose administration were eligible for collection. A nonlinear mixed-effects model was developed to characterize the population pharmacokinetic parameters of tocilizumab in ICU-admitted COVID-19 patients. Covariate analysis was performed to identify potential covariates for dose individualization. For the development of alternative dosing schedules, Monte Carlo simulations using the final model were performed. Results Overall, 29 patients were enrolled between 15 December 2020 and 15 March 2021. A total of 139 tocilizumab plasma samples were obtained covering the pharmacokinetic curve of day 0 to day 20 after tocilizumab initiation. A population pharmacokinetic model with parallel linear and nonlinear clearance (CL) was developed and validated. Average CL was estimated to be 0.725 L/day, average volume of distribution (Vd) was 4.34 L, maximum elimination rate (Vmax) was 4.19 μg/day, and concentration at which the elimination pathway is half saturated (Km) was 0.22 μg/mL. Interindividual variability was identified for CL (18.9%) and Vd (21%). Average area under the concentration versus time curve from time zero to infinity of the first dose (AUCinf 1st DOSE) was 938 [±190] μg/mL*days. All patients had tocilizumab exposure above 1 μg/mL for at least 15 days. Bodyweight-based dosing increases variability in exposure compared with fixed dosing. Conclusions This study provides evidence to support a fixed dose of tocilizumab 600 mg in COVID-19 patients. Fixed dosing is a safe, logistically attractive, and drug expenses saving alternative compared with the current 8 mg/kg recommendation. Supplementary Information The online version contains supplementary material available at 10.1007/s40262-021-01074-2.

The current Dutch Pharmacogenetics Working Group (DPWG) guideline, describes the gene-drug interaction between CYP2D6 and the opioids codeine, tramadol and oxycodone. CYP2D6 genotype is translated into normal metaboliser (NM), intermediate metaboliser (IM), poor metaboliser (PM) or ultra-rapid metaboliser (UM). Codeine is contraindicated in UM adults if doses20 mg every 6 h (q6h), in children ≥12 years if doses10 mg q6h, or with additional risk factors. In PMs, an alternative analgesic should be given which is not or to a lesser extent metabolised by CYP2D6 (not tramadol). In IMs with insufficient analgesia, a higher dose or alternative analgesic should be given. For tramadol, the recommendations for IMs and PMs are the same as the recommendation for codeine and IMs. UMs should receive an alternative drug not or to a lesser extent metabolised by CYP2D6 or the dose should be decreased to 40% of the commonly prescribed dose. Due to the absence of effect on clinical outcomes of oxycodone in PMs, IMs and UMs no action is required. DPWG classifies CYP2D6 genotyping for codeine "beneficial" and recommends testing prior to, or shortly after initiation of treatment in case of higher doses or additional risk factors. CYP2D6 genotyping is classified as "potentially beneficial" for tramadol and can be considered on an individual patient basis.

Contains fulltext : 286843.pdf (Publisher’s version ) (Closed access) The current Dutch Pharmacogenetics Working Group (DPWG) guideline, describes the gene-drug interaction between CYP2D6 and the opioids codeine, tramadol and oxycodone. CYP2D6 genotype is translated into normal metaboliser (NM), intermediate metaboliser (IM), poor metaboliser (PM) or ultra-rapid metaboliser (UM). Codeine is contraindicated in UM adults if doses >20 mg every 6 h (q6h), in children ≥12 years if doses >10 mg q6h, or with additional risk factors. In PMs, an alternative analgesic should be given which is not or to a lesser extent metabolised by CYP2D6 (not tramadol). In IMs with insufficient analgesia, a higher dose or alternative analgesic should be given. For tramadol, the recommendations for IMs and PMs are the same as the recommendation for codeine and IMs. UMs should receive an alternative drug not or to a lesser extent metabolised by CYP2D6 or the dose should be decreased to 40% of the commonly prescribed dose. Due to the absence of effect on clinical outcomes of oxycodone in PMs, IMs and UMs no action is required. DPWG classifies CYP2D6 genotyping for codeine "beneficial" and recommends testing prior to, or shortly after initiation of treatment in case of higher doses or additional risk factors. CYP2D6 genotyping is classified as "potentially beneficial" for tramadol and can be considered on an individual patient basis.

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.