Clopidogrel remains the most widely used P2Y₁₂ receptor inhibitor worldwide and is often used in combination with aspirin for secondary prevention in patients with arterial disease. The drug is associated with a wide response variability with one on three patients exhibiting little or no inhibition of adenosine diphosphate-induced platelet aggregation. It is a prodrug that is mainly metabolized by hepatic cytochrome P450 (CYP) 2C19. Patients who carry a CYP2C19 loss-of-function (LoF) allele have reduced metabolism of clopidogrel that is associated with reduced platelet inhibition compared to non-carriers that is associated with increased risk for thrombotic event occurrences, particularly, stent thrombosis. The United States Food and Drug Administration (US FDA) issued a black box warning in the clopidogrel label highlighting the importance of presence of CYP2C19 LOF allele during the insufficient metabolism of clopidogrel and availability of other potent P2Y₁₂ inhibitor for the treatment in CYP2C19 poor metabolizers. Clinical trials have conclusively demonstrated greater anti-ischemic benefits of prasugrel/ticagrelor in the treatment of patients carrying the CYP2C19 LoF allele. However, uniform use of these more potent P2Y₁₂ inhibitors has been associated with greater bleeding and cost, and lower adherence. The latter information provides a strong rationale for personalizing P2Y₁₂ inhibitor therapy based on the laboratory determination of CYP2C19 genotype. However, cardiologists have been slow to take up pharmacogenetic testing possibly due to lack of provider and patient education, clear cardiology guidelines and, and lack of positive results from adequately sized randomized clinical trials. However, current evidence strongly supports genotyping of patients who are candidates for clopidogrel. Physicians should strongly consider performing genetic tests to identify LoF carriers and treat these patients with more pharmacodynamically predictable P2Y₁₂ inhibitors than clopidogrel.

Percutaneous coronary intervention (PCI) is a widely used reperfusion strategy for coronary artery disease, with millions of procedures performed annually. Attention has recently been drawn to a unique population, known as \"bi-risk\" patients, who have high ischemic and high bleeding risks and undergo PCI. However, there is currently no established definition or optimal antithrombotic therapy for this group. Genotype-guided antithrombotic therapy, which uses cytochrome P450 (CYP) 2C19 gene testing, may offer a more personalized and precise approach. Nevertheless, recent research has shown that routine genetic testing to guide treatment in the PCI population does not improve patient outcomes, preventing it from being routinely recommended in guidelines. This review proposes, for the first time, the definition of the bi-risk population and the concept of TAILOR-BIRISK for their treatment strategies. TAILOR-BIRISK emphasizes de-escalating antithrombotic treatment and suggests that a short course of dual antiplatelet therapy (DAPT) followed by monotherapy by either clopidogrel or ticagrelor 60 mg BID (BID, twice daily) could be a reasonable option for this population. Additionally, the use of CYP2C19 gene testing to guide P2Y 12 inhibitor selection can help better individualize and customize the antithrombotic regimen. However, more large-sample randomized control studies should be conducted to further explore the optimal antithrombotic strategy for the bi-risk population.

BACKGROUND: Helicobacter pylori eradication therapy based on antimicrobial susceptibility in Vietnamese children currently get low efficiency. There are causes of treatment failure, among host genetic factors namely MDR1 C3435T and CYP2C19 affect the absorption and metabolism of proton pump inhibitors - a crucial component of eradication therapy. The study aimed to investigate the effect of MDR1 C3435T and CYP2C19 genetic polymorphisms on the cure rate.
METHODS: 207 pediatric patients with gastritis and peptic ulcer infecting Helicobacter pylori completed the eradication therapy based on antimicrobial susceptibility with proton pump inhibitor esomeprazole. Eradication efficacy was assessed after at least 4 weeks by the urease breath test. MDR1 C3435T genetic polymorphism and CYP2C19 genotype were determined using a sequencing method based on Sanger\'s principle.
RESULTS: Among 207 children recruited in this study, the ratio of CYP2C19 EM, IM, and PM phenotypes was 40.1%, 46.4%, and 16.9%, respectively. The patient with MDR1 3435 C/C polymorphism accounted for 43.0%, MDR1 3435 C/T was 40.1%, and MDR1 3435T/T was 16.9%. The cure rate of Helicobacter pylori infection in patients with CYP2C19 EM genotype was 78.3%; 83.3% of those with the IM genotype, and PM genotype was 96,4% (p = 0.07). Successful eradication rates for Helicobacter pylori were 85.4%, 86.7%, and 68.6% in patients with the MDR1 3435 C/C, C/T, and T/T, respectively (p = 0.02). Multiple logistic regression analysis found that MDR1 C3435T genetic polymorphisms of patients were significant independent risk factors for treatment failure, and CYP2C19 genotype did not affect Helicobacter pylori eradication.
CONCLUSIONS: The Helicobacter pylori eradication rates by regimens based on antibiotic susceptibility and esomeprazole were not significantly different between the CYP2C19 phenotypes. The MDR1 C3435T polymorphism is one of the factors impacting Helicobacter pylori eradication results in children.

Clothianidin, classified as a second-generation neonicotinoid, has achieved extensive application due to its high efficacy against insect pests. This broad-spectrum usage has resulted in its frequent detection in environmental surveys. CYP2C19 and CYP3A4 are crucial for converting clothianidin to desmethyl-clothianidin (dm-clothianidin). The expression of these CYP450s can be significantly influenced by genetic polymorphisms. The objective of our research was to examine the catalytic effects of 27 CYP3A4 variants and 31 CYP2C19 variants on the metabolism of clothianidin within recombinant insect microsomes. These variants were assessed through a well-established incubation procedure. In addition, the concentration of its metabolite dm-clothianidin was quantified by employing an ultra performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS). Lastly, the kinetic parameters of these CYP3A4 and CYP2C19 variants were calculated by applying Michaelis-Menten kinetic analysis to fit the data. The observed changes in enzyme activity were related to the metabolic transformation of clothianidin to dm-clothianidin. In the CYP2C19 metabolic pathway, one variant (CYP2C19.23) showed no notable change in intrinsic clearance (CLint), four variants (CYP2C19.29, .30, .31 and L16F) demonstrated a marked increase in CLint (110.86-183.46 %), and the remaining 25 variants exhibited a considerable decrease in CLint (26.38-89.79 %), with a maximum decrease of 73.62 % (CYP2C19.6). In the CYP3A4 metabolic pathway, 26 variants demonstrated significantly reduced CLint (10.54-52.52 %), with a maximum decrease of 89.46 % (CYP3A4.20). Our results suggested that most variants of CYP3A4 and CYP2C19 significantly altered the enzymatic activities associated with clothianidin metabolism to various degrees. This study provides new insights into assessing the metabolic behavior of pesticides and delivers crucial data that can guide clinical detoxification strategies.

OBJECTIVE: The genetic polymorphism of CYP2C19 influences clopidogrel metabolism and resistance. Aim was to assess the association between CYP2C19 loss of function variation, clopidogrel resistance based on platelet reactivity units and clinical outcomes.
METHODS: A total of 668 patients of Acute Coronary Sundrome (ACS) who underwent Percutaneous Coronary Intervention (PCI) were subjected to genetic screening and 143 patients undrewent platelet function test to study the association between drug metabolization and its effects based on platelet reactivity unit values.
RESULTS: Clopidogrel resistance with CYP2C 19 loss of function variation was noted in 54.64% of patients. Clinical outcomes, such as target vessel revascularization, target lesion revascularization, in-stent restenosis, and stent thrombosis, were also studied.
CONCLUSIONS: CYP2C19 loss of function variation is strongly associated with clopidogrel resistance and adverse clinical outcomes.

UNASSIGNED: Aspirin and anti-P2Y12 are widely prescribed in cardiovascular patients, often in combination with proton pump inhibitors (PPIs) to limit the risk of upper gastrointestinal bleedings. The potential interaction between PPIs and antiplatelet agents has been widely discussed, but doubts remain as to whether PPIs may reduce the cardiovascular protection provided by aspirin, prasugrel, ticagrelor, and clopidogrel.
UNASSIGNED: Many pharmacokinetic (PK) and pharmacodynamic (PD) studies have confirmed the interaction, especially between PPIs and clopidogrel, but with uncertain consequences on clinical outcomes. Therefore, we aimed to summarize the evidence for the widespread combined use of oral antiplatelet drugs and PPIs, to outline the current evidence supporting or opposing drug-drug interaction, and to discuss the clinical implications of such interactions.
UNASSIGNED: A large body of evidence describes the PK/PD interaction of antiplatelet drugs with PPIs and its potential role in increasing clinical cardiovascular adverse events, but no solid clinical data have confirmed these effects. In the light of the published studies, there seems to be no restriction on the choice of PPI with aspirin, prasugrel, and/or ticagrelor. The choice of a PPI with no (or minimal) interference with the hepatic cytochrome P450 2C19 is preferred in patients receiving clopidogrel.

OBJECTIVE: The aim of the present study was to investigate the impact of CYP2D6 genotype on exposure and metabolism of escitalopram in patients stratified by CYP2C19 genotype in a large real-world population.
METHODS: Patients were included from a therapeutic drug monitoring service if they had measured serum concentration of escitalopram and the metabolite, N-desmethyl escitalopram, and performed CYP2C19 and CYP2D6 genotyping. Patients were divided into 16 combined genotype-predicted phenotype subgroups (poor [PM], intermediate [IM], normal [NM] and ultrarapid metabolizers [UM]) of CYP2C19/CYP2D6. The concentration-to-dose (CD) ratio and metabolite-to-parent ratio (metabolic ratio) of escitalopram were compared across subgroups using the Kruskal-Wallis test followed by Dunn\'s test with CYP2D6 NMs as the reference group.
RESULTS: A total of 5067 patients were included in the study. A stepwise increase in escitalopram CD ratio by decreasing CYP2D6 activity was observed in all CYP2C19 subgroups, except for in CYP2C19 UMs. The percentage differences in escitalopram CD ratio between CYP2D6 PMs and NMs were 24% in CYP2C19 NMs (P < .001), 28% in CYP2C19 IMs (P < .001) and 31% in CYP2C19 PMs (P = .04). As for the CD ratio, CYP2D6 genotype effect on metabolic ratio increased stepwise by decreasing CYP2C19 metabolism.
CONCLUSIONS: CYP2D6 genotype is of significant importance for the individual variation in escitalopram pharmacokinetics. The most relevant increase in escitalopram concentration is seen in individuals with decreased and/or absent CYP2C19 activity. By combining CYP2C19 and CYP2D6 genotypes, the optimal dose for patients may be predicted with greater precision than for CYP2C19 genotype alone.

BACKGROUND: Cytochrome P450 (CYP) are phase I metabolizing enzymes involved in detoxification of chemotherapeutic agents. Among the CYP gene family, including CYP1A1, CYP1B1, CYP2C, CYP2D, CYP2E and CYP17, their significance in cancer susceptibility is well established. However, there remains limited understanding regarding the polymorphisms of CYP2C19*2 and CYP17 and their potential correlation with chemotherapy-induced toxicity reactions in breast cancer (BC) patients. In this study we intended to identify the association of CYP2C19*2 and CYP17 gene polymorphisms on drug response as well as toxicity reactions in BC patients undergoing adriamycin/paclitaxel based chemotherapy within Indian population.
METHODS: Two hundred BC patients receiving adriamycin and paclitaxel chemotherapy were enrolled in this study and chemotherapy induced hematological and non-hematological toxicity reactions were noted. The polymorphisms of CYP2C19*2 (681G>A) and CYP17 (34T>C) isoforms of cytochrome p 450 gene was studied by PCR and RFLP analysis.
RESULTS: The univariate logistic regression analysis revealed significant associations between CYP2C19*2 (681 G>A) polymorphisms with hematological toxicities i.e., anemia (OR=9.77, 95% CI: 2.84-33.52; p=0.0003), neutropenia (OR=5.72, 95% CI: 1.75-18.68; p=0.003), febrile neutropenia (OR=4.29, 95% CI: 1.32-13.87; p=0.014) and thrombocytopenia (OR=5.86, 95% CI: 1.15-29.72); p=0.032) in BC patients. Additionally BC patients treated with adriamycin exhibited significant association between CYP2C19*2 polymorphism with chemotherapy induced nausea and vomiting (CINV) (OR=99.73, 95% CI: 5.70-174.64); p=0.001), fatigue (OR=83.29, 95% CI: 4.77-145.69); p=0.002), bodyache (OR=4.44, 95% CI: 1.24-15.91); p=0.021) and peripheral neuropathy (OR=12.00, 95% CI: 1.80-79.89); p=0.010. Furthermore, the regression analysis indicated an association between CYP17 with body ache (OR=2.77, 95% CI: 1.21-6.34; p=0.015) and peripheral neuropathy (OR=3.90, 95% CI: 1.59-9.53; p=0.002) in BC patients treated with paclitaxel chemotherapy.
CONCLUSIONS: The findings obtained from this study illustrated significant association of CYP2C9*2 (681G>A) polymorphism with adreamicin based chemotherapy induced toxicities and CYP17 (34T>C) polymorphism with paclitaxel induced bodyache and peripheral neuropathy in BC patients.

BACKGROUND: Voriconazole pharmacokinetics (PK) are known to be affected by genetic polymorphisms of drug-metabolizing enzymes such as CYP2C19; however, such information is limited for the pediatric population. The primary aim of this study is to establish a voriconazole PK model incorporating CYP2C19 phenotypes in Japanese children with malignancy or inborn errors of immunity.
METHODS: CYP2C19 genotypes were assessed by whole-genome genotyping and defined as follows: *17/*17: ultrarapid metabolizer (URM), *1/*17: rapid metabolizer (RM), *1/*1:normal metabolizer (NM), *1/*2, *1/*3, *2/*17:intermediate metabolizer (IM), and *2/*2, *2/*3, *3/*3: poor metabolizer (PM). Population PK analysis was performed. The voriconazole serum concentration profile was described by a two-compartment model with first-order absorption, mixed linear and nonlinear (Michaelis-Menten) elimination.
RESULTS: Voriconazole concentration data were available from 60 patients with a median age of 5.3 years. The phenotypes predicted from CYP2C19 genotypes were RM in 1 (2 %), NM in 21 (35 %) patients, IM in 27 (45 %) patients, and PM in 11 (18 %) patients. Underlying diseases included 38 (63%) patients with hematological malignancy and 18 (30 %) patients with inborn errors of immunity. Among the CYP2C19 phenotypes, PM was predicted to show complete inhibition (the degree of Vmax inhibition [Vmax, inh] = 100 %; Vmax = 0). The estimated parameters of Vmax,inh were +0.8 higher in patients with gamma-glutamyl transpeptidase (γ-GTP) Grade 2 or higher and +2.7 higher when C-reactive protein (CRP) levels were 2.0 mg/dL or higher.
CONCLUSIONS: CYP2C19 genetic polymorphisms, γ-GTP, and CRP affect Vmax,inh of voriconazole in children with malignancy or inborn errors of immunity.

Pharmaceutical researchers are continually searching for techniques to improve both drug development processes and patient outcomes. An area of recent interest is the potential for machine learning (ML) applications within pharmacology. One such application not yet given close study is the unsupervised clustering of plasma concentration-time curves, hereafter, pharmacokinetic (PK) curves. In this paper, we present our findings on how to cluster PK curves by their similarity. Specifically, we find clustering to be effective at identifying similar-shaped PK curves and informative for understanding patterns within each cluster of PK curves. Because PK curves are time series data objects, our approach utilizes the extensive body of research related to the clustering of time series data as a starting point. As such, we examine many dissimilarity measures between time series data objects to find those most suitable for PK curves. We identify Euclidean distance as generally most appropriate for clustering PK curves, and we further show that dynamic time warping, Fréchet, and structure-based measures of dissimilarity like correlation may produce unexpected results. As an illustration, we apply these methods in a case study with 250 PK curves used in a previous pharmacogenomic study. Our case study finds that an unsupervised ML clustering with Euclidean distance, without any subject genetic information, is able to independently validate the same conclusions as the reference pharmacogenomic results. To our knowledge, this is the first such demonstration. Further, the case study demonstrates how the clustering of PK curves may generate insights that could be difficult to perceive solely with population level summary statistics of PK metrics.