CYP2C9 and CYP2C19 polymorphic forms are related to increased indisulam exposure and higher risk of severe hematologic toxicity

Novel models for the prediction of drug-gene interactions

INTRODUCTION

Adverse drug reactions (ADRs) are among the leading causes of death, and frequently associated with drug-gene interactions (DGIs). In addition to pharmacogenomic programs for implementation of genetic preemptive testing into clinical practice, mathematical modeling can help to understand, quantify and predict the effects of DGIs in vivo. Moreover, modeling can contribute to optimize prospective clinical drug trial activities and to reduce DGI-related ADRs.

AREAS COVERED

Approaches and challenges of mechanistical DGI implementation and model parameterization are discussed for population pharmacokinetic and physiologically based pharmacokinetic models. The broad spectrum of published DGI models and their applications is presented, focusing on the investigation of DGI effects on pharmacology and model-based dose adaptations.

EXPERT OPINION

Mathematical modeling provides an opportunity to investigate complex DGI scenarios and can facilitate the development process of safe and efficient personalized dosing regimens. However, reliable DGI model input data from in vivo and in vitro measurements are crucial. For this, collaboration among pharmacometricians, laboratory scientists and clinicians is important to provide homogeneous datasets and unambiguous model parameters. For a broad adaptation of validated DGI models in clinical practice, interdisciplinary cooperation should be promoted and qualification toolchains must be established.

Pharmacogenetics of toxicity of 5-fluorouracil, doxorubicin and cyclophosphamide chemotherapy in breast cancer patients

The differences in patients' response to the same medication, toxicity included, are one of the major problems in breast cancer treatment. Chemotherapy toxicity makes a significant clinical problem due to decreased quality of life, prolongation of treatment and reinforcement of negative emotions associated with therapy. In this study we evaluated the genetic and clinical risk factors of FAC chemotherapy-related toxicities in the group of 324 breast cancer patients. Selected genes and their polymorphisms were involved in FAC drugs transport (ABCB1, ABCC2, ABCG2,SLC22A16), metabolism (ALDH3A1, CBR1, CYP1B1, CYP2C19, DPYD, GSTM1, GSTP1, GSTT1, MTHFR,TYMS), DNA damage recognition, repair and cell cycle control (ATM, ERCC1, ERCC2, TP53, XRCC1). The multifactorial risk models that combine genetic risk modifiers and clinical characteristics were constructed for 12 toxic symptoms. The majority of toxicities was dependent on the modifications in components of more than one pathway of FAC drugs, while the impact level of clinical factors was comparable to the genetic ones. For the carriers of multiple high risk factors the chance of developing given symptom was significantly elevated which proved the factor-dosage effect. We found the strongest associations between concurrent presence of clinical factors - overall and recurrent anemia, nephrotoxicity and early nausea and genetic polymorphisms in genes responsible for DNA repair, drugs metabolism and transport pathways. These results indicate the possibility of selection of the patients with expected high tolerance to FAC treatment and consequently with high chance of chemotherapy completion without the dose reduction, treatment delays and decline in the quality of life.

High CYP2C19 phenotypic variability in gastrointestinal cancer patients

PURPOSE

CYP2C19 contributes to the metabolism of several chemotherapeutic agents. The CYP2C19 homozygous null function genotype strongly predicts activity phenotype in healthy populations. An additional acquired loss of function has been reported in up to one-third of cancer patients. It is not known whether this phenomenon also occurs in patients with earlier stage or in resected disease.

METHODS

This study investigated whether acquired loss of CYP2C19 function was detectable in patients with stage III-IV or resected gastrointestinal cancer. CYP2C19 genotype was determined in 49 patients, and subjects were probed for CYP2C19 activity on three test occasions.

RESULTS

An acquired loss of CYP2C19 activity was observed in 20% of stage III-IV and 17% of resected patients at the first test. Significant (p < 0.01) genotype-phenotype discordance was observed in both groups. There were no direct associations between this discordance and inflammatory markers, tumour burden or chemotherapeutic history. Notably, hepatic CYP2C19 function was not stable over time and phenotype conversion occurred in 23 patients over the period of testing.

CONCLUSION

Reliance on germ-line genotype to infer a poor metaboliser status could substantially underestimate the number of patients with deficient CYP2C19 function. This could compromise the interpretation of genotype-based clinical association studies.

Mass spectrometry based identification of geometric isomers during metabolic stability study of a new cytotoxic sulfonamide derivatives supported by quantitative structure-retention relationships

A set of 15 new sulphonamide derivatives, presenting antitumor activity have been subjected to a metabolic stability study. The results showed that besides products of biotransformation, some additional peaks occurred in chromatograms. Tandem mass spectrometry revealed the same mass and fragmentation pathway, suggesting that geometric isomerization occurred. Thus, to support this hypothesis, quantitative structure-retention relationships were applied. Human liver microsomes were used as an in vitro model of metabolism. The biotransformation reactions were tracked by liquid chromatography assay and additionally, fragmentation mass spectra were recorded. In silico molecular modeling at a semi-empirical level was conducted as a starting point for molecular descriptor calculations. A quantitative structure-retention relationship model was built applying multiple linear regression based on selected three-dimensional descriptors. The studied compounds revealed high metabolic stability, with a tendency to form hydroxylated biotransformation products. However, significant chemical instability in conditions simulating human body fluids was noticed. According to literature and MS data geometrical isomerization was suggested. The developed in sillico model was able to describe the relationship between the geometry of isomer pairs and their chromatographic retention properties, thus it supported the hypothesis that the observed pairs of peaks are most likely geometric isomers. However, extensive structural investigations are needed to fully identify isomers' geometry. An effort to describe MS fragmentation pathways of novel chemical structures is often not enough to propose structures of potent metabolites and products of other chemical reactions that can be observed in compound solutions at early drug discovery studies. The results indicate that the relatively non-expensive and not time- and labor-consuming in sillico approach could be a good supportive tool assisting the identification of cis-trans isomers based on retention data. This methodology can be helpful during the structural identification of biotransformation and degradation products of new chemical entities--potential new drugs.

Impact of genetic polymorphisms in CYP2C9 and CYP2C19 on the pharmacokinetics of clinically used drugs

Human cytochrome P450 (CYP) is a superfamily of hemoproteins which oxidize a number of endogenous compounds and xenobiotics. The human CYP2C subfamily consists of four members: CYP2C8, CYP2C9, CYP2C18 and CYP2C19. CYP2C9 and CYP2C19 are important drug-metabolizing enzymes and together metabolize approximately 20% of therapeutically used drugs. Forty-two allelic variants for CYP2C9 and 34 for CYP2C19 have been reported. The frequencies of these variants show marked inter-ethnic variation. The functional consequences of genetic polymorphisms have been examined, and many studies have shown the clinical importance of these polymorphisms. Current evidence suggests that taking the genetically determined metabolic capacity of CYP2C9 and CYP2C19 into account has the potential to improve individual risk/benefit relationships. However, more prospective studies with clinical endpoints are needed before the paradigm of "personalized medicine" based on the variants can be established. This review summarizes the currently available important information on this topic.

Performance of methods for handling missing categorical covariate data in population pharmacokinetic analyses

In population pharmacokinetic analyses, missing categorical data are often encountered. We evaluated several methods of performing covariate analyses with partially missing categorical covariate data. Missing data methods consisted of discarding data (DROP), additional effect parameter for the group with missing data (EXTRA), and mixture methods in which the mixing probability was fixed to the observed fraction of categories (MIX(obs)), based on the likelihood of the concentration data (MIX(conc)), or combined likelihood of observed covariate data and concentration data (MIX(joint)). Simulations were implemented to study bias and imprecision of the methods in datasets with equal-sized and unbalanced category ratios for a binary covariate as well as datasets with non-random missingness (MNAR). Additionally, the performance and feasibility of implementation was assessed in two real datasets. At either low (10%) or high (50%) levels of missingness, all methods performed similarly well. Performance was similar for situations with unbalanced datasets (3:1 covariate distribution) and balanced datasets. In the MNAR scenario, the MIX methods showed a higher bias in the estimation of CL and covariate effect than EXTRA. All methods could be applied to real datasets, except DROP. All methods perform similarly at the studied levels of missingness, but the DROP and EXTRA methods provided less bias than the mixture methods in the case of MNAR. However, EXTRA was associated with inflated type I error rates of covariate selection, while DROP handled data inefficiently.

Covariate pharmacokinetic model building in oncology and its potential clinical relevance

When modeling pharmacokinetic (PK) data, identifying covariates is important in explaining interindividual variability, and thus increasing the predictive value of the model. Nonlinear mixed-effects modeling with stepwise covariate modeling is frequently used to build structural covariate models, and the most commonly used software-NONMEM-provides estimations for the fixed-effect parameters (e.g., drug clearance), interindividual and residual unidentified random effects. The aim of covariate modeling is not only to find covariates that significantly influence the population PK parameters, but also to provide dosing recommendations for a certain drug under different conditions, e.g., organ dysfunction, combination chemotherapy. A true covariate is usually seen as one that carries unique information on a structural model parameter. Covariate models have improved our understanding of the pharmacology of many anticancer drugs, including busulfan or melphalan that are part of high-dose pretransplant treatments, the antifolate methotrexate whose elimination is strongly dependent on GFR and comedication, the taxanes and tyrosine kinase inhibitors, the latter being subject of cytochrome p450 3A4 (CYP3A4) associated metabolism. The purpose of this review article is to provide a tool to help understand population covariate analysis and their potential implications for the clinic. Accordingly, several population covariate models are listed, and their clinical relevance is discussed. The target audience of this article are clinical oncologists with a special interest in clinical and mathematical pharmacology.

Part 2: pharmacogenetic variability in drug transport and phase I anticancer drug metabolism

Equivalent drug doses in anticancer chemotherapy may lead to wide interpatient variability in drug response reflected by differences in treatment response or in severity of adverse drug reactions. Differences in the pharmacokinetic (PK) and pharmacodynamic (PD) behavior of a drug contribute to variation in treatment outcome among patients. An important factor responsible for this variability is genetic polymorphism in genes that are involved in PK/PD processes, including drug transporters, phase I and II metabolizing enzymes, and drug targets, and other genes that interfere with drug response. In order to achieve personalized pharmacotherapy, drug dosing and treatment selection based on genotype might help to increase treatment efficacy while reducing unnecessary toxicity. We present a series of four reviews about pharmacogenetic variability in anticancer drug treatment. This is the second review in the series and is focused on genetic variability in genes encoding drug transporters (ABCB1 and ABCG2) and phase I drug-metabolizing enzymes (CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, DPYD, CDA and BLMH) and their associations with anticancer drug treatment outcome. Based on the literature reviewed, opportunities for patient-tailored anticancer therapy are presented.

Development of primer-special TaqMan PCR: a novel SNP detection method to detect CYP2C9 3 in South Chinese

BACKGROUND

CYP2C9 3 (1075A/C) is an inherited single nuclear polymorphism (SNP) of cytochrome P450 (CYP) 2C9, which affects the activity of the enzyme. In vitro studies with several drugs have indicated that the CYP2C9 3 variant has an impaired capacity for drug metabolism. Therefore an efficient detection assay for this mutation may be important for clinical dose adjustment.

OBJECTIVE

The aim of this work was to develop an appropriate tool for detection of the CYP2C9 3 polymorphism in the clinical laboratory.

STUDY DESIGN

The previously described TaqMan mismatch amplification mutation assay (TaqMAMA) was modified to a primer-special (PS)-TaqMan PCR to satisfy the high-throughput requirements of a clinical laboratory. 404 genomic DNA samples from South Chinese individuals were genotyped to test the detection system. The results were checked by bi-directional sequencing.

RESULTS

PS-TaqMan PCR could correctly genotype the CYP2C9 allele from a genomic template at a concentration of 1 x 104 to 1 x 1011 copies/PCR. Among the 404 genomic DNA samples, 24 heterozygotes and 380 wild-type homozygotes were detected and confirmed by bi-directional sequencing.

CONCLUSION

PS-TaqMan PCR was successfully developed for CYP2C9 3 detection. This efficient, reliable, high-throughput tool could satisfy the requirements of a clinical laboratory test.

Genetic polymorphism of metabolic enzymes P450 (CYP) as a susceptibility factor for drug response, toxicity, and cancer risk

The polymorphic P450 (CYP) enzyme superfamily is the most important system involved in the biotransformation of many endogenous and exogenous substances including drugs, toxins, and carcinogens. Genotyping for CYP polymorphisms provides important genetic information that help to understand the effects of xenobiotics on human body. For drug metabolism, the most important polymorphisms are those of the genes coding for CYP2C9, CYP2C19, CYP2D6, and CYP3A4/5, which can result in therapeutic failure or severe adverse reactions. Genes coding for CYP1A1, CYP1A2, CYP1B1, and CYP2E1 are among the most responsible for the biotransformation of chemicals, especially for the metabolic activation of pre-carcinogens. There is evidence of association between gene polymorphism and cancer susceptibility. Pathways of carcinogen metabolism are complex, and are mediated by activities of multiple genes, while single genes have a limited impact on cancer risk. Multigenic approach in addition to environmental determinants in large sample studies is crucial for a reliable evaluation of any moderate gene effect. This article brings a review of current knowledge on the relations between the polymorphisms of some CYPs and drug activity/toxicity and cancer risk.

Covariate-based dose individualization of the cytotoxic drug indisulam to reduce the risk of severe myelosuppression

AIM

Chemotherapy with indisulam causes myelosuppression. This study aimed to evaluate the influence of patient-related covariates on pharmacokinetics and pharmacodynamics, to identify patients at risk for severe myelosuppression and to develop a dosing algorithm for treatment optimization.

METHODS

Pharmacokinetic and pharmacodynamic data of 412 patients were available. Non-linear mixed effects modeling was used to determine the relative risk of dose-limiting myelosuppression for various covariates (demographics, physical condition, prior treatment, comedication, CYP2C genotype and biochemistry).

RESULTS

Body surface area (BSA), race and CYP2C genotype had a significant impact on indisulam elimination (P < 0.001). Low BSA, Japanese race, variant CYP2C genotype, low baseline neutrophil and thrombocyte counts and female sex were clinically relevant risk factors of dose-limiting myelosuppression (RR > 1.1). A dosing strategy was developed to optimize treatment for patient subgroups.

CONCLUSIONS

This study has identified covariates related to an increased risk of myelosuppression after indisulam therapy. Dose individualization may contribute to treatment optimization.

Population pharmacokinetic and pharmacodynamic analysis to support treatment optimization of combination chemotherapy with indisulam and carboplatin

AIMS

Indisulam and carboplatin have shown synergistic activity in preclinical studies. In a dose escalation study of the combination, a treatment delay was frequently required in a 3-weekly regimen to allow recovery from myelosuppression from previous cycles. A 4-weekly regimen was better tolerated, but had a decreased dose-intensity which may compromise efficacy. The aims of this study were (i) to develop a pharmacokinetic-pharmacodynamic (PK-PD) model to describe the myelosuppressive effect of the combination, and (ii) to use this model to select a dosing regimen for Phase II evaluation.

METHODS

Sixteen patients were treated at four different dose levels of indisulam (1-h infusion on day 1) and carboplatin (30-min infusion on day 2). Pharmacokinetic data were analysed with nonlinear mixed effects modelling. A semiphysiological model describing chemotherapy-induced myelosuppression characterized the relationship between the pharmacokinetics and the haematological toxicity of indisulam and carboplatin. A simulation study was performed to evaluate the tolerability and dose-intensity for 3-weekly and 4-weekly treatment regimens.

RESULTS

The PK-PD model described the pharmacokinetics and the myelosuppressive effect of indisulam and carboplatin. The risk of a treatment delay at cycle 2 due to myelosuppression was unacceptably high (34-65%) in a 3-weekly regimen for various dose levels (350-600 mg m(-2) indisulam in combination with carboplatin to achieve an AUC of 4-6 mg min(-1) ml(-1)). This risk was acceptable for a 4-weekly regimen (9-24%), which is in line with the clinical study results.

CONCLUSIONS

This PK-PD study supports the selection of indisulam 500 mg m(-2) and a dose of carboplatin to achieve an AUC of 6 mg min(-1) ml(-1) in a 4-weekly regimen as the recommended dose for future studies.

A Pharmacokinetic and Pharmacogenetic Study of Efavirenz in Children: Dosing Guidelines can Result in Subtherapeutic Concentrations

Background

Our main objectives were to study the population pharmacokinetics of efavirenz and to explore the adequacy of dosing guidelines.

Methods

A total of 33 HIV-1-infected patients were recruited from the Emma Children's Hospital (Amsterdam, the Netherlands). Gender, age, drug formulation, the presence of the c.516G>T polymorphism in the CYP2B6 gene and the quantitation of liver enzymes alanine aminotransferase and aspartate aminotransferase at baseline were collected. A non-linear mixed effect pharmacokinetic model was developed.

Results

CYP2B6 genotype and drug formulation significantly influenced efavirenz pharmacokinetics. Clearance was 29.7% lower in children carrying the CYP2B6-516-G/T genotype compared with children carrying the G/G genotype. Relative bioavailiability of the oral liquid compared with tablets or capsules was 46.6%. Children carrying the CYP2B6-516-G/G genotype had a 50–70% probability of developing a subtherapeutic trough level of efavirenz and only 1–3% probability of developing a trough level >4 mg/l. To reduce the probability of developing a subtherapeutic trough concentration, we propose to give an adult efavirenz dose to children weighing ≥25 kg and to allometrically scale doses for other weight levels a priori. The dose of the oral solution should be twice the dose of capsules.

Conclusions

Population pharmacokinetics of efavirenz in children were adequately described. Current dosing guidelines can result in subtherapeutic concentrations in children carrying the CYP2B6-516-G/G genotype and with the liquid formulation. A priori dose adaptations in the paediatric population seem feasible and need prospective validation.

PK/PD model of indisulam and capecitabine: interaction causes excessive myelosuppression

The anticancer agent indisulam was evaluated in a dose-escalation study in combination with capecitabine. Severe myelotoxicity was observed after multiple treatment cycles. We hypothesized that capecitabine inhibits the synthesis of CYP2C9, which metabolizes indisulam. The objectives were to develop a pharmacokinetic/pharmacodynamic (PK/PD) model for the combination treatment and to estimate the impact of a drug-drug interaction on the safety of various dose levels. NONMEM was used to develop a PK/PD model, including the impact of capecitabine coadministration on indisulam pharmacokinetics. A simulation study was performed to evaluate the risk of dose-limiting neutropenia. A time-dependent pharmacokinetic drug-drug interaction resulted in increased exposure to indisulam and in increased myelotoxicity. The risk of dose-limiting neutropenia increased with treatment duration and with dose. The excessive myelosuppression after multiple cycles may be explained by a pharmacokinetic interaction between indisulam and capecitabine. The combination of 550 mg/m(2) indisulam and 1,250 mg/m(2) capecitabine twice daily was considered safe.