A mechanism-based pharmacokinetic model for the cytochrome P450 drug-drug interaction between cyclophosphamide and thioTEPA and the autoinduction of cyclophosphamide

A Novel Algorithm to Improve PrEP Adherence Monitoring Using Dried Blood Spots

Tenofovir diphosphate (TFVdp; an active metabolite of oral HIV pre-exposure prophylaxis (PrEP)) is measured in dried blood spots (DBS) to estimate adherence. However, TFVdp's long half-life in whole blood may lead to misclassification following a recent change in adherence. PrEP's other metabolite, emtricitabine triphosphate (FTCtp), has a shorter half-life in whole blood but adherence thresholds are undefined. We characterized DBS TFVdp and FTCtp concentrations across many dosing scenarios. Population pharmacokinetic models were fit to TFVdp and FTCtp DBS concentrations from a directly observed therapy study (NCT03218592). Concentrations were simulated for 90 days of daily dosing followed by 90 days of 1 to 7 doses/week and for event-driven PrEP (edPrEP) scenarios. Thresholds of 1,000 and 200 fmol/punch, for TFVdp and FTCtp, respectively, were reflective of taking 4 doses/week (a minimum target for effective PrEP in men). TFVdp was < 1,000 fmol/punch for 17 days after initiating daily PrEP and > 1,000 fmol/punch for 62 days after decreasing to 3 doses/week. Respectively, FTCtp was < 200 fmol/punch for 4 days and > 200 fmol/punch for 6 days. Accuracy of edPrEP adherence classification depended on duration between last sex act and DBS sampling for both measures with misclassification ranging from 9-100%. These data demonstrate adherence misclassification by DBS TFVdp for 2 months following a decline in adherence, elucidating the need for FTCtp to estimate recent adherence. We provide proof of principle that individualized interpretation is needed to support edPrEP adherence monitoring. Our collective approach facilitates clinicians' ability to interpret DBS results and administer patient-centric interventions.

Overestimation of the effect of (fos)aprepitant on intravenous dexamethasone pharmacokinetics requires adaptation of the guidelines for children with chemotherapy-induced nausea and vomiting

Purpose

Chemotherapy-induced nausea and vomiting (CINV) are common side effects in pediatric oncology treatment. Besides 5-HT₃-antagonists, both dexamethasone and aprepitant are cornerstone drugs in controlling these side effects. Based on results of adult studies, the dexamethasone dose is reduced by 50% when combined with aprepitant, because of a drug-drug interaction, even though data on the interaction in children is lacking. The current study was developed to investigate the effect of aprepitant on dexamethasone clearance (CL) in children, in order to assess if dexamethasone dose reduction for concomitant use of aprepitant is appropriate in the current antiemetic regimen.

Methods

In total, 65 children (0.6–17.9 years), receiving intravenous or oral antiemetic therapy (dexamethasone ± aprepitant) as standard of care, were included. 305 dexamethasone plasma concentrations were determined using LC–MS/MS. An integrated dexamethasone and aprepitant pharmacokinetic model was developed using non-linear mixed effects modelling in order to investigate the effect of aprepitant administration on dexamethasone CL.

Results

In this population, dexamethasone CL in patients with concomitant administration of aprepitant was reduced by approximately 30% of the uninhibited CL (23.3 L/h (95% confidence interval 20.4–26.0)). This result is not consistent with the results of adult studies (50% reduction). This difference was not age dependent, but might be related to the route of administration of dexamethasone. Future studies are needed to assess the difference in oral/intravenous dexamethasone.

Conclusion

When dexamethasone is given intravenously as a component of triple therapy to prevent CINV in children, we advise to reduce the dexamethasone dose by 30% instead of 50%.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00520-022-07423-6.

Population Pharmacokinetic, Pharmacogenetic, and Pharmacodynamic Analysis of Cyclophosphamide in Ethiopian Breast Cancer Patients

Cyclophosphamide (CPA) containing chemotherapy regimen is the standard of care for breast cancer treatment in sub-Saharan Africa. Wide inter-individual variations in pharmacokinetics (PK) of cyclophosphamide (CPA) influence the efficacy and toxicity of CPA containing chemotherapy. Data on the pharmacokinetics (PK) profile of CPA and its covariates among black African patients is lacking. We investigated population pharmacokinetic/pharmacogenetic/pharmacodynamic (PK-PG-PD) of CPA in Ethiopian breast cancer patients. During the first cycle of CPA-based chemotherapy, the population PK parameters for CPA were determined in 267 breast cancer patients. Absolute neutrophil count was recorded at baseline and day 20 post-CPA administration. A population PK and covariate model analysis was performed using non-linear mixed effects modeling. Semi-mechanistic and empiric drug response models were explored to describe the relationship between the area under concentration-time curve (AUC), and neutrophil toxicity. One compartment model better described CPA PK with population clearance and apparent volume of distribution (V_D) of 5.41 L/h and 46.5 L, respectively. Inter-patient variability in CPA clearance was 54.5%. Patients carrying CYP3A5*3 or *6 alleles had lower elimination rate constant and longer half-life compared to wild type carriers. CYP2C9 *2 or *3 carriers were associated with increased clearance of CPA. Patients who received 500 mg/m² based CPA regimen were associated with a 32.3% lower than average clearance and 37.1% lower than average V_D compared to patients who received 600 mg/m². A 0.1 m² unit increase in body surface area (BSA) was associated with a 5.6% increment in V_D. The mean V_D (33.5 L) in underweight group (BMI < 18.5 kg/m²) was significantly lower compared to those of overweight (48.1 L) or obese patients (51.9 L) (p < 0.001). AUC of CPA was positively correlated with neutropenic toxicity. In conclusion, we report large between-patient variability in clearance of CPA. CYP3A5 and CYP2C9 genotypes, BSA, BMI, and CPA dosage regimen influence PK of CPA. Plasma CPA exposure positively predicts chemotherapy-associated neutropenic toxicity.

Exposure-Toxicity Association of Cyclophosphamide and Its Metabolites in Infants and Young Children with Primary Brain Tumors: Implications for Dosing

PURPOSE

To characterize the population pharmacokinetics of cyclophosphamide, active 4-hydroxy-cyclophosphamide (4OH-CTX), and inactive carboxyethylphosphoramide mustard (CEPM), and their associations with hematologic toxicities in infants and young children with brain tumors. To use this information to provide cyclophosphamide dosing recommendations in this population.

PATIENTS AND METHODS

Patients received four cycles of a 1-hour infusion of 1.5 g/m² cyclophosphamide. Serial samples were collected to measure cyclophosphamide, 4OH-CTX, and CEPM plasma concentrations. Population pharmacokinetic modeling was performed to identify the patient characteristics influencing drug disposition. Associations between drug exposures and metrics reflecting drug-induced neutropenia, erythropenia, and thrombocytopenia were investigated. A Bayesian approach was developed to predict 4OH-CTX exposure using only cyclophosphamide and CEPM plasma concentrations.

RESULTS

Data from 171 patients (0.07-4.9 years) were adequately fitted by a two-compartment (cyclophosphamide) and one-compartment model (metabolites). Young infants (<6 months) exhibited higher mean 4OH-CTX exposure than did young children (138.4 vs. 107.2 μmol/L·h, P < 0.0001). No genotypes exhibited clinically significant influence on drug exposures. Worse toxicity metrics were significantly associated with higher 4OH-CTX exposures. Dosing simulations suggested decreased cyclophosphamide dosage to 1.2 g/m² for young infants versus 1.5 g/m² for children to attain similar 4OH-CTX exposure. Bayesian-modeled 4OH-CTX exposure predictions were precise (mean absolute prediction error 14.8% ± 4.2%) and had low bias (mean prediction error 4.9% ± 5.1%).

CONCLUSIONS

A 4OH-CTX exposure-toxicity association was established, and a decreased cyclophosphamide dosage for young infants was suggested to reduce toxicity in this population. Bayesian modeling to predict 4OH-CTX exposure may reduce clinical processing-related costs and provide insights into further exposure-response associations.

Phenobarbital, Midazolam Pharmacokinetics, Effectiveness, and Drug-Drug Interaction in Asphyxiated Neonates Undergoing Therapeutic Hypothermia

BACKGROUND

Phenobarbital and midazolam are commonly used drugs in (near-)term neonates treated with therapeutic hypothermia for hypoxic-ischaemic encephalopathy, for sedation, and/or as anti-epileptic drug. Phenobarbital is an inducer of cytochrome P450 (CYP) 3A, while midazolam is a CYP3A substrate. Therefore, co-treatment with phenobarbital might impact midazolam clearance.

OBJECTIVES

To assess pharmacokinetics and clinical anti-epileptic effectiveness of phenobarbital and midazolam in asphyxiated neonates and to develop dosing guidelines.

METHODS

Data were collected in the prospective multicentre PharmaCool study. In the present study, neonates treated with therapeutic hypothermia and receiving midazolam and/or phenobarbital were included. Plasma concentrations of phenobarbital and midazolam including its metabolites were determined in blood samples drawn on days 2-5 after birth. Pharmacokinetic analyses were performed using non-linear mixed effects modelling; clinical effectiveness was defined as no use of additional anti-epileptic drugs.

RESULTS

Data were available from 113 (phenobarbital) and 118 (midazolam) neonates; 68 were treated with both medications. Only clearance of 1-hydroxy midazolam was influenced by hypothermia. Phenobarbital co-administration increased midazolam clearance by a factor 2.3 (95% CI 1.9-2.9, p < 0.05). Anticonvulsant effectiveness was 65.5% for phenobarbital and 37.1% for add-on midazolam.

CONCLUSIONS

Therapeutic hypothermia does not influence clearance of phenobarbital or midazolam in (near-)term neonates with hypoxic-ischaemic encephalopathy. A phenobarbital dose of 30 mg/kg is advised to reach therapeutic concentrations. Phenobarbital co-administration significantly increased midazolam clearance. Should phenobarbital be substituted by non-CYP3A inducers as first-line anticonvulsant, a 50% lower midazolam maintenance dose might be appropriate to avoid excessive exposure during the first days after birth.

Deep learning improves prediction of drug-drug and drug-food interactions

Drug interactions, including drug-drug interactions (DDIs) and drug-food constituent interactions (DFIs), can trigger unexpected pharmacological effects, including adverse drug events (ADEs), with causal mechanisms often unknown. Several computational methods have been developed to better understand drug interactions, especially for DDIs. However, these methods do not provide sufficient details beyond the chance of DDI occurrence, or require detailed drug information often unavailable for DDI prediction. Here, we report development of a computational framework DeepDDI that uses names of drug-drug or drug-food constituent pairs and their structural information as inputs to accurately generate 86 important DDI types as outputs of human-readable sentences. DeepDDI uses deep neural network with its optimized prediction performance and predicts 86 DDI types with a mean accuracy of 92.4% using the DrugBank gold standard DDI dataset covering 192,284 DDIs contributed by 191,878 drug pairs. DeepDDI is used to suggest potential causal mechanisms for the reported ADEs of 9,284 drug pairs, and also predict alternative drug candidates for 62,707 drug pairs having negative health effects. Furthermore, DeepDDI is applied to 3,288,157 drug-food constituent pairs (2,159 approved drugs and 1,523 well-characterized food constituents) to predict DFIs. The effects of 256 food constituents on pharmacological effects of interacting drugs and bioactivities of 149 food constituents are predicted. These results suggest that DeepDDI can provide important information on drug prescription and even dietary suggestions while taking certain drugs and also guidelines during drug development.

Cyclophosphamide pharmacokinetics and pharmacogenetics in children with B-cell non-Hodgkin's lymphoma

Introduction

Variation in cyclophosphamide pharmacokinetics and metabolism has been highlighted as a factor that may impact on clinical outcome in various tumour types. The current study in children with B-cell non-Hodgkin's lymphoma (NHL) was designed to corroborate previous findings in a large prospective study incorporating genotype for common polymorphisms known to influence cyclophosphamide pharmacology.

Methods

A total of 644 plasma samples collected over a 5 year period, from 49 B-cell NHL patients ≤18 years receiving cyclophosphamide (250 mg/m²), were used to characterise a population pharmacokinetic model. Polymorphisms in genes including CYP2B6 and CYP2C19 were analysed.

Results

A two-compartment model provided the best fit of the population analysis. The mean cyclophosphamide clearance value following dose 1 was significantly lower than following dose 5 (1.83 ± 1.07 versus 3.68 ± 1.43 L/h/m², respectively; mean ± standard deviation from empirical Bayes estimates; P < 0.001). The presence of at least one CYP2B6*6 variant allele was associated with a lower cyclophosphamide clearance following both dose 1 (1.54 ± 0.11 L/h/m² versus 2.20 ± 0.31 L/h/m², P = 0.033) and dose 5 (3.12 ± 0.17 L/h/m² versus 4.35 ± 0.37 L/h/m², P = 0.0028), as compared to homozygous wild-type patients. No pharmacokinetic parameters investigated were shown to have a significant influence on progression free survival.

Conclusion

The results do not support previous findings of a link between cyclophosphamide pharmacokinetics or metabolism and disease recurrence in childhood B-cell NHL. While CYP2B6 genotype was shown to influence pharmacokinetics, there was no clear impact on clinical outcome.

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The influence of cyclophosphamide clinical pharmacology on childhood cancer outcome has been investigated

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The presence of at least one CYP2B6*6 variant allele was associated with a lower rate of cyclophosphamide clearance

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Pharmacokinetic parameters investigated were not shown to have a marked influence on clinical outcome

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Findings do not support a link between cyclophosphamide metabolism and disease recurrence in B-cell non-Hodgkin's lymphoma

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.

Characterization of the time course of carbamazepine deinduction by an enzyme turnover model

BACKGROUND AND OBJECTIVE

Carbamazepine is a potent inducer of drug metabolizing enzymes, which results in a number of clinically significant drug-drug interactions. Deinduction occurs when long-term carbamazepine therapy is discontinued. The goal of this study was to develop a population pharmacokinetic model to describe the time course of carbamazepine deinduction.

PATIENTS AND METHODS

Stable-labelled carbamazepine was administered intravenously on three occasions during the deinduction period to 15 patients with epilepsy for whom carbamazepine therapy was being discontinued. Data were analysed using a nonlinear mixed-effects model (NONMEM). An enzyme turnover model consisting of a one-compartment model linked with a hypothetical enzyme compartment was applied to characterize the time course of carbamazepine deinduction. Model evaluation was performed using the bootstrap approach and a visual predictive check.

RESULTS

In the final model, the deinduction process was accomplished by decreasing the rate of enzyme synthesis, resulting in a decrease in the relative amount of enzymes. The estimated rate constant for enzyme degradation was 0.00805 h-1, corresponding to a half-life of the combined enzymes of 86.1 hours (3.6 days).

CONCLUSION

An enzyme turnover model adequately characterized the experimental data. Based on the predicted enzyme half-life from the final model, the deinduction process should be completed within 2 weeks after carbamazepine therapy is terminated.

Population pharmacokinetics of cyclophosphamide and metabolites in children with neuroblastoma: a report from the Children's Oncology Group

Cyclophosphamide-based regimens are front-line treatment for numerous pediatric malignancies; however, current dosing methods result in considerable interpatient variability in tumor response and toxicity. In this pediatric population, the authors' objectives were (1) to quantify and explain the pharmacokinetic variability of cyclophosphamide and 2 of its metabolites, hydroxycyclophosphamide (HCY) and carboxyethylphosphoramide mustard (CEPM), and (2) to apply a population pharmacokinetic model to describe the disposition of cyclophosphamide and these metabolites. A total of 196 blood samples were obtained from 22 children with neuroblastoma receiving intravenous cyclophosphamide (400 mg/m2/d) and topotecan. Blood samples were quantitated for concentrations of cyclophosphamide, HCY, and CEPM using liquid chromatography-mass spectrometry and analyzed using nonlinear mixed-effects modeling with the NONMEM software system. After model building was complete, the area under the concentration-time curve (AUC) was computed using NONMEM. Cyclophosphamide elimination was described by noninducible and inducible routes, with the latter producing HCY. Glomerular filtration rate was a covariate for the fractional elimination of HCY and its conversion to CEPM. Considerable interpatient variability was observed in the AUC of cyclophosphamide, HCY, and CEPM. These results represent a critical first step in developing pharmacokinetic-linked pharmacodynamic studies in children receiving cyclophosphamide to determine the clinical relevance of the pharmacokinetic variability in cyclophosphamide and its metabolites.

Influence of polymorphisms of drug metabolizing enzymes (CYP2B6, CYP2C9, CYP2C19, CYP3A4, CYP3A5, GSTA1, GSTP1, ALDH1A1 and ALDH3A1) on the pharmacokinetics of cyclophosphamide and 4-hydroxycyclophosphamide

PURPOSE

The anticancer agent, cyclophosphamide, is metabolized by cytochrome P450 (CYP), glutathione S-transferase (GST) and aldehyde dehydrogenase (ALDH) enzymes. Polymorphisms of these enzymes may affect the pharmacokinetics of cyclophosphamide and thereby its toxicity and efficacy. The purpose of this study was to evaluate the effects of known allelic variants in the CYP2B6, CYP2C9, CYP2C19, CYP3A4, CYP3A5, GSTA1, GSTP1, ALDH1A1 and ALDH3A1 genes on the pharmacokinetics of the anticancer agent, cyclophosphamide, and its active metabolite 4-hydroxycyclophosphamide.

EXPERIMENTAL DESIGN

A cohort of 124 Caucasian patients received a high-dose chemotherapy combination consisting of cyclophosphamide (4-6 g/m2), thiotepa (320-480 mg/m2) and carboplatin (area under the curve 13-20 mg x min/ml) as intravenous infusions over 4 consecutive days. Genomic DNA was analysed using PCR and sequencing. Liquid chromatography-tandem mass spectrometry was used to measure plasma concentrations of cyclophosphamide and 4-hydroxycyclophosphamide. The relationship between allelic variants and the elimination pharmacokinetic parameters noninducible cyclophosphamide clearance (CL(nonind)), inducible cyclophosphamide clearance (CL(ind)) and elimination rate constant of 4-hydroxycyclophosphamide (k(4OHCP)) were evaluated using nonlinear mixed effects modelling.

RESULTS

The interindividual variability in the noninducible cyclophosphamide clearance, inducible cyclophosphamide clearance and 4-hydroxycyclophosphamide clearance was 23, 27 and 31%, respectively. No effect of the allelic variants investigated on the clearance of cyclophosphamide or 4-hydroxycyclophosphamide could be demonstrated.

CONCLUSION

This study indicates that the presently evaluated variant alleles in the CYP2B6, CYP2C9, CYP2C19, CYP3A4, CYP3A5, GSTA1, GSTP1, ALDH1A1 and ALDH3A1 genes do not explain the interindividual variability in cyclophosphamide and 4-hydroxycyclophosphamide pharmacokinetics and are, probably, not the cause of the observed variability in toxicity.

Cancer chemotherapy II: atypical hepatic injuries

Although chemotherapy generally is accompanied by regular testing for liver enzyme abnormalities, atypical reactions may occur that escape ordinary detection, because hepatocyte injury is not the primary event. The presence of fatty liver, mitochondrial changes, and even biliary abnormalities can be associated with normal or nearly normal liver enzyme levels. This article discusses unique aspects of liver damage associated with cancer chemotherapy. These unique reactions merit special attention and a special vigilance from clinicians.

Population pharmacokinetic/pharmacodynamic (PK/PD) modelling of the hypothalamic-pituitary-gonadal axis following treatment with GnRH analogues

AIMS

To develop a population pharmacokinetic/pharmacodynamic (PK/PD) model of the hypothalamic-pituitary-gonadal (HPG) axis describing the changes in luteinizing hormone (LH) and testosterone concentrations following treatment with the gonadotropin-releasing hormone (GnRH) agonist triptorelin and the GnRH receptor blocker degarelix.

METHODS

Fifty-eight healthy subjects received single subcutaneous or intramuscular injections of 3.75 mg of triptorelin and 170 prostate cancer patients received multiple subcutaneous doses of degarelix of between 120 and 320 mg. All subjects were pooled for the population PK/PD data analysis. A systematic population PK/PD model-building framework using stochastic differential equations was applied to the data to identify nonlinear dynamic dependencies and to deconvolve the functional feedback interactions of the HPG axis.

RESULTS

In our final PK/PD model of the HPG axis, the half-life of LH was estimated to be 1.3 h and that of testosterone 7.69 h, which corresponds well with literature values. The estimated potency of LH with respect to testosterone secretion was 5.18 IU l(-1), with a maximal stimulation of 77.5 times basal testosterone production. The estimated maximal triptorelin stimulation of the basal LH pool release was 1330 times above basal concentrations, with a potency of 0.047 ng ml(-1). The LH pool release was decreased by a maximum of 94.2% by degarelix with an estimated potency of 1.49 ng ml(-1).

CONCLUSIONS

Our model of the HPG axis was able to account for the different dynamic responses observed after administration of both GnRH agonists and GnRH receptor blockers, suggesting that the model adequately characterizes the underlying physiology of the endocrine system.

Population pharmacokinetics of lopinavir in combination with ritonavir in HIV-1-infected patients

AIMS

To develop a population pharmacokinetic model for lopinavir in combination with ritonavir, in which the interaction between both drugs was characterized, and in which relationships between patient characteristics and pharmacokinetics were identified.

METHODS

The pharmacokinetics of lopinavir in combination with ritonavir were described using NONMEM (version V, level 1.1). First, ritonavir data were fitted to a previously developed model to obtain individual Bayesian estimates of pharmacokinetic parameters. Hereafter, an integrated model for the description of the pharmacokinetics of lopinavir with ritonavir was designed.

RESULTS

From 122 outpatients 748 lopinavir and 748 ritonavir plasma concentrations were available for analysis. The interaction between the drugs was described by a time-independent inverse relationship between the exposure to ritonavir over a dosing-interval and the apparent clearance (CL/F) of lopinavir. The model parameters volume of distribution and absorption rate constant were 61.6 l (95% prediction interval (PI) 22.4, 83.7) and 0.564 h(-1) (95% PI 0.208, 0.947), respectively. The model yielded a theoretical value for the CL/F of lopinavir without ritonavir of 14.8 l h(-1) (95%PI 12.1, 20.1), which translates to a value of 5.73 l h(-1) in the presence of ritonavir. The only factor with significant effect on the pharmacokinetics was concurrent use of non-nucleoside reverse transcriptase inhibitors (NNRTI), which increased the CL/F of lopinavir by 39% (P < 0.001).

CONCLUSIONS

We have developed a model that has defined a time-independent inverse relationship between the exposure to ritonavir and the CL/F of lopinavir, and provided an adequate description of the pharmacokinetic parameters for the latter. Concomitant use of the NNRTIs efavirenz and nevirapine increased the CL/F of lopinavir.

Dealing with time-dependent pharmacokinetics during the early clinical development of a new leukotriene B4 synthesis inhibitor

PURPOSE

The aim of this study was to explore the possibility of achieving a practical dosing regimen for 2,4,6-triiodophenol (AM-24), a new leukotriene B4 (LTB4) synthesis inhibitor. First, a model capable of dealing with the nonlinearity in its pharmacokinetic profile was built, and then it was combined with a pharmacodynamic model previously established with data from earlier phase I trials.

METHODS

One week after the first 240-, 350-, or 500-mg oral dose of AM-24, six additional doses were given to 24 healthy volunteers once daily. A total of 33 blood samples were obtained from each individual. Different models, including enzyme turnover models, were fitted to the data by using the software NONMEM.

RESULTS

Drug absorption was modeled with a first-order process. Drug disposition was described with a one-compartment model, and elimination with an (auto)inhibited and a noninhibited clearance. AM-24 inhibited the enzyme production rate to a maximum of 98%. Relative bioavailability was independent of the decrease in the amount of enzyme. The estimate of the enzyme turnover half-life was 8.5 h.

CONCLUSIONS

Simulations have shown that steady-state conditions eliciting 90% of maximal LTB4 synthesis inhibition can be reached after 3 weeks during an oral treatment with AM-24 administered at the dosage of 500 mg once daily.

Population pharmacokinetics of cyclophosphamide and its metabolites 4-hydroxycyclophosphamide, 2-dechloroethylcyclophosphamide, and phosphoramide mustard in a high-dose combination with Thiotepa and Carboplatin

The anticancer prodrug cyclophosphamide (CP) is activated by the formation of 4-hydroxycyclophosphamide (4OHCP), which decomposes into phosphoramide mustard (PM). This activation pathway is inhibited by thiotepa. CP is inactivated by formation of 2-dechloroethylcyclophosphamide (2DCECP). The aim of this study was to develop a population pharmacokinetic model describing the complex pharmacokinetics of CP, 4OHCP, 2DCECP, and PM when CP is administered in a high-dose combination with thiotepa and carboplatin. Patients received a combination of CP (1000-1500 mg/m/d), carboplatin (265-400 mg/m/d), and thiotepa (80-120 mg/m/d) administered in short infusions over 4 days. Twenty blood samples were collected per patient per course. Concentrations of CP, 4OHCP, 2DCECP, PM, thiotepa, and tepa were determined in plasma. Using NONMEM, an integrated population pharmacokinetic model was used to describe the pharmacokinetics of CP, 4OHCP, 2DCECP, and PM, including the already described processes of autoinduction of CP and the interaction with thiotepa. Data were available on 35 patients (70 courses). The pharmacokinetics of CP were described with a 2-compartment model, and those of 4OHCP, 2DCECP, and PM with 1-compartment models. Before onset of autoinduction, it was assumed that CP is eliminated through a noninducible pathway accounting for 20% of total CP clearance, whereas 2 inducible pathways resulted in formation of 4OHCP (75%) and 2DCECP (5%). It was assumed that 4OHCP was fully converted to PM. Induction of CP metabolism was mediated by 2 hypothetical amounts of enzyme whose quantities increased in time in the presence of CP (kenz=0.0223 and 0.0198 hours). Induction resulted in an increased formation of 4OHCP (approximately 50%), PM (approximately 50%), and 2DCECP (approximately 35%) during the 4-day course, and concomitant decreased exposure to CP (approximately 50%). The formation of 2DCECP was not inhibited by thiotepa. Apparent volumes of distribution of CP, PM, and 2DCECP could be estimated being 43.7, 55.5, and 18.5 L, respectively. Exposure to metabolites varied up to 9-fold. The complex population pharmacokinetics of CP, 4OHCP, 2DCECP, and PM in combination with thiotepa and carboplatin has been established and may form the basis for further treatment optimization with this combination.

High exposures to bioactivated cyclophosphamide are related to the occurrence of veno-occlusive disease of the liver following high-dose chemotherapy

We investigated whether the occurrence of veno-occlusive disease of the liver (VOD) may be associated with individual variations in the pharmacokinetics of high-dose cyclophosphamide. Patients received single or multiple courses of cyclophosphamide (1000 or 1500 mg m-2 day-1), thiotepa (80 or 120 mg m-2 day-1) and carboplatin (265-400 mg m-2 day-1) (CTC) for 4 consecutive days. The area under the plasma concentration-time curves (AUCs) were calculated for cyclophosphamide and its activated metabolites 4-hydroxycyclophosphamide and phosphoramide mustard based on multiple blood samples. Possible relationships between the AUCs and the occurrence of VOD were studied. A total of 59 patients (115 courses) were included. Four patients experienced VOD after a second CTC course. The first-course AUC of 4-hydroxycyclophosphamide (P=0.003) but not of phosphoramide mustard (P=0.101) appeared to be predictive of the occurrence of VOD after multiple courses. High exposures to bioactivated cyclophosphamide may lead to increased organ toxicity.

Metabolism and transport of oxazaphosphorines and the clinical implications

The oxazaphosphorines including cyclophosphamide (CPA), ifosfamide (IFO), and trofosfamide represent an important group of therapeutic agents due to their substantial antitumor and immuno-modulating activity. CPA is widely used as an anticancer drug, an immunosuppressant, and for the mobilization of hematopoetic progenitor cells from the bone marrow into peripheral blood prior to bone marrow transplantation for aplastic anemia, leukemia, and other malignancies. New oxazaphosphorines derivatives have been developed in an attempt to improve selectivity and response with reduced toxicity. These derivatives include mafosfamide (NSC 345842), glufosfamide (D19575, beta-D-glucosylisophosphoramide mustard), NSC 612567 (aldophosphamide perhydrothiazine), and NSC 613060 (aldophosphamide thiazolidine). This review highlights the metabolism and transport of these oxazaphosphorines (mainly CPA and IFO, as these two oxazaphosphorine drugs are the most widely used alkylating agents) and the clinical implications. Both CPA and IFO are prodrugs that require activation by hepatic cytochrome P450 (CYP)-catalyzed 4-hydroxylation, yielding cytotoxic nitrogen mustards capable of reacting with DNA molecules to form crosslinks and lead to cell apoptosis and/or necrosis. Such prodrug activation can be enhanced within tumor cells by the CYP-based gene directed-enzyme prodrug therapy (GDEPT) approach. However, those newly synthesized oxazaphosphorine derivatives such as glufosfamide, NSC 612567 and NSC 613060, do not need hepatic activation. They are activated through other enzymatic and/or non-enzymatic pathways. For example, both NSC 612567 and NSC 613060 can be activated by plain phosphodiesterase (PDEs) in plasma and other tissues or by the high-affinity nuclear 3'-5' exonucleases associated with DNA polymerases, such as DNA polymerases and epsilon. The alternative CYP-catalyzed inactivation pathway by N-dechloroethylation generates the neurotoxic and nephrotoxic byproduct chloroacetaldehyde (CAA). Various aldehyde dehydrogenases (ALDHs) and glutathione S-transferases (GSTs) are involved in the detoxification of oxazaphosphorine metabolites. The metabolism of oxazaphosphorines is auto-inducible, with the activation of the orphan nuclear receptor pregnane X receptor (PXR) being the major mechanism. Oxazaphosphorine metabolism is affected by a number of factors associated with the drugs (e.g., dosage, route of administration, chirality, and drug combination) and patients (e.g., age, gender, renal and hepatic function). Several drug transporters, such as breast cancer resistance protein (BCRP), multidrug resistance associated proteins (MRP1, MRP2, and MRP4) are involved in the active uptake and efflux of parental oxazaphosphorines, their cytotoxic mustards and conjugates in hepatocytes and tumor cells. Oxazaphosphorine metabolism and transport have a major impact on pharmacokinetic variability, pharmacokinetic-pharmacodynamic relationship, toxicity, resistance, and drug interactions since the drug-metabolizing enzymes and drug transporters involved are key determinants of the pharmacokinetics and pharmacodynamics of oxazaphosphorines. A better understanding of the factors that affect the metabolism and transport of oxazaphosphorines is important for their optional use in cancer chemotherapy.

Clinical pharmacokinetics of cyclophosphamide

Cyclophosphamide is an extensively used anticancer and immunosuppressive agent. It is a prodrug undergoing a complicated process of metabolic activation and inactivation. Technical difficulties in the accurate determination of the cyclophosphamide metabolites have long hampered the assessment of the clinical pharmacology of this drug. As these techniques are becoming increasingly available, adequate description of the pharmacokinetics of cyclophosphamide and its metabolites has become possible. There is incomplete understanding on the role of cyclophosphamide metabolites in the efficacy and toxicity of cyclophosphamide therapy. However, relationships between toxicity (cardiotoxicity, veno-occlusive disease) and exposure to cyclophosphamide and its metabolites have been established. Variations in the balance between metabolic activation and inactivation of cyclophosphamide owing to autoinduction, dose escalation, drug-drug interactions and individual differences have been reported, suggesting possibilities for optimisation of cyclophosphamide therapy. Knowledge of the pharmacokinetics of cyclophosphamide, and possibly monitoring the pharmacokinetics of cyclophosphamide in individuals, may be useful for improving its therapeutic index.

A Toxicologist's Guide to the Preclinical Assessment of Hepatic Microsomal Enzyme Induction

The assessment of hepatic microsomal enzyme induction at the completion of preclinical toxicology studies in rodents and large mammals provides a wealth of information to the toxicologist and pharmacokineticist regarding how the drug-metabolizing system of the hepatocyte endoplasmic reticulum responded to high-dose levels of a xenobiotic designed for a specific pharmacological target in any of several target organs. The interpretation of these data can be greatly enhanced by a clear understanding of how this system functions and what the immediate and long-term ramifications are to organs and organ systems. This review focuses on how drugs modify the hepatic cytochrome P450 system, how those modifications are detected, the various consequences of these modifications, and some differences in the induction response among species.

Integrated Population Pharmacokinetic Model of both cyclophosphamide and thiotepa suggesting a mutual drug-drug interaction

PURPOSE/AIMS

Cyclophosphamide (CP) and thiotepa (TT) are frequently administered simultaneously in high-dose chemotherapy regimens. The prodrug CP shows strong autoinduction resulting in increased formation of its activated metabolite 4-hydroxycyclophosphamide (4OHCP). TT inhibits this bioactivation of CP. Previously, we successfully modelled CP bioactivation and the effect of TT on the autoinduction. Recently we suggested that CP may also induce the conversion of TT in to its metabolite tepa (T). The aim of the current study was to investigate whether the influence of CP on TT metabolism can be described with a population pharmacokinetic model and whether this interaction can be incorporated in an integrated model describing both CP and TT pharmacokinetics.

METHODS

Plasma samples were collected from 49 patients receiving 86 courses of a combination of high-dose CP (4000 or 6000 mg/m2), TT (320 or 480 mg/m2) and carboplatin (1067 or 1600 mg/m2) given in short infusions during four consecutive days. For each patient, approximately 20 plasma samples were available per course. Concentrations of CP, 4OHCP, TT and T were determined using GC and HPLC. Kinetic data were processed using NONMEM.

RESULTS

The pharmacokinetics of TT and T were described with a two-compartment model. TT was eliminated through a non-inducible and an inducible pathway, the latter resulting information of T (ClindTT = 12.4 l/hr, ClnonindTT = 17.0 l/hr). Induction of TT metabolism was mediated by a hypothetical amount of enzyme, different from that involved in CP induction, whose amount increased with time in the presence of CP. The amount of enzyme followed a zero-order formation and a decrease with a first-order elimination rate constant of 0.0343 hr(-1) (t1/2 = 20 hr). This model was significantly better than a model lacking the induction by CP. The model was successfully incorporated into the previously published pharmacokinetic model for CP, and resulted in comparable parameter estimates for this compound and its metabolite 4OHCP.

CONCLUSION

The pharmacokinetics of TT, when administered in combination with CP, were successfully described. The model confirms induction of TT metabolism with time and it appears likely that CP is responsible for this phenomenon. The existence of a mutual pharmacokinetic interaction between CP and TT, as described in our integrated model, may be relevant in clinical practice.

Drug interactions in oncology

Drug interactions are an ongoing concern in treatment of cancer, especially when cytotoxic drugs are being used. However, the clinical relevance of these interactions is not always investigated. Drug interactions can be pharmaceutical, pharmacokinetic, or pharmacodynamic. They can also be wanted (eg, use of ciclosporin to enhance the oral bioavailability of paclitaxel); unwanted (eg, combination of the antiviral agent sorivudine and oral fluorouracil analogues can lead to fatal complications); between cytotoxic drugs, cytotoxic drugs and non-cytotoxic drugs; or with pharmaceutical vehicles. Potential interactions between anticancer drugs and over-the-counter or alternative medicines and herbs should not be underestimated. More attention should be given to the recognition of potential drug interactions in the preclinical and early clinical development phase of a new anticancer drug. Here, we provide a comprehensive overview of drug interactions, with selected examples.

Pharmacokinetic-pharmacodynamic guided trial design in oncology

The application of pharmacokinetic (PK) and pharmacodynamic (PD) modeling in drug development has emerged during the past decades and it is has been suggested that the investigation of PK-PD relationships during drug development may facilitate and optimize the design of subsequent clinical development. Especially in oncology, well designed PK-PD modeling could be extremely useful as anticancer agents usually have a very narrow therapeutic index. This paper describes the application of the current insights in the use of PK-PD modeling to the design of clinical trials in oncology. The application of PK-PD modeling in each separate stage of (pre)clinical drug development of anticancer agents is discussed. The implementation of this approach is illustrated with the clinical development of docetaxel.

Population pharmacokinetics of the novel anticancer agent E7070 during four phase I studies: model building and validation

PURPOSE

N-(3-Chloro-7-indolyl)-1,4-benzenedisulfonamide (E7070) is a novel sulfonamide anticancer agent currently in phase II clinical development for the treatment of solid tumors. Four phase I studies have been finalized, with E7070 administered at four different treatment schedules to identify the maximum-tolerated dose and the dose-limiting toxicities. Pharmacokinetic analyses of all studies revealed E7070 to have nonlinear pharmacokinetics. A population pharmacokinetic model was designed and validated to describe the pharmacokinetics of E7070 at all four treatment schedules and to identify the possible influences of patient characteristics on the pharmacokinetic parameters.

PATIENTS AND METHODS

Plasma concentration-time data of all patients (n = 143) were fitted to several pharmacokinetic models using NONMEM. Seventeen covariables were investigated for their relation with individual pharmacokinetic parameters. A bootstrap procedure was performed to check the validity of the model.

RESULTS

The data were best described using a three-compartment model with nonlinear distribution to a peripheral compartment and two parallel pathways of elimination from the central compartment: a linear and a saturable pathway. Body-surface area (BSA) was significantly correlated to both the volume of distribution of the central compartment and to the maximal elimination capacity. The fits of 500 bootstrap replicates of the data set demonstrated the robustness of the developed population pharmacokinetic model.

CONCLUSION

A population pharmacokinetic model has been designed and validated that accurately describes the data of four phase I studies with E7070. Furthermore, it has been demonstrated that BSA-guided dosing for E7070 is important.

Relationship between exposure and toxicity in high-dose chemotherapy with cyclophosphamide, thiotepa and carboplatin

BACKGROUND

High-dose chemotherapy in combination with peripheral blood progenitor cell transplantation is widely used in the treatment of several malignancies. The use of high-dose chemotherapy can be complicated by the occurrence of severe and sometimes life threatening toxicity. A wide interpatient variability in toxicity is encountered, which may be caused by variability in the pharmacokinetics of the agents. The aim of this study was to establish the pharmacokinetics of cyclophosphamide, thiotepa, carboplatin and all relevant metabolites in a widely used high-dose combination and to study possible relationships between the pharmacokinetics and toxicity.

PATIENTS AND METHODS

Blood samples were collected from patients treated with modifications of the CTCb regimen consisting of cyclophosphamide (1000-1500 mg/m2/day), carboplatin (265-400 mg/m2/day) and thiotepa (80-120 mg/m2/day) as short infusions for four consecutive days. Thiotepa and its main metabolite tepa, ultrafilterable carboplatin, cyclophosphamide and its activated metabolites 4-hydroxycyclophosphamide and phosphoramide mustard were determined. Pharmacokinetics were assessed with the use of population pharmacokinetic analyses. Relationship between the area under the concentration-time curves (AUCs) of these compounds and toxicity were tested.

RESULTS

A total of 46 patients (83 courses of chemotherapy) was included. Relationships were identified between elevation of transaminases and the thiotepa and tepa AUC, mucositis and the tepa AUC and ototoxicity and the carboplatin AUC. A strong trend between the 4-hydroxycyclophosphamide AUC and veno-occlusive disease was found.

CONCLUSIONS

The complex pharmacokinetics of the different agents and their metabolites have been established and several relationships between the pharmacokinetics and toxicity were identified. These findings may form the basis for further treatment optimisation and dose-individualisation in this high-dose chemotherapy combination.