Semi-mechanistic Population Pharmacokinetic Model Research Articles

A Semi-Mechanistic Population Pharmacokinetic Model of Noscapine in Healthy Subjects Considering Hepatic First-Pass Extraction and CYP2C9 Genotypes.

Noscapine is a commonly used cough suppressant, with ongoing research on its anti-inflammatory and anti-tumor properties. The drug has a pronounced pharmacokinetic variability. This evaluation aims to describe the pharmacokinetics of noscapine using a semi-mechanistic population pharmacokinetic model and to identify covariates that could explain inter-individual pharmacokinetic variability. Forty-eight healthy volunteers (30 men and 18 women, mean age 33 years) were enrolled in a randomized, two-period, two-stage, crossover bioequivalence study of noscapine in two different liquid formulations. Noscapine plasma concentrations following oral administration of noscapine 50 mg were evaluated by a non-compartmental analysis and by a population pharmacokinetic model separately. Compared to the reference formulation, the test formulation exhibited ratios (with 94.12% confidence intervals) of 0.784 (0.662-0.929) and 0.827 (0.762-0.925) for peak plasma concentrations and area under the plasma concentration-time curve, respectively. Significant differences in p values (<0.01) were both observed when comparing peak plasma concentrations and area under the plasma concentration-time curve between CYP2C9 genotype-predicted phenotypes. A three-compartmental model with zero-order absorption and first-order elimination process best described the plasma data. The introduction of a liver compartment was able to describe the profound first-pass effect of noscapine. Total body weight and the CYP2C9 genotype-predicted phenotype were both identified as significant covariates on apparent clearance, which was estimated as 958 ± 548 L/h for extensive metabolizers (CYP2C9*1/*1 and *1/*9), 531 ± 304 L/h for intermediate metabolizers with an activity score of 1.5 (CYP2C9*1/*2), and 343 ± 197 L/h for poor metabolizers and intermediate metabolizers with an activity score of 1.0 (CYP2C9*1/*3, *2/*3, and*3/*3). The current work is expected to facilitate the future pharmacokinetic/pharmacodynamic development of noscapine. This study was registered prior to starting at "Deutsches Register Klinischer Studien" under registration no. DRKS00017760.

Population Pharmacokinetic Analysis of Drug-Drug Interactions Between Perampanel and Carbamazepine Using Enzyme Induction Model in Epileptic Patients.

Perampanel (PER) is an oral antiepileptic drug and its concomitant use with carbamazepine (CBZ) leads to decreased PER concentrations. However, the magnitude of its influence may vary, depending on the dynamics of the enzyme induction properties of CBZ. This study aimed to develop a population pharmacokinetic (PPK) model considering the dynamics of enzyme induction and evaluate the effect of CBZ on PER pharmacokinetics. We retrospectively collected data on patient background, laboratory tests, and prescribed drugs from electronic medical records. We developed 2 PPK models incorporating the effect of CBZ-mediated enzyme induction to describe time-concentration profiles of PER using the following different approaches: (1) treating the concomitant use of CBZ as a categorical covariate (empirical PPK model) and (2) incorporating the time-course of changes in the amount of enzyme by CBZ-mediated induction (semimechanistic PPK model). The bias and precision of the predictions were investigated by calculating the mean error, mean absolute error, and root mean squared error. A total of 133 PER concentrations from 64 patients were available for PPK modelling. PPK analyses showed that the co-administration of CBZ increased the clearance of PER. Goodness-of-fit plots indicated a favorable description of the observed data and low bias. The mean error, mean absolute error, and root mean square error values based on the semimechanistic model were smaller than those obtained using the empirical PPK model for predicting PER concentrations in patients with CBZ. We developed 2 PPK models to describe PER pharmacokinetics based on different approaches, using electronic medical record data. Our PPK models support the use of PER in clinical practice.

Integrated multiple analytes and semi-mechanistic population pharmacokinetic model of tusamitamab ravtansine, a DM4 anti-CEACAM5 antibody-drug conjugate

Tusamitamab ravtansine (SAR408701) is an antibody-drug conjugate (ADC), combining a humanized monoclonal antibody (IgG1) targeting carcinoembryonic antigen-related cell adhesion molecule 5 (CEACAM5) and a potent cytotoxic maytansinoid derivative, DM4, inhibiting microtubule assembly. SAR408701 is currently in clinical development for the treatment of advanced solid tumors expressing CEACAM5. It is administered intravenously as a conjugated antibody with an average Drug Antibody Ratio (DAR) of 3.8. During SAR408701 clinical development, four entities were measured in plasma: conjugated antibody (SAR408701), naked antibody (NAB), DM4 and its methylated metabolite (MeDM4), both being active. Average DAR and proportions of individual DAR species were also assessed in a subset of patients. An integrated and semi-mechanistic population pharmacokinetic model describing the time-course of all entities in plasma and DAR measurements has been developed. All DAR moieties were assumed to share the same drug disposition parameters, excepted for clearance which differed for DAR0 (i.e. NAB entity). The conversion of higher DAR to lower DAR resulted in a DAR-dependent ADC deconjugation and was represented as an irreversible first-order process. Each conjugated antibody was assumed to contribute to DM4 formation. All data were fitted simultaneously and the model developed was successful in describing the pharmacokinetic profile of each entity. Such a structural model could be translated to other ADCs and gives insight of mechanistic processes governing ADC disposition. This framework will further be expanded to evaluate covariates impact on SAR408701 pharmacokinetics and its derivatives, and thus can help identifying sources of pharmacokinetic variability and potential efficacy and safety pharmacokinetic drivers.

Effect of autoinduction and food on the pharmacokinetics of furmonertinib and its active metabolite characterized by a population pharmacokinetic model.

Furmonertinib (AST2818) is a novel third-generation irreversible EGFR TKI and recently has been approved in China for the treatment of non-small cell lung cancer (NSCLC) with EGFR-sensitizing and T790M resistance mutations. In the current study, we developed a semi-mechanistic population pharmacokinetic model to characterize the nonstationary pharmacokinetics (PK) of the furmonertinib and its active metabolite AST5902 simultaneously. The PK data of furmonertinib and AST5902 were obtained from 38 NSCLC patients and 16 healthy volunteers receiving 20-240 mg furmonertinib in three clinical trials. A nonlinear mixed-effects modeling approach was used to describe the PK data. The absorption process of furmonertinib was described by a transit compartment model. The disposition of both furmonertinib and AST5902 was described by a two-compartment model. An indirect response model accounted for the autoinduction of furmonertinib metabolism mediated by CYP3A4. The model-based simulation suggested that furmonertinib clearance was increased in one cycle of treatment (orally once daily for 21 days) compared to baseline, ranging from 1.1 to 1.8 fold corresponding to the dose range of 20-240 mg. The concentration of furmonertinib was decreased over time whereas that of AST5902 was increased. Interestingly, the concentration of the total active compounds (furmonertinib and AST5902) appeared to be stable. The food intake, serum alkaline phosphatase and body weight were identified as statistically significant covariates. The mechanism of food effect on PK was investigated, where the food intake might increase the bioavailability of furmonertinib via increasing the splanchnic blood flow. Overall, a population PK model was successfully developed to characterize the nonstationary PK of furmonertinib and AST5902 simultaneously. The concentrations of total active compounds were less affected by the autoinduction of furmonertinib metabolism.

Population Pharmacokinetic Model of N-acetylmannosamine (ManNAc) and N-acetylneuraminic acid (Neu5Ac) in Subjects with GNE Myopathy.

BackgroundGNE myopathy is a rare genetic muscle disease resulting from deficiency in an enzyme critical for the biosynthesis of N-acetylneuraminic acid (Neu5Ac, sialic acid). The uncharged Neu5Ac precursor, N-acetylmannosamine (ManNAc), is under development as an orphan drug for treating GNE myopathy.MethodsA semi-mechanistic population pharmacokinetic model was developed to simultaneously characterize plasma ManNAc and its metabolite Neu5Ac following oral administration of ManNAc to subjects with GNE myopathy. Plasma ManNAc and Neu5Ac pharmacokinetic data were obtained from two clinical studies (ClinicalTrials.gov identifiers NCT01634750, NCT02346461) and were simultaneously modeled using NONMEM.ResultsManNAc and Neu5Ac plasma concentrations were obtained from 34 subjects with GNE myopathy (16 male, 18 female, median age 39.5 years). The model parameter estimates included oral absorption rate (ka) = 0.256 h−1, relative bioavailability relationship with dose (F-Dose) slope = −0.405 (where F = 1 for 6-g dose), apparent clearance (CLM/F) = 631 L/h, volume of distribution (VM/F) = 506 L, Neu5Ac elimination rate constant (kout) = 0.283 h−1, initial ManNAc to Neu5Ac conversion (SLP0) = 0.000619 (ng/mL)−1 and at steady-state (SLPSS) = 0.00334 (ng/mL)−1, with a rate-constant of increase (kinc) = 0.0287 h−1. Goodness-of-fit plots demonstrated an acceptable and unbiased fit to the plasma ManNAc and Neu5Ac concentration data. Visual predictive checks demonstrated reasonable agreement between the 5th, 50th, and 95th percentiles of the observed and simulated data.ConclusionsThis population pharmacokinetic model can be used to evaluate ManNAc dosing regimens and to calculate Neu5Ac production and exposure following oral administration of ManNAc in subjects with GNE myopathy.Supplementary InformationThe online version contains supplementary material available at 10.1007/s40268-021-00343-6.

Simultaneous Semi-Mechanistic Population Pharmacokinetic Modeling Analysis of Enalapril and Enalaprilat Serum and Urine Concentrations From Child Appropriate Orodispersible Minitablets.

Enalapril is recommended as the first line of therapy and is proven to improve survival rates for treatment of Pediatric Heart Failure; however, an approved drug and child appropriate dosage formulation is still absent. The present analysis was conducted to perform a detailed model informed population pharmacokinetic analysis of prodrug enalapril and its active metabolite enalaprilat in serum and urine. Further, a model informed dosage form population-pharmacokinetic analysis was conducted to evaluate differences in pharmacokinetics of enalapril and its active metabolite enalaprilat when prodrug was administered to 24 healthy adults in a crossover, two periods, two treatments, phase I clinical trial using child-appropriate orodispersible mini-tablets (ODMT) and reference (Renitec®) dosage formulation. A simultaneous semi-mechanistic population-pharmacokinetic model was developed using NONMEM software, which predicted full profile serum and urine concentrations of enalapril and enalaprilat. First-order conditional estimation with interaction was used for parameter estimation. Transit compartments added using Erlang distribution method to predicted enalapril absorption and enalaprilat formation phases. Normalized body weight was identified as covariate related to enalapril volume of distribution. Visual predictive check (VPC) plots and conducted bootstrap analysis validated the model. The data from the two formulations were pooled for population-pharmacokinetic analysis and covariate effect of the formulation was found on mean transit time (MTT1) of enalapril absorption. In addition, data of each formulation were modeled separately and the estimated parameters of each individual administered both formulations were correlated using paired samples Wilcoxon rank test (p < 0.05 = significant) which also showed only a significant difference (p = 0.03) in MTT1 i.e., 5 min early appearance of enalapril from ODMT compared to reference tablets. No difference in the pharmacokinetics of active enalaprilat was found from the ODMT compared to the reference formulation. The population pharmacokinetic analysis provided detailed information about the pharmacokinetics of enalapril and enalaprilat, which showed that the ODMT formulation might have similar pharmacodynamic response compared to the reference formulation.

Semimechanistic Population Pharmacokinetic Model to Predict the Drug-Drug Interaction Between S-ketamine and Ticlopidine in Healthy Human Volunteers.

Low‐dose oral S‐ketamine is increasingly used in chronic pain therapy, but extensive cytochrome P450 (CYP) mediated metabolism makes it prone to pharmacokinetic drug‐drug interactions (DDIs). In our study, concentration‐time data from five studies were used to develop a semimechanistic model that describes the ticlopidine‐mediated inhibition of S‐ketamine biotransformation. A mechanistic model was implemented to account for reversible and time‐dependent hepatic CYP2B6 inactivation by ticlopidine, which causes elevated S‐ketamine exposure in vivo. A pharmacokinetic model was developed with gut wall and hepatic clearances for S‐ketamine, its primary metabolite norketamine, and ticlopidine. Nonlinear mixed effects modeling approach was used (NONMEM version 7.3.0), and the final model was evaluated with visual predictive checks and the sampling‐importance‐resampling procedure. Our final model produces biologically plausible output and demonstrates that ticlopidine is a strong inhibitor of CYP2B6 mediated S‐ketamine metabolism. Simulations from our model may be used to evaluate chronic pain therapy with S‐ketamine.

Semi-Mechanistic Population Pharmacokinetic Modeling of L-Histidine Disposition and Brain Uptake in Wildtype and Pht1 Null Mice.

To develop a semi-mechanistic population pharmacokinetic (PK) model to quantitate the disposition kinetics of L-histidine, a peptide-histidine transporter 1 (PHT1) substrate, in the plasma, cerebrospinal fluid and brain parenchyma of wildtype (WT) and Pht1 knockout (KO) mice. L-[14C]Hisidine (L-His) was administrated to WT and KO mice via tail vein injection, after which plasma, cerebrospinal fluid (CSF) and brain parenchyma samples were collected. A PK model was developed using non-linear mixed effects modeling (NONMEM). The disposition of L-His between the plasma, brain, and CSF was described by a combination of PHT1-mediated uptake, CSF bulk flow and first-order micro-rate constants. The PK profile of L-His was best described by a four-compartment model. A more rapid uptake of L-His in brain parenchyma was observed in WT mice due to PHT1-mediated uptake, a process characterized by a Michaelis-Menten component (Vmax=0.051 nmoL/min and Km=34.94μM). A semi-mechanistic population PK model was successfully developed, for the first time, to quantitatively characterize the disposition kinetics of L-His in brain under in vivo conditions. This model may prove a useful tool in predicting the uptake of L-His, and possibly other PHT1 peptide/mimetic substrates, for drug delivery to the brain.

Predicting Cortisol Exposure from Paediatric Hydrocortisone Formulation Using a Semi-Mechanistic Pharmacokinetic Model Established in Healthy Adults

Optimisation of hydrocortisone replacement therapy in children is challenging as there is currently no licensed formulation and dose in Europe for children under 6 years of age. In addition, hydrocortisone has non-linear pharmacokinetics caused by saturable plasma protein binding. A paediatric hydrocortisone formulation, Infacort® oral hydrocortisone granules with taste masking, has therefore been developed. The objective of this study was to establish a population pharmacokinetic model based on studies in healthy adult volunteers to predict hydrocortisone exposure in paediatric patients with adrenal insufficiency. Cortisol and binding protein concentrations were evaluated in the absence and presence of dexamethasone in healthy volunteers (n=30). Dexamethasone was used to suppress endogenous cortisol concentrations prior to and after single doses of 0.5, 2, 5 and 10mg of Infacort® or 20 mg of Infacort®/hydrocortisone tablet/hydrocortisone intravenously. A plasma protein binding model was established using unbound and total cortisol concentrations, and sequentially integrated into the pharmacokinetic model. Both specific (non-linear) and non-specific (linear) protein binding were included in the cortisol binding model. A two-compartment disposition model with saturable absorption and constant endogenous cortisol baseline (Baseline cort,15.5nmol/L) described the data accurately. The predicted cortisol exposure for a given dose varied considerably within a small body weight range in individuals weighing <20kg. Our semi-mechanistic population pharmacokinetic model for hydrocortisone captures the complex pharmacokinetics of hydrocortisone in a simplified but comprehensive framework. The predicted cortisol exposure indicated the importance of defining an accurate hydrocortisone dose to mimic physiological concentrations for neonates and infants weighing <20 kg. EudraCT number: 2013-000260-28, 2013-000259-42.

Simultaneous Pharmacogenetics-Based Population Pharmacokinetic Analysis of Darunavir and Ritonavir in HIV-Infected Patients

Darunavir is a potent protease inhibitor of HIV. To enhance its pharmacokinetic profile, darunavir must be co-administered with ritonavir. There is wide inter-patient variability in darunavir pharmacokinetics among HIV-infected individuals, however. Darunavir is a known substrate for influx transporters, such as the 1A2 and the 1B1 members of the solute carrier organic anion transporter family (SLCO1A2, SLCO1B1), as well as for efflux transporters such as the multi-drug resistance protein 1 (MRP1). The aim of this study was to develop a semi-mechanistic population pharmacokinetic model for darunavir and ritonavir administered in HIV-infected adults. The desired model would incorporate patient characteristics and pharmacogenetic data contributing to variability in drug concentrations and also take into account the interaction between the two compounds. A population pharmacokinetic analysis was performed with 705 plasma samples from 75 Caucasian individuals receiving darunavir/ritonavir (600/100mg twice daily) for at least 4weeks. At least one full pharmacokinetic profile was obtained for each participant, and darunavir and ritonavir concentrations in plasma were determined by high performance liquid chromatography. Genotyping for 148 polymorphisms in genes coding for transporters or metabolizing enzymes was conducted by two methods: MALDI-TOF mass spectrometry and real-time polymerase chain reaction-based allelic discrimination. A population pharmacokinetic model was developed for darunavir and for ritonavir. The effect of single nucleotide polymorphisms on the post hoc individual pharmacokinetic parameters was first explored using graphic methods and regression analysis. Those covariates related to changes in darunavir or ritonavir pharmacokinetic parameters were then further evaluated using non-linear mixed effects modeling (NONMEM version VII). Darunavir and ritonavir pharmacokinetics were best described by a two- and one-compartment model, respectively, both with first-order absorption and elimination. The darunavir peripheral volume of distribution decreased as α1-acid glycoprotein concentrations increased. Darunavir clearance was 12% lower in patients with SLCO3A1 rs8027174 GT/TT genotypes, while homozygosity for the rs4294800 A allele was associated with 2.5-fold higher central volume of distribution. Body weight influenced ritonavir clearance. Ritonavir inhibited darunavir clearance following a maximum-effect model. A population pharmacokinetic model to simultaneously describe the pharmacokinetics of darunavir and ritonavir was developed in HIV-infected patients. The model provides better understanding of the interaction between darunavir and ritonavir and suggests an association between SLCO3A1 polymorphisms and darunavir pharmacokinetics. Bayesian estimates of individual darunavir parameters and ritonavir may be useful to predict darunavir exposure.

Semi-mechanistic Population Pharmacokinetic Model of Multivalent Trastuzumab Emtansine in Patients with Metastatic Breast Cancer

Trastuzumab emtansine (T-DM1) is an antibody-drug conjugate (ADC) composed of multiple molecules of the antimicrotubule agent DM1 linked to trastuzumab, a humanized anti-human epidermal growth factor receptor 2 (HER2) monoclonal antibody. Pharmacokinetics data from phase I (n = 52) and phase II (n = 111) studies in HER2-positive metastatic breast cancer patients show a shorter terminal half-life for T-DM1 than for total trastuzumab (TTmAb). In this work, we translated prior preclinical modeling in monkeys to develop a semi-mechanistic population pharmacokinetics model to characterize T-DM1 and TTmAb concentration profiles. A series of transit compartments with the same disposition parameters was used to describe the deconjugation process from higher to lower drug-to-antibody ratios (DARs). The structure could explain the shorter terminal half-life of T-DM1 relative to TTmab. The final model integrates prior knowledge of T-DM1 DARs from preclinical studies and could provide a platform for understanding and characterizing the pharmacokinetics of other ADC systems.

A Semi-mechanistic Gastric Emptying Model for the Population Pharmacokinetic Analysis of Orally Administered Acetaminophen in Critically Ill Patients

To develop a semi-mechanistic population pharmacokinetic model based on gastric emptying function for acetaminophen plasma concentration in critically ill patients tolerant and intolerant to enteral nutrition before and after prokinetic therapy. Acetaminophen plasma concentrations were available from a study with 10 tolerant and 20 intolerant patients before and after prokinetic therapy with either erythromycin or metoclopramide. Population pharmacokinetic modelling was carried out in a nonlinear mixed effects analysis software, NONMEM. A four-compartment semi-mechanistic model for stomach, intestine, central and peripheral compartments was described. The rate of emptying of the stomach was described by a first-order rate parameter. The final model has two gastric emptying rate constant parameters: kg1 (1.30 h(-1), RSE=53.84%, T1/2=0.53 h) for the intolerant group before prokinetic therapy and kg2 (27.8 h(-1), RSE=59.35%, T1/2=0.025 h) for both the intolerant group after prokinetic therapy and the tolerant group. Other parameters and estimates (RSE) in the model were ka=5.12 h(-1) (28.13%), CL=13.0 L/h (19.62%), CLD=22.6 L/h (19.78%), V1=63.8 L (12.79%) and V2=69 L (38.70%). The four-compartment semi-mechanistic population pharmacokinetic model adequately described the data. The gastric emptying half-time is improved by a factor of about 20 in the patients that are intolerant to enteral nutrition after treatment with prokinetic agents.

Desipramine, substrate for CYP2D6 activity: population pharmacokinetic model and design elements of drug–drug interaction trials

To develop a population pharmacokinetic model to describe the pharmacokinetics of desipramine in healthy subjects, after oral administration of a 50mg dose. Additional objectives were to develop a semi-mechanistic population pharmacokinetic model for desipramine, which allowed simulation of CYP2D6-mediated inhibition, when using desipramine as a probe substrate, and to evaluate certain study design elements, such as duration of desipramine pharmacokinetic sampling, required sample size and optimal pharmacokinetic sampling schedule for intermediate, extensive and ultrarapid metabolizers of CYP2D6 substrates. The mean population estimates of the first order absorption rate constant (k(a) ), apparent clearance (CL/F) and apparent volume of distribution at steady state (V(ss) /F) were 0.15h(-1) , 111 lh(-1) and 2950 l, respectively. Further, using the proposed semi-mechanistic hepatic intrinsic clearance model with Bayesian inference, mean population desipramine hepatic intrinsic clearance was estimated to be 262 lh(-1) with between-subject variability of 84%. d-optimal PK sampling times for intermediate metabolizers were calculated to be approximately 0.25, 24, 75 and 200h. Similar sampling times were found for ultrarapid and extensive metabolizers except that the second d-optimal sample was earlier at 14 and 19h, respectively, compared with 24h for intermediate metabolizers. This difference in sampling times between the three genotypes can be attributed to the different intrinsic clearances and elimination rates. A two compartment population pharmacokinetic model best described desipramine disposition. The semi-mechanistic population model developed is suitable to describe the pharmacokinetic behaviour of desipramine for the dose routinely used in drug-drug interaction (DDI) studies. Based on this meta-analysis of seven trials, a sample size of 21 subjects in cross-over design is appropriate for assessing CYP2D6 interaction with novel compounds.

Maraviroc modelling strategy: use of early phase 1 data to support a semi‐mechanistic population pharmacokinetic model

To model the basic pharmacokinetic (PK) characteristics of maraviroc to construct an integrated semi-mechanistic PK model for use in later population PK analyses. Three analyses were performed utilizing intravenous, oral and radiolabel data. Firstly, a PK disposition model was developed from data from 20 healthy males who received 3, 10 or 30 mg of intravenous maraviroc. Secondly, a sigmoid E(max)vs dose model of dose-normalized non-compartmental AUC from oral dosing in 134 healthy young males and females across five phase 1 studies was constructed. This described absorption dose non-linearities and tested for the influence of food, formulation and dose frequency on model parameters. The third analysis developed a mass balance model for both absorption and disposition of maraviroc with 300 mg solution and predicted the mass balance after administration of 100 mg tablet formulation. A four-compartment PK model best described the intravenous data and no influence of dose was found on clearance. Total clearance was 48 l h(-1) (2.2% SE). The main covariate effect in the non-compartmental analysis reproduced the dose-dependency of food through a five-fold increase in the ED(50) of the sigmoid E(max) model. The mass balance models calculated that 33.3% and 22.9% of 300 mg solution and 100 mg tablet doses, respectively, are systemically available, and first-pass metabolism extracts 62% of an absorbed dose, estimating a hepatic blood flow of 101 l h(-1). The analysis demonstrates a novel integration approach to build a maraviroc semi-mechanistic population PK model for further use in volunteers and patients.

Modeling the Autoinhibition of Clarithromycin Metabolism during Repeated Oral Administration

Clarithromycin decreases CYP3A4 activity and thus gradually inhibits its own metabolism as well as that of coadministered drugs. The aim of this study was to obtain an understanding of the time course of these changes. The plasma concentration-time profiles of clarithromycin and its active metabolite, 14(R)-hydroxy-clarithromycin, in 12 young healthy volunteers after oral administration of a clarithromycin suspension (500 mg twice a day [b.i.d.] for seven doses) were modeled by population pharmacokinetic analysis in the NONMEM program. The nonlinearity of clarithromycin metabolism was considered during model development, and the metabolite disposition kinetics were assumed to be linear. The absorption kinetics of clarithromycin were best described by a Weibull function model. The pharmacokinetics of clarithromycin and its 14(R)-hydroxyl metabolite were adequately described by a one-compartment model each for clarithromycin and its metabolite as well as an inhibition compartment that reflects the autoinhibition of clarithromycin metabolism. Up to 90% of the apparent total clarithromycin clearance (60 liters/h) was susceptible to reversible autoinhibition, depending on the concentration in the inhibition compartment. The proposed semimechanistic population pharmacokinetic model successfully described the autoinhibition of clarithromycin metabolism and may be used to adjust the doses of other drugs that are metabolized by CYP3A4 and that are coadministered with clarithromycin. Simulations showed that for the standard dose of 500 mg b.i.d., no further increase in the level of exposure occurs after approximately 48 h of treatment. For a 1,000-mg b.i.d. dose, the achievement of steady state is expected to take several days and to achieve a 3.6-fold higher level of clarithromycin exposure than the 500-mg b.i.d. dose. This evaluation provides a rationale for safer and more effective therapy with clarithromycin.

Population pharmacokinetics of orally administered paclitaxel formulated in Cremophor EL.

The vehicle Cremophor EL (CrEL) has been shown to impair the absorption of paclitaxel by micellar entrapment of the drug in the gastrointestinal tract. The goal of this study was to develop a semimechanistic population pharmacokinetic model to study the influence of CrEL on the oral absorption of paclitaxel. Paclitaxel plasma-concentration time profiles were available from 55 patients (M:F, 17 : 38; total 67 courses; 797 samples), receiving paclitaxel orally once or twice daily (dose range 60-360 mg m(-2)) together with 12-15 mg kg(-1) cyclosporin A. A population pharmacokinetic model was developed using the nonlinear mixed effect modelling program NONMEM. After absorption, paclitaxel pharmacokinetics were best described using a two-compartment model with linear distribution from the central compartment into a peripheral compartment and first-order elimination. Paclitaxel in the gastrointestinal tract was modelled as free fraction or bound to CrEL, with only the free fraction available for absorption into the central compartment. The equilibrium between free and bound paclitaxel was influenced by the concentration of CrEL present in the gastrointestinal tract. The concentration of CrEL in the gastrointestinal tract decreased with time with a first order rate constant of 1.73 h(-1). The bioavailability of paclitaxel was independent of the dose and of CrEL. Estimated apparent paclitaxel clearance and volume of distribution were 127 l h(-1) and 409 l, respectively. Large interpatient variability was observed. Covariate analysis did not reveal significant relationships with any of the pharmacokinetic parameters. A pharmacokinetic model was developed that described the pharmacokinetics of orally administered paclitaxel. CrEL strongly influenced paclitaxel absorption from the gastrointestinal tract resulting in time-dependent but no significant dose-dependent absorption over the examined dose range studied.