Pharmacoepidemiologic investigation of clonazepam relative clearance by mixed-effect modeling using routine clinical pharmacokinetic data in Japanese patients

Population-Based Assessments of Clinical Drug-Drug Interactions: Qualitative Indices or Quantitative Measures?

Population-based assessments of drug-drug interactions have become more common since the introduction and acceptance of the population pharmacokinetic approach. Unlike traditional methods, population-based studies provide clinically relevant results that can be applied directly to a target patient population. Furthermore, population-based studies do not demand the traditional requirements of intensive pharmacokinetic sampling, rigorous inpatient stays, or stringent assessment schedules. As such, the population-based approach can effectively be used to confirm known drug-drug interactions and further characterize anticipated interactions. A prospectively designed analysis can also reveal drug-drug interactions that might otherwise have gone undetected with traditional methods. Ultimately, these results could help to alleviate clinicians' concerns about using widely marketed drugs in combination therapies and also reduce patients' risk of experiencing unacceptable side effects. This article intends to provide a balanced overview of the population-based approach and its merits, drawbacks, and potential utility in the assessment of drug-drug interactions during clinical drug development.

[Therapeutic drug monitoring of clonazepam]

Clonazepam is a 1-4 benzodiazepine mainly used to treat epilepsy and epileptiform convulsion state. Rapidly absorbed after oral administration, it is widely distributed in the organism and is extensively converted in metabolites, poorly or not active, eliminated mainly in urine (70%) and feces. Elimination half-life is long, around 40 h. In adult and child, several studies showed a concentration-effect relation. Meanwhile, a large inter-individual variability in the dose-concentration relation was observed. A 15-50 microg/L range of clonazepam blood concentrations appears to be retained as an acceptable target to control a majority of epileptic seizures. The Therapeutic Drug Monitoring (TDM) of clonazepam can be considered as possibly useful in case of association with CYP450 inducers or inhibitors, suspicion of poor observance, or toxicity signs.

Population clinical pharmacology of children: modelling covariate effects

INTRODUCTION

Population modelling using mixed effects models provides a means to study variability in paediatric drug responses among individuals representative of those in whom the drug will be used clinically.

DISCUSSIONS

Explanatory covariates explain the predictable part of the between-individual variability. Growth and development are two major aspects of children not seen in adults. These aspects can be investigated by using size and age as covariates. Problems attributable to co-linearity can be approached by using size as the first covariate. Size standardisation is achieved using allometric scaling, a mechanistic approach that has a strong theoretical and empirical basis. Age is used to describe the maturation of clearance. The quantitative models (linear, exponential, first-order, variable slope sigmoidal) used to describe this maturation process vary depending on the span of the ages under investigation. Measures of response are not always straightforward and can be more difficult to quantify in children.

CONCLUSION

Covariate investigation in children is improving the understanding of developmental aspects of drug disposition and effects in the paediatric population, ultimately leading to more effective use of medications.

Population pharmacokinetic studies in pediatrics: issues in design and analysis

The current review addresses the following 3 frequently encountered challenges in the design and analysis of population pharmacokinetic studies in pediatrics: (1) body size adjustments during the development of pharmacostatistical models, (2) design and validation of limited sampling strategies, and (3) the integration of historical priors in data analysis and trial simulation. Size adjustments with empiric approaches based on body weight or body surface area have frequently proven as a pragmatic tool to overcome large size differences in a pediatric study population. Allometric size adjustments, however, provide a more mechanistic, physiologically based approach that, if used a priori, allows delineation of the effect of size from that of other covariates that show a high degree of collinearity. The frequent lack of dense data sets in pediatric clinical pharmacology because of ethical and logistic constraints in study design can be overcome with the application of D-optimality-based limited sampling schemes in combination with Bayesian and nonlinear mixed-effects modeling approaches. Empirically based dose selection and clinical trial designs for pediatric clinical pharmacology studies can be improved by applying clinical trial simulation techniques, especially if they integrate adult and pediatric in vitro and/or in vivo data as historic priors. Although integration of these concepts and techniques in population pharmacokinetic analyses is not only limited to pediatric research, their application allows researchers to overcome some major hurdles frequently encountered in pharmacokinetic studies in pediatrics and, thus, provides the basis for additional clinical pharmacology research in this previously insufficiently studied fraction of the general population.

Pharmacoepidemiologic investigation of a clonazepam-valproic acid interaction by mixed effect modeling using routine clinical pharmacokinetic data in Japanese patients

Non-linear Mixed Effects Modeling (NONMEM) was used to estimate the effects of clonazepam-valproic acid interaction on clearance values using 576 serum levels collected from 317 pediatric and adult epileptic patients (age range, 0.3-32.6 years) during their clinical routine care. Patients received the administration of clonazepam and/or valproic acid. The final model describing clonazepam clearance was CL = 144.0 TBW-0.172 1.14VPA, where CL is total body clearance (mL/kg/h); TBW is total body weight (kg); VPA = 1 for concomitant administration of valproic acid and VPA = zero otherwise. The final model describing valproic acid clearance was CL (mL/kg/h) = 17.2 TBW-0.264 DOSE0.159 0.821CZP 0.896GEN, where DOSE is the daily dose of valproic acid (mg/kg/day); CZP = 1 for concomitant administration of clonazepam and CZP = zero otherwise; GEN = 1 for female and GEN = zero otherwise. Concomitant administration of clonazepam and valproic acid resulted in a 14% increase in clonazepam clearance, and a 17.9% decrease in valproic acid clearance.