Prediction of drug disposition in infants and children by means of physiologically based pharmacokinetic (PBPK) modelling: theophylline and midazolam as model drugs

Whole-body physiologically based pharmacokinetic models

This review summarizes the most recent developments in and applications of physiologically based pharmacokinetic (PBPK) modeling methodology originating from both the pharmaceutical and environmental toxicology areas. It focuses on works published in the last 5 years, although older seminal papers have also been referenced. After a brief introduction to the field and several essential definitions, the main body of the text is structured to follow the major steps of a typical PBPK modeling exercise. Various applications of the methodology are briefly described. The major future trends and perspectives are outlined. The main conclusion from the review of the available literature is that PBPK modeling, despite its obvious potential and recent incremental developments, has not taken the place it deserves, especially in pharmaceutical and drug development sciences.

Developmental pharmacokinetics of ciclosporin--a population pharmacokinetic study in paediatric renal transplant candidates

AIMS

To use population pharmacokinetic modelling to characterize the influence of developmental and demographic factors on the pharmacokinetic variability of ciclosporin.

METHODS

Pharmacokinetic modelling was performed in NONMEM using a dataset comprising 162 pretransplant children, aged 0.36-17.5 years. Ciclosporin was given intravenously (3 mg kg(-1)) and orally (10 mg kg(-1)) on separate occasions followed by blood sampling for 24 h.

RESULTS

A three-compartment model with first-order absorption without lag-time best described the pharmacokinetics of ciclosporin. The most important covariate affecting systemic clearance (CL) and distribution volume (V) was body weight (BW; scaled allometrically), responsible for a fourfold difference in uncorrected ciclosporin CL and a sixfold difference in ciclosporin V. The other significant covariates, haematocrit, plasma cholesterol and creatinine, were estimated to explain 20-30% of interindividual differences in CL and V of ciclosporin. No age-related changes in oral bioavailability or in BW-normalized V were seen. The BW-normalized CL (CL/BW) declined with age and prepubertal children (<8 years) had an approximately 25% higher CL/BW than did older children. Normalization of CL for allometric BW (BW(3/4)) removed its relationship to age.

CONCLUSION

The relationship between CL and allometric BW is consistent with a gradual reduction in relative liver size, until adult values, and a relatively constant CYP3A4 content in the liver from about 6-12 months of age to adulthood. Ciclosporin oral bioavailability, known previously to display large interindividual variability, is not influenced by age. These findings can enable better individualization of ciclosporin dosing in infants, children and adolescents.

Lamotrigine in children and adolescents: the impact of age on its serum concentrations and on the extent of drug interactions

OBJECTIVE

To investigate the impact of age and co-treatment with other drugs on the serum concentrations of lamotrigine in children and adolescents.

METHODS

A review of routine serum concentration measurements of lamotrigine performed in our laboratory yielded a total of 744 serum samples from 296 subjects (110 males, 186 females, age: 2-19 years) suitable for statistical analysis. The primary outcome variable was the dose-corrected lamotrigine serum concentration, expressed as the lamotrigine concentration/dose (C/D) ratio. A linear mixed model that allowed multiple observations from the same patient was used to identify and quantify the effect of factors influencing the lamotrigine C/D ratio.

RESULTS

According to the model, the lamotrigine C/D ratio decreases by 6% per year of age. Valproate and levetiracetam were found to raise the lamotrigine C/D ratio, whereas the following co-medications reduced it: carbamazepine, clobazam, fluoxetine, clonazepam and ethinyl estradiol. The effect of carbamazepine decreased with increasing age. No gender difference was detected.

CONCLUSIONS

Age is an important factor with respect to the pharmacokinetics and the extent of drug interactions of lamotrigine in children and adolescents. In this population, older individuals will need higher doses than younger ones in order to achieve the same serum concentrations.

Development of a Physiology-Based Whole-Body Population Model for Assessing the Influence of Individual Variability on the Pharmacokinetics of Drugs

In clinical development stages, an a priori assessment of the sensitivity of the pharmacokinetic behavior with respect to physiological and anthropometric properties of human (sub-) populations is desirable. A physiology-based pharmacokinetic (PBPK) population model was developed that makes use of known distributions of physiological and anthropometric properties obtained from the literature for realistic populations. As input parameters, the simulation model requires race, gender, age, and two parameters out of body weight, height and body mass index. From this data, the parameters relevant for PBPK modeling such as organ volumes and blood flows are determined for each virtual individual. The resulting parameters were compared to those derived using a previously published model (P(3)M). Mean organ weights and blood flows were highly correlated between the two models, despite the different methods used to generate these parameters. The inter-individual variability differed greatly especially for organs with a log-normal weight distribution (such as fat and spleen). Two exemplary population pharmacokinetic simulations using ciprofloxacin and paclitaxel as model drugs showed good correlation to observed variability. A sensitivity analysis demonstrated that the physiological differences in the virtual individuals and intrinsic clearance variability were equally influential to the pharmacokinetic variability but were not additive. In conclusion, the new population model is well suited to assess the influence of individual physiological variability on the pharmacokinetics of drugs. It is expected that this new tool can be beneficially applied in the planning of clinical studies.

Guidelines on paediatric dosing on the basis of developmental physiology and pharmacokinetic considerations

The approach to paediatric drug dosing needs to be based on the physiological characteristics of the child and the pharmacokinetic parameters of the drug. This review summarises the current knowledge on developmental changes in absorption, distribution, metabolism and excretion and combines this knowledge with in vivo and in vitro pharmacokinetic data that are currently available. In addition, dosage adjustments based on practical problems, such as child-friendly formulations and feeding regimens, disease state, genetic make-up and environmental influences are presented. Modification of a dosage based on absorption, depends on the route of absorption, the physico chemical properties of the drug and the age of the child. For oral drug absorption, a distinction should be made between the very young and children over a few weeks old. In the latter case, it is likely that practical considerations, like appropriate formulations, have much greater relevance to oral drug absorption. The volume of distribution (V(d)) may be altered in children. Hydrophilic drugs with a high V(d) in adults should be normalised to bodyweight in young children (age <2 years), whereas hydrophilic drugs with a low V(d) in adults should be normalised to body surface area (BSA) in these children. For drugs that are metabolised by the liver, the effect of the V(d) becomes apparent in children <2 months of age. In general, only the first dose should be based on the V(d); subsequent doses should be determined by the clearance. Pharmacokinetic studies on renal and liver function clarify that a distinction should be made between maturation and growth of the organs. After the maturation process has finished, the main influences on the clearance of drugs are growth and changes in blood flow of the liver and kidney. Drugs that are primarily metabolised by the liver should be administered with extreme care until the age of 2 months. Modification of dosing should be based on response and on therapeutic drug monitoring. At the age of 2-6 months, a general guideline based on bodyweight may be used. After 6 months of age, BSA is a good marker as a basis for drug dosing. However, even at this age, drugs that are primarily metabolised by cytochrome P450 2D6 and uridine diphosphate glucuronosyltransferase should be normalised to bodyweight. In the first 2 years of life, the renal excretion rate should be determined by markers of renal function, such as serum creatinine and p-aminohippuric acid clearance. A dosage guideline for drugs that are significantly excreted by the kidney should be based on the determination of renal function in first 2 years of life. After maturation, the dose should be normalised to BSA. These guidelines are intended to be used in clinical practice and to form a basis for more research. The integration of these guidelines, and combining them with pharmacodynamic effects, should be considered and could form a basis for further study.

Use of probabilistic modeling within a physiologically based pharmacokinetic model to predict sulfamethazine residue withdrawal times in edible tissues in swine

The presence of antimicrobial agents in edible tissues of food-producing animals remains a major public health concern. Probabilistic modeling techniques incorporated into a physiologically based pharmacokinetic (PBPK) model were used to predict the amounts of sulfamethazine residues in edible tissues in swine. A PBPK model for sulfamethazine in swine was adapted to include an oral dosing route. The distributions for sensitive parameters were determined and were used in a Monte Carlo analysis to predict tissue residue times. Validation of the distributions was done by comparison of the results of a Monte Carlo analysis to those obtained with an external data set from the literature and an in vivo pilot study. The model was used to predict the upper limit of the 95% confidence interval of the 99th percentile of the population, as recommended by the U.S. Food and Drug Administration (FDA). The external data set was used to calculate the withdrawal time by using the tolerance limit algorithm designed by FDA. The withdrawal times obtained by both methods were compared to the labeled withdrawal time for the same dose. The Monte Carlo method predicted a withdrawal time of 21 days, based on the amounts of residues in the kidneys. The tolerance limit method applied to the time-limited data set predicted a withdrawal time of 12 days. The existing FDA label withdrawal time is 15 days. PBPK models can incorporate probabilistic modeling techniques that make them useful for prediction of tissue residue times. These models can be used to calculate the parameters required by FDA and explore those conditions where the established withdrawal time may not be sufficient.

Population-based analysis of methadone distribution and metabolism using an age-dependent physiologically based pharmacokinetic model

Limited pharmacokinetic (PK) and pharmacodynamic (PD) data are available to use in methadone dosing recommendations in pediatric patients for either opioid abstinence or analgesia. Considering the extreme inter-individual variability of absorption and metabolism of methadone, population-based PK would be useful to provide insight into the relationship between dose, blood concentrations, and clinical effects of methadone. To address this need, an age-dependent physiologically based pharmacokinetic (PBPK) model has been constructed to systematically study methadone metabolism and PK. The model will facilitate the design of cost-effective studies that will evaluate methadone PK and PD relationships, and may be useful to guide methadone dosing in children. The PBPK model, which includes whole-body multi-organ distribution, plasma protein binding, metabolism, and clearance, is parameterized based on a database of pediatric PK parameters and data collected from clinical experiments. The model is further tailored and verified based on PK data from individual adults, then scaled appropriately to apply to children aged 0-24 months. Based on measured variability in CYP3A enzyme expression levels and plasma orosomucoid (ORM2) concentrations, a Monte-Carlo-based simulation of methadone kinetics in a pediatric population was performed. The simulation predicts extreme variability in plasma concentrations and clearance kinetics for methadone in the pediatric population, based on standard dosing protocols. In addition, it is shown that when doses are designed for individuals based on prior protein expression information, inter-individual variability in methadone kinetics may be greatly reduced.

A Mechanistic Approach for the Scaling of Clearance in Children

BACKGROUND AND OBJECTIVE

Clearance is an important pharmacokinetic concept for scaling dosage, understanding the risks of drug-drug interactions and environmental risk assessment in children. Accurate clearance scaling to children requires prior knowledge of adult clearance mechanisms and the age-dependence of physiological and enzymatic development. The objective of this research was to develop and evaluate ontogeny models that would provide an assessment of the age-dependence of clearance.

METHODS

Using in vitro data and/or in vivo clearance values for children for eight compounds that are eliminated primarily by one process, models for the ontogeny of renal clearance, cytochrome P450 (CYP) 3A4, CYP2E1, CYP1A2, uridine diphosphate glucuronosyltransferase (UGT) 2B7, UGT1A6, sulfonation and biliary clearance were developed. Resulting ontogeny models were evaluated using six compounds that demonstrated elimination via multiple pathways. The proportion of total clearance attributed to each clearance pathway in adults was delineated. Each pathway was individually scaled to the desired age, inclusive of protein-binding prediction, and summed to generate a total plasma clearance for the child under investigation. The paediatric age range included in the study was premature neonates to sub-adults.

RESULTS

There was excellent correlation between observed and predicted clearances for the model development (R2 = 0.979) and test sets (Q2 = 0.927). Clearance in premature neonates could also be well predicted (development R2 = 0.951; test Q2 = 0.899).

CONCLUSION

Paediatric clinical trial development could greatly benefit from clearance scaling, particularly in guiding dosing regimens. Furthermore, since the proportion of clearance via different elimination pathways is age-dependent, information could be gained on the developmental extent of drug-drug interactions.

Development and Evaluation of a Generic Physiologically Based Pharmacokinetic Model for Children

BACKGROUND

Clinical trials in children are being encouraged by regulatory authorities in light of the immense off-label and unlicensed use of drugs in the paediatric population. The use of in silico techniques for pharmacokinetic prediction will aid in the development of paediatric clinical trials by guiding dosing regimens, ensuring efficient blood sampling times, maximising therapeutic effect and potentially reducing the number of children required for the study. The goal of this study was to extend an existing physiologically based pharmacokinetic (PBPK) model for adults to reflect the age-related physiological changes in children from birth to 18 years of age and, in conjunction with a previously developed age-specific clearance model, to evaluate the accuracy of the paediatric PBPK model to predict paediatric plasma profiles.

METHODS

The age-dependence of bodyweight, height, organ weights, blood flows, interstitial space and vascular space were taken from the literature. Physiological parameters that were used in the PBPK model were checked against literature values to ensure consistency. These included cardiac output, portal vein flow, extracellular water, total body water, lipid and protein. Five model compounds (paracetamol [acetaminophen], alfentanil, morphine, theophylline and levofloxacin) were then examined by gathering the plasma concentration-time profiles, volumes of distribution and elimination half-lives from different ages of children and adults. First, the adult data were used to ensure accurate prediction of pharmacokinetic profiles. The model was then scaled to the specific age of children in the study, including the scaling of clearance, and the generated plasma concentration profiles, volumes of distribution and elimination half-lives were compared with literature values.

RESULTS

Physiological scaling produced highly age-dependent cardiac output, portal vein flow, extracellular water, total body water, lipid and protein values that well represented literature data. The pharmacokinetic profiles in children for the five compounds were well predicted and the trends associated with age were evident. Thus, young neonates had plasma concentrations greater than the adults and older children had concentrations less than the adults. Eighty-three percent, 97% and 87% of the predicted plasma concentrations, volumes of distribution and elimination half-lives, respectively, were within 50% of the study reported values. There was no age-dependent bias for term neonates to 18 years of age when examining volumes of distribution and elimination half-lives.

CONCLUSION

This study suggests that the developed paediatric PBPK model can be used to scale pharmacokinetics from adults. The accurate prediction of pharmacokinetic parameters in children will aid in the development of dosing regimens and sampling times, thus increasing the efficiency of paediatric clinical trials.