Children differ from adults in their response to drugs. While this may be the result of changes in dose exposure (pharmacokinetics [PK]) and/or exposure response (pharmacodynamics [PD]) relationships, the magnitude of these changes may not be solely reflected by differences in body weight. As a consequence, dosing recommendations empirically derived from adults dosing regimens using linear extrapolations based on body weight, can result in therapeutic failure, occurrence of adverse effect or even fatalities. In order to define rational, patient-tailored dosing schemes, population PK–PD studies in children are needed. For the analysis of the data, population modelling using non-linear mixed effect modelling is the preferred tool since this approach allows for the analysis of sparse and unbalanced datasets. Additionally, it permits the exploration of the influence of different covariates such as body weight and age to explain the variability in drug response. Finally, using this approach, these PK–PD studies can be designed in the most efficient manner in order to obtain the maximum information on the PK–PD parameters with the highest precision. Once a population PK–PD model is developed, internal and external validations should be performed. If the model performs well in these validation procedures, model simulations can be used to define a dosing regimen, which in turn needs to be tested and challenged in a prospective clinical trial. This methodology will improve the efficacy/safety balance of dosing guidelines, which will be of benefit to the individual child.

Model-based simulations show that in newborns, including preterms, infants and children under the age of 3 years, a loading dose in microg/kg and a maintenance dose expressed in microg/kg1.5/h, with a 50% reduction of the maintenance dose in newborns younger than 10 days, results in a narrow range of morphine and metabolite serum concentrations throughout the studied age range. Future pharmacodynamic investigations are needed to reveal target concentrations in this population, after which final dosing recommendations can be made.

Allometric scaling on the basis of bodyweight raised to the power of 0.75 (AS0.75) is frequently used to scale size-related changes in plasma clearance (CLp) from adults to children. A systematic assessment of its applicability is undertaken for scenarios considering size-related changes with and without maturation processes. A physiologically-based pharmacokinetic (PBPK) simulation workflow was developed in R for 12,620 hypothetical drugs. In scenario one, only size-related changes in liver weight, hepatic blood flow, and glomerular filtration were included in simulations of ‘true’ paediatric CLp. In a second scenario, maturation in unbound microsomal intrinsic clearance (CLint,mic), plasma protein concentration, and haematocrit were also included in these simulated ‘true’ paediatric CLp values. For both scenarios, the prediction error (PE) of AS0.75-based paediatric CLp predictions was assessed, while, for the first scenario, an allometric exponent was also estimated based on ‘true’ CLp. In the first scenario, the PE of AS0.75-based paediatric CLp predictions reached up to 278 % in neonates, and the allometric exponent was estimated to range from 0.50 to 1.20 depending on age and drug properties. In the second scenario, the PE sensitivity to drug properties and maturation was higher in the youngest children, with AS0.75 resulting in accurate CLp predictions above 5 years of age. Using PBPK principles, there is no evidence for one unique allometric exponent in paediatric patients, even in scenarios that only consider size-related changes. As PE is most sensitive to the allometric exponent, drug properties and maturation in younger children, AS0.75 leads to increasingly worse predictions with decreasing age.Electronic supplementary materialThe online version of this article (doi:10.1007/s40262-016-0436-x) contains supplementary material, which is available to authorized users.

PurposeTo explore different allometric equations for scaling clearance across the human life-span using propofol as a model drug.MethodsData from seven previously published propofol studies ((pre)term neonates, infants, toddlers, children, adolescents and adults) were analysed using NONMEM VI. To scale clearance, a bodyweight-based exponential equation with four different structures for the exponent was used: (I) 3/4 allometric scaling model; (II) mixture model; (III) bodyweight-cut-point separated model; (IV) bodyweight-dependent exponent model.ResultsModel I adequately described clearance in adults and older children, but overestimated clearance of neonates and underestimated clearance of infants. Use of two different exponents in Model II and Model III showed significantly improved performance, but yielded ambiguities on the boundaries of the two subpopulations. This discontinuity was overcome in Model IV, in which the exponent changed sigmoidally from 1.35 at a hypothetical bodyweight of 0 kg to a value of 0.56 from 10 kg onwards, thereby describing clearance of all individuals best.ConclusionsA model was developed for scaling clearance over the entire human life-span with a single continuous equation, in which the exponent of the bodyweight-based exponential equation varied with bodyweight.

The BDE model was able to scale both total morphine clearance and glucuronidation clearance through the M3G pathway across all age ranges between (pre)term neonates and adults by allowing the allometric exponent to decrease across the paediatric age range from values higher than 1 for neonates to values lower than 1 for infants and children.

Posaconazole is typically used for preventing invasive yeast and mold infections such as invasive aspergillosis in high-risk immunocompromised patients. The oral suspension was the first released formulation and many pharmacokinetic and pharmacodynamic studies of this formulation have been published. Erratic absorption profiles associated with this formulation were widely reported. Posaconazole exposure was found to be significantly influenced by food and many gastrointestinal conditions, including pH and motility. As a result, low posaconazole plasma concentrations were obtained in large groups of patients. These issues of erratic absorption urged the development of the subsequently marketed delayed-release tablet, which proved to be associated with higher and more stable exposure profiles. Shortly thereafter, an intravenous formulation was released for patients who are not able to take oral formulations. Both new formulations require a loading dose on day 1 to achieve high posaconazole concentrations more quickly, which was not possible with the oral suspension. So far, there appears to be no evidence of increased toxicity correlated to the higher posaconazole exposure achieved with the regimen for these formulations. The higher systemic availability of posaconazole for the delayed-release tablet and intravenous formulation have resulted in these two formulations being preferable for both prophylaxis and treatment of invasive fungal disease. This review aimed to integrate the current knowledge on posaconazole pharmacokinetics, pharmacodynamics, major toxicity, existing resistance, clinical experience in special populations, and new therapeutic strategies in order to get a clear understanding of the clinical use of this drug.

Morphine paediatric dosing algorithms corrected for pharmacokinetic differences alone yield effective doses that prevent over-dosing for neonates with a PNA <10 days. The fact that many neonates and infants with a PNA ≥10 days still required rescue medication warrants pharmacodynamic studies to further optimize the dosing algorithm for these patients.

PurposeA framework for the evaluation of paediatric population models is proposed and applied to two different paediatric population pharmacokinetic models for morphine. One covariate model was based on a systematic covariate analysis, the other on fixed allometric scaling principles.MethodsThe six evaluation criteria in the framework were 1) number of parameters and condition number, 2) numerical diagnostics, 3) prediction-based diagnostics, 4) η-shrinkage, 5) simulation-based diagnostics, 6) diagnostics of individual and population parameter estimates versus covariates, including measurements of bias and precision of the population values compared to the observed individual values. The framework entails both an internal and external model evaluation procedure.ResultsThe application of the framework to the two models resulted in the detection of overparameterization and misleading diagnostics based on individual predictions caused by high shrinkage. The diagnostic of individual and population parameter estimates versus covariates proved to be highly informative in assessing obtained covariate relationships. Based on the framework, the systematic covariate model proved to be superior over the fixed allometric model in terms of predictive performance.ConclusionsThe proposed framework is suitable for the evaluation of paediatric (covariate) models and should be applied to corroborate the descriptive and predictive properties of these models.