Pharmacokinetic (PK) parameters for pediatric patients have traditionally been scaled using a linear per kilogram model. This paradigm has resulted in under- and overdosing, depending on the specific age group.
Physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) models can bridge pediatric and adult pharmacology. Assuming that the PD is similar in pediatrics and adults, creating a comparable PK profile requires a more logical approach based on the development of pediatric PBPK models.
The general concept of PBPK modeling is to mathematically describe relevant physiological, physicochemical, and biochemical processes that determine the pharmacokinetics of a compound in as much detail as is appropriate or needed. PBPK models map the complex mechanistic drug movements in the body to a physiologically realistic structure. It needs to incorporate information about developmental physiology and ontogeny of cytochrome P450 and their use to extrapolate drug pharmacokinetics from adults to children and to explore age-related changes.
In recent years, the implementation of PBPK models in pediatric drug development has become more attractive, encouraged by an increased awareness of interest in pediatric research, especially after the new regulations on medicinal products for pediatrics. However, lack of good in vitro and in vivo data could cause PBPK model to under or over predict the pediatric PK.
PK studies in children have limitation of sampling times; therefore appropriate methods such as the population PK (PPK) approach, are necessary for analysis of the PK data. PPK allows the estimation of population and individual parameters as well as intra- and intersubject variability and also the effects of predefined covariates. The PPK approach has a number of attractions for studying PKPD in children: it is less invasive and can thus be considered as more ethical in this age group, and PK sampling times are flexible and can be taken without causing the inconvenience to the patient. However, the choice of the PK sampling design has an important impact on the precision of population parameter estimates.
Several commercial software packages are available in developing PBPK models. Simcyp software (http://www.simcyp.com), allows simulation of complex absorption, distribution, metabolism, and excretion outcomes involving multiple drug interactions and parent drug and metabolite profiles. Software also allows the simulation of virtual patient populations such as obese/morbidly obese individuals and patients with renal impairment or liver cirrhosis, and include a clearance prediction model that incorporates knowledge about growth, maturation of various organs and tissues involved in drug metabolism and elimination across pediatric age groups to predict clearance in children using adult values.