No abstract

Mathematical modelling was used to extrapolate enalapril efficacy to young children to support a paediatric investigation plan targeting a paediatric-use marketing authorization application.

A preliminary population pharmacokinetic (PopPK) model of valacyclovir in children was developed from non-compartmental analysis (NCA) parameter values from literature, including several age groups, combined with Bayesian priors from a PopPK model of acyclovir, the active metabolite of valacyclovir, from literature too. Also a simulation study was carried out to evaluate the performance of various modelling choices related to the estimation of model parameters from NCA parameters originating from sparse PK studies. Assuming a one-compartment model with first order absorption, a mixed effects, meta-analysis approach was utilized which allows accounting the random intergroup variability, the detection of covariates and the application of informative Bayesian priors on the parameters. The conclusions from the simulation study calculating bias and precision for various cases, were that a model which takes explicitly into account the sampling schedule, performs better than a model using the theoretical expressions of calculating the NCA parameters. Also by using the geometric rather than the arithmetic means of NCA parameters, less biased results are obtained. These findings guided the choices for the valacyclovir model, for which informative priors from a PopPK model of acyclovir were applied for some of the parameters, in order to include a richer covariate model for clearance, not supported by the NCA dataset and a value for bioavailability. This preliminary valacyclovir model can be used in simulations to provide dosage recommendations for children of various ages and to help design more efficiently prospective clinical trials.