Population Pharmacokinetics of Lithium in Young Pediatric Patients With Intellectual Disability

The pharmacokinetic behavior of medicines used in humans follows largely predictable patterns across the human age range from premature babies to elderly adults. Most of the differences associated with age are in fact due to differences in size. Additional considerations are required to describe the processes of maturation of clearance processes and postnatal changes in body composition. Application of standard approaches to reporting pharmacokinetic parameters is essential for comparative human pharmacokinetic studies from babies to adults. A standardized comparison of pharmacokinetic parameters obtained in children and adults is shown for 46 drugs. Appropriate size scaling shows that children (over 2 years old) are similar to adults. Maturation changes are generally completed within the first 2 years of postnatal life; consequently babies may be considered as immature children, whereas children are just small adults.

This is the first meta-analysis of randomized placebo-controlled trials testing lithium as a treatment for patients with Alzheimer's disease (AD) and individuals with mild cognitive impairment (MCI).

Taking parameter uncertainty into account is key to make drug development decisions such as testing whether trial endpoints meet defined criteria. Currently used methods for assessing parameter uncertainty in NLMEM have limitations, and there is a lack of diagnostics for when these limitations occur. In this work, a method based on sampling importance resampling (SIR) is proposed, which has the advantage of being free of distributional assumptions and does not require repeated parameter estimation. To perform SIR, a high number of parameter vectors are simulated from a given proposal uncertainty distribution. Their likelihood given the true uncertainty is then approximated by the ratio between the likelihood of the data given each vector and the likelihood of each vector given the proposal distribution, called the importance ratio. Non-parametric uncertainty distributions are obtained by resampling parameter vectors according to probabilities proportional to their importance ratios. Two simulation examples and three real data examples were used to define how SIR should be performed with NLMEM and to investigate the performance of the method. The simulation examples showed that SIR was able to recover the true parameter uncertainty. The real data examples showed that parameter 95 % confidence intervals (CI) obtained with SIR, the covariance matrix, bootstrap and log-likelihood profiling were generally in agreement when 95 % CI were symmetric. For parameters showing asymmetric 95 % CI, SIR 95 % CI provided a close agreement with log-likelihood profiling but often differed from bootstrap 95 % CI which had been shown to be suboptimal for the chosen examples. This work also provides guidance towards the SIR workflow, i.e.,which proposal distribution to choose and how many parameter vectors to sample when performing SIR, using diagnostics developed for this purpose. SIR is a promising approach for assessing parameter uncertainty as it is applicable in many situations where other methods for assessing parameter uncertainty fail, such as in the presence of small datasets, highly nonlinear models or meta-analysis. Electronic supplementary material The online version of this article (doi:10.1007/s10928-016-9487-8) contains supplementary material, which is available to authorized users.