Pharmacometric estimation methods for aggregate data, including data simulated from other pharmacometric models.

ABSTRACT: Lack of data is an obvious limitation to what can be modelled. However, aggregate data in the form of means and possibly (co)variances, as well as previously published pharmacometric models, are often available. Being able to use all available data is desirable, and therefore this paper will outline several methods for using aggregate data as the basis of parameter estimation. The presented methods can be used for estimation of parameters from aggregate data, and as a computationally efficient alternative for the stochastic simulation and estimation procedure. They also allow for population PK/PD optimal design in the case when the data-generating model is different from the data-analytic model, a scenario for which no solutions have previously been available. Mathematical analysis and com

SUBMITTER: Valitalo PAJ 

PROVIDER: S-EPMC8405508 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature