Multiple outputs or measurement types are commonly gathered in biological experiments.
Often, these experiments are expensive (such as clinical drug trials) or require careful …

One goal of large scale clinical trials is to determine how a drug is processed by, and
cleared from, the human body [ie, its pharmacokinetic (PK) properties] and how these PK …

The population approach to estimating mixed effects model parameters of interest in
pharmacokinetic (PK) studies has been demonstrated to be an effective method in …

Experimental design is fundamental to successful scientific investigation. Poorly designed
experiments lead to the loss of information, which is costly and potentially unethical …

To maximize the chance for success in an experiment, good experimental design is needed.
However, the presence of unique constraints may prevent mapping the experimental …

Pharmacokinetics and pharmacodynamics data are often analysed by mixed‐effects
modelling techniques (also known as population analysis), which has become a standard …

We discuss a Matlab-based library for constructing optimal sampling schemes for
pharmacokinetic (PK) and pharmacodynamic (PD) studies. The software relies on optimal …

This chapter provides an overview of the theory and application of optimal design with the
focus on PKPD studies. Different optimality criteria for parameter estimation and model …

Optimization of clinical trial designs can help investigators achieve higher quality results for
the given resource constraints. The present paper gives an overview of optimal designs for …

Random effects models are widely used in population pharmacokinetics and dose-finding
studies. However, when more than one observation is taken per patient, the presence of …