1On fitting model equations to experimental data, the situation may arise that individual subjects provide insufficient information to obtain adequate parameter estimates due to the fact that not all aspects are exhibited by all subjects or that the models are simply too complex. This may be solved by applying nonlinear mixed effect modelling to the data, which integrates the information provided by different subjects. 2We aim to provide insight into the methodology and its use in these situations, illustrated by three examples: determination of pharmacokinetics in a rising dose design, where the lower doses provide insufficient information (due to assay limitations) to estimate terminal half-life; determination of the kinetics of the low molecular weight heparin enoxaparine (Clexane®) using anti-Xa activity, effectively dealing with lingering low/basal activity; simultaneous estimation of the pharmacokinetics and pharmacodynamics of the low molecular weight heparin dalteparine (Fragmin®) after subcutaneous and intravenous administration.