Effect of the Number of Samples on Bayesian and Non‐linear Least‐squares Individualization: A Study of Cyclosporin Treatment of Haematological Patients with Multidrug Resistance

We have studied whether the prediction of drug concentrations improves as the number of samples used for individualization is increased, and whether the Bayesian method of individualization is superior to the non‐linear least‐squares method. Data were obtained from ten adult haematological patients with multidrug resistance who were treated with cyclosporin. The predictions of blood–cyclosporin concentrations were made using the Abbott PKS program. The number of samples used for individualization was increased from 1 to 30 for the Bayesian method and from 4 to 30 for the non‐linear least‐squares method. Linear regression, percentage prediction error, and absolute and relative predictive performance were used to evaluate the predictions.