Individualizing drug dosage by using a random intercept linear model

Abstract

An algorithm for drug dosage individualization is proposed. The algorithm assumes a random intercept linear model for the log of trough-plasma-concentration-to-dosage ratio of the drug at steady-state, and aims at determining an optimum dosage for producing a trough steady-state plasma concentration within a target concentration range. The minimum number of algorithm steps necessary to find the optimum dosage is computed. Computations are illustrated for clozapine, an antipsychotic drug used to treat patients with severe schizophrenia.