Drug dosage individualization based on a random-effects linear lodel
Fecha
2012-01-01
Autores
Diaz, Francisco J.
Cogollo, Myladis R.
Spina, Edoardo
Santoro, Vincenza
Rendon, Diego M.
de Leon, Jose
Título de la revista
ISSN de la revista
Título del volumen
Editor
TAYLOR & FRANCIS INC
Resumen
This article investigates drug dosage individualization when the patient population can be described with a random-effects linear model of a continuous pharmacokinetic or pharmacodynamic response. Specifically, we show through both decision-theoretic arguments and simulations that a published clinical algorithm may produce better individualized dosages than some traditional methods of therapeutic drug monitoring. Since empirical evidence suggests that the linear model may adequately describe drugs and patient populations, and linear models are easier to handle than the nonlinear models traditionally used in population pharmacokinetics, our results highlight the potential applicability of linear mixed models to dosage computations and personalized medicine. Copyright © Taylor & Francis Group, LLC.