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Current Hypertension Reviews

Editor-in-Chief

ISSN (Print): 1573-4021
ISSN (Online): 1875-6506

Pharmacokinetic-Pharmacodynamic Modeling of Antihypertensive Drugs: From Basic Research to Clinical Practice

Author(s): Christian Hocht, Marcos A. Mayer, Javier A. W. Opezzo, Facundo M. Bertera and Carlos A. Taira

Volume 4, Issue 4, 2008

Page: [289 - 302] Pages: 14

DOI: 10.2174/157340208786241273

Price: $65

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Abstract

Knowledge of pharmacokinetic-pharmacodynamic (PK/PD) properties of antihypertensive drugs may optimize drug therapy of hypertension. PK/PD modeling of antihypertensive drugs in both basic and clinical research could contribute to drug development and clinical practice in several aspects, including a profound evaluation of the efficacy and safety of investigational antihypertensive agents, enhancement of preclinical information during the development process, identification of factors that contribute to drug response variability, by allowing a rapid identification of poor or nonresponders and by helping to determine optimal antihypertensive drug and dose requirements in each hypertensive patient. Although a concentration-response relationship for antihypertensive agents was found in normotensive and hypertensive patients, there are some limitations in PK/PD modeling of antihypertensive drugs in the clinical setting, including application of inadequate pharmacodynamic models and the inability to study large doses of antihypertensive drugs in order to determine the complete pharmacodynamic range of their antihypertensive effect. Most limitations in the clinical study of PK/PD models of antihypertensive drugs are not present in basic research, and therefore study of PK/PD models in laboratory animals could be of interest. The aim of the present review is to describe the current knowledge of PK/PD modeling of antihypertensive drugs in basic and clinical research and its future applications.

Keywords: Antihypertensive drugs, pharmacokinetic-pharmacodynamic modeling, drug development, clinical practice, dose optimization


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