Pharmacogenetic prediction of individual variability in drug response based on CYP2D6, CYP2C9 and CYP2C19 genetic polymorphisms
| Autor: | Shafqat Rasul Chaudhry, Marco Klemm, Maria-Paz Weisshaar, Sajjad Muhammad, Thomas Efferth, Moritz Eidens, Dilaware Khan |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
Pharmacology
Genetics Drug education.field_of_study CYP2D6 Polymorphism Genetic media_common.quotation_subject Clinical Biochemistry Population Area under the curve Computational biology CYP2C19 Biology Cytochrome P-450 CYP2C19 Cytochrome P-450 CYP2D6 Pharmaceutical Preparations Pharmacogenetics Humans education CYP2C9 Drug metabolism media_common Cytochrome P-450 CYP2C9 |
| Zdroj: | Current drug metabolism. 15(7) |
| ISSN: | 1875-5453 |
| Popis: | Interindividual variability in drug response depends on a number of genetic and environmental factors. The metabolic enzymes are well known for their contribution to this variability due to drug-drug interactions and genetic polymorphisms. The phase I drug metabolism is highly dependent upon the cytochrome P450 mono-oxygenases (CYP) and their genetic polymorphism leads to the variable internal drug exposures. The highly polymorphic CYP2C9, CYP2C19 and CYP2D6 isozymes are responsible for metabolizing a large portion of routinely prescribed drugs and contribute significantly to adverse drug reactions and therapeutic failures. In this review, two attractive and easily implementable approaches are highlighted to recommend drug doses ensuring similar internal exposures in the face of these polymorphisms. The first approach relies on subpopulation-based dose recommendations that consider the original population dose as an average of the doses recommended in genetically polymorphic subpopulations. By using bioequivalence principles and assuming linear gene-dose effect, dose recommendations can be made for different metabolic phenotypes. The second approach relates area under the curve to two characteristic parameters; the contribution ratio (CR), computes for the contribution of the metabolic enzyme and the fractional activity (FA), considers the impact of the genetic polymorphism. This approach provides valid and error free internal drug exposure predictions and can take into consideration genetic polymorphisms and drug interactions and/ or both simultaneously. Despite certain advantages and limitations, both approaches provide a good initial frame-work for devising models to predict internal exposure and individualize drug therapy, one of the promises from human genome project. |
| Databáze: | OpenAIRE |
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