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Implications of pharmacogenetics for individualizing drug treatment and for study design
Authors:Email author" target="_blank">Christian?MeiselEmail author  Thomas?Gerloff  Julia?Kirchheiner  Przemyslaw?M?Mrozikiewicz  Przemyslaw?Niewinski  Jürgen?Brockm?ller  Ivar?Roots
Institution:Institute of Clinical Pharmacology, Berlin Center for Genome-Based Bioinformatics, University Hospital Charité, Humboldt University of Berlin, Schumannstrasse 20-21, 10098 Berlin, Germany. christian.meisel@charite.de
Abstract:Adverse drug reactions and ineffective drug treatment are responsible for a large health care burden. Considerable variability in drug response makes the prediction of the individual reaction difficult. Pharmacogenetics can help to individualize drug treatment in accordance with the genetic make-up of the patient. Drug response is best understood as a complex interplay between pharmacokinetics, pharmacodynamics, and other disease-associated factors. There are a large number of genetic variants in the enzymes of phase I and phase II drug metabolism, in drug transporters, and drug targets, all of which account for differences in drug response. The polymorphisms in the cytochrome P450 enzyme system have been investigated most extensively. Genotype-based dose adjustment which should ensure "bioequivalent" drug concentrations in all patients has been derived from pharmacokinetic parameters, but this approach will have to be verified in prospective studies. Drug transport has recently been recognized as a further crucial determinant in pharmacokinetics. The effect of genetics on disease susceptibility and drug treatment has been studied quite extensively; however, hardly any of this progress is at present reflected in routine health care. The integration of pharmacogenetic factors in clinical trials requires novel considerations for study design and data interpretation. It is to be hoped that the new science bioinformatics will (a) help us identify the contribution of genetics to disease and treatment response and will (b) create data-processing devices which help the physician in the face of the enormously expanding scientific knowledge in selecting the best individually adapted treatment for the patient.
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