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Clinical application of high throughput molecular screening techniques for pharmacogenomics

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Author(s): Wiita AP | Schrijver I

Journal: Pharmacogenomics and Personalized Medicine
ISSN 1178-7066

Volume: 2011;
Issue: default;
Start page: 109;
Date: 2011;
Original page

ABSTRACT
Arun P Wiita1, Iris Schrijver21Department of Laboratory Medicine, University of California, San Francisco, CA, USA; 2Department of Pathology and Pediatrics, Stanford University School of Medicine, Stanford, CA, USAAbstract: Genetic analysis is one of the fastest-growing areas of clinical diagnostics. Fortunately, as our knowledge of clinically relevant genetic variants rapidly expands, so does our ability to detect these variants in patient samples. Increasing demand for genetic information may necessitate the use of high throughput diagnostic methods as part of clinically validated testing. Here we provide a general overview of our current and near-future abilities to perform large-scale genetic testing in the clinical laboratory. First we review in detail molecular methods used for high throughput mutation detection, including techniques able to monitor thousands of genetic variants for a single patient or to genotype a single genetic variant for thousands of patients simultaneously. These methods are analyzed in the context of pharmacogenomic testing in the clinical laboratories, with a focus on tests that are currently validated as well as those that hold strong promise for widespread clinical application in the near future. We further discuss the unique economic and clinical challenges posed by pharmacogenomic markers. Our ability to detect genetic variants frequently outstrips our ability to accurately interpret them in a clinical context, carrying implications both for test development and introduction into patient management algorithms. These complexities must be taken into account prior to the introduction of any pharmacogenomic biomarker into routine clinical testing.Keywords: high throughput, clinical laboratories, pharmacogenomics, mutation
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