The DMET™ Plus Premier Pack is used as part of the DMET Plus Solution.
Translating pharmacogenetics into practice Understanding the common variation in genes encoding for drug metabolism enzymes and drug transporters has the potential to significantly impact clinical research by predicting the impact of an individual's genetic variation on metabolic capacity. This understanding takes us one step closer towards the vision of personalized medicine by helping to avoid adverse drug responses, increasing treatment efficacy, and providing both improved healthcare outcomes as well as substantial economic benefits.
The DMET Plus Solution consists of the: • DMETPlus Assay – Molecular Inversion Probe (MIP) panel amplifies the precise target DNA of interest • DMETPlus Array – allele-specific oligonucleotide array provides a single color readout on the GeneChip™ Scanner 3000 or GeneChip Scanner 3000Dx v.2, installed in over 2,000 labs globally • DMET Console Analysis Software – provides both the flexibility for user-defined reporting as well as the most comprehensive translation from genotypic data to star allele classification to predicted metabolizer status for the most clinically relevant genes
Key Benefits • Enables the cost-effective measurement of existing and new metabolic pathway involvement – by providing broad coverage of relevant pharmacogenetic markers (1,936 genetic variants across 231 relevant genes) in one assay • Provides high confidence in results – outstanding assay performance of ≥99% average sample call rate and ≥99.8% average sample reproducibility enables the accurate generation of haplotypes and supports longitudinal and other clinical research studies • Supports the rapid and comprehensive interpretation of genotyping data – the DMET Console Software tool translates genotyping data through to star allele classification and to predicted metabolizer status, allowing the rapid implementation of genetic understanding in clinical research
During the development of the DMET Plus Panel, an average sample pass rate in excess of 95 percent was observed with the specifications above, based on the performance of more than 3,500 samples processed by six sites (three external and three internal). Markers have been evaluated across a minimum of 1,200 individuals including 597 individuals from the extended HapMap population data. See Fig. 1 for Peformance Specifications.
Comprehensive and relevant genetic content • 1,936 SNP, copy number, and indel markers across 231 genes including many genetic variants that cannot easily be detected by other technologies (e.g. SNPs and indels with secondary polymorphisms in close proximity, triallelic markers, and variants from multi-gene families) • 100% coverage of PharmaADME 'Core ADME Genes' (32 genes) and 95% coverage of PharmaADME 'Core Markers' (185 variants)
Extensive coverage beyond PharmaADME core content to cover common and functional variants associated with hepatic detoxification for processing xenobiotics and environmental toxins including: • Markers associated with newly described adverse drug events (e.g., CYP3A4_-392A>G) • Structural variants in transporter genes - an important pharmaceutical target (e.g., ABCG2_c.421C>A(Q141K) • Enrichment for mutations in ADME regulatory genes (e.g., PPARD_c.-101-25241A>G • Inclusion of many population specific markers (e.g., VKORC1_c.-1639G>A)
Comprehensive interpretation analysis
The DMET Console Software offers: • Single-sample genotyping – pre-defined marker boundaries allow samples to be processed in batches of any size with no impact on reported genotypes • Easy-to-view data – cluster visualization for SNP and copy number markers • Customized content data reports – user-defined marker lists for initial genotyping as well as final reports • Translation of genotypes into gene – level diplotypes using star allele nomenclature and then into a metabolizer status bin that indicates the relative level of metabolic activity, for example, the metabolic status bin that describes ultra-rapid metabolizers (UM), extensive metabolizers (EM), intermediate metabolizers (IM) and poor metabolizers (PM).
Applications of DMET Plus Solution include: • Pharmacology research – discovery and application of novel biomarkers resulting from pharmacogenetic associations • Translational clinical research – longitudinal clinical research studies designed to generate comprehensive metabolic profiles • Pre-clinical research and development – approximately 30% of drug candidates fail during development due to poor pharmacokinetics and toxicity, which can be strongly influenced by genetically determined variation in drug metabolizing genes and transporter genes • Clinical research trials – building databases of known genotypes to show effects of known metabolic pathways in intermediate and poor metabolizers and to confirm metabolic pathway involvement in newly discovered drug metabolism associations
DMET Plus Solution Publications
The following publications and review articles demonstrate the importance and the utility of DMET Plus Products in pharmacogenomic studies, clinical research and the development of personalized medicine. Hu Y., et al. Genotyping performance between saliva and blood-derived genomic DNAs on the DMET array: a comparison. PLoS One, 7(3): e33968 (2012). Burmester J. K., et al. DMET microarray technology for pharmacogenomics-based personalized medicine. Methods in Molecular Biology 632:99-124 (2010). Sissung T. M., et al. Clinical pharmacology and pharmacogenetics in a genomics era: the DMET platform. Pharmacogenomics 11(1):89-;103 (2010). Bridget Bradley B., et al. Developing an interdisciplinary pharmacogenomic treatment approach to reduce medication burden and improve subject outcomes. Journal of Pharmacy Practice [College of Psychiatric and Neurologic Pharmacists 2011 Poster Abstracts] 24: 268-269 (2011). Stack C.B., et al. Genetic risk estimation in the Coriell Personalized Medicine Collaborative. Genetics in Medicine 13(2):131-139 (2011). Man M., et al. Genetic variation in metabolizing enzyme and transporter genes: Comprehensive assessment in 3 major East Asian subpopulations with comparison to Caucasians and Africans. Journal of Clinical Pharmacology 50(8): 929-;940 (2010). UNC's McCleod discusses 'practical' approach to bringing pharmacogenetics to all countries. GenomeWeb Pharmacogenomics Reporter (2010). Affymetrix, Inc. Coriell Institiute for Medical Research selects DMET Plus Product for national personalized medicine project. Press release (2009).
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