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FDA Officials Say MAQC Results Offer 'Foundation' to Use Array Data in PGx

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The first published results of the Microarray Quality Control Consortium could enable pharmacogenomics technologies to play a larger role in the regulatory submissions process, according to US Food and Drug Administration officials.
 
In a foreword to a collection of articles the MAQC published in a special issue of Nature Biotechnology last week, Janet Woodcock, deputy commissioner for operations at the FDA, and Daniel Casciano of the University of Arkansas for Medical Sciences and former director of the FDA’s National Center for Toxicological Research, noted that the agency views the MAQC effort as a “a solid foundation on which to build a consensus on the use of microarray data in a regulatory setting.”
 
The MAQC is a community-wide effort spearheaded by the NCTR to evaluate the reliability of DNA microarray data and involves 137 participants representing 51 organizations, including the National Institutes of Health, the US Department of Agriculture, and the Environmental Protection Agency.
 
The Nature Biotech papers, available here, represent the first formal results of the study to have been published. According to the MAQC participants, the project proved that microarray data from different platforms can be “reproducible and comparable” and will provide the microarray community with metrics to compare different gene-expression platforms. 
 
In their article, Woodcock and Casciano outline the FDA’s recent activities in advancing genomics and pharmacogenomics, including its Critical Path white paper [PGx Reporter 12-09-04], its draft guidance on “Pharmacogenetic Tests and Genetic Tests for Heritable Markers,” [PGx Reporter 02-15-06] and its “Guidance for Industry: Pharmacogenomic Data Submissions.” [PGx Reporter 03-24-05].
 
However, they note, despite these efforts, “most pharmacogenomic data are of an exploratory or of a research nature, and FDA regulations do not require that these data be submitted to an investigational new drug application or that complete reports be submitted to a new drug application or biologics licensing application.”
 
The FDA anticipates that genomic data submissions will grow. In a separate commentary in the same issue of Nature Biotech, Felix Frueh, associate director of the FDA Center for Drug Evaluation and Research and head of the agency's Interdisciplinary Pharmacogenomics Research Group, said that the number of data submissions containing genomic information is increasing “significantly.” The agency has received 20 voluntary genomic data submissions since the VGDS initiative was launched in 2004, and the combined number of VGDS submissions and so-called “consults” — formal requests for genomic data review as part of regular INDs, NDAs, or BLAs — is growing exponentially, reaching more than 15 in the second quarter of 2006 alone.
 
In order to properly evaluate this growing number of submissions that include genomic data, FDA will need to work with industry to develop “an understanding” of relevant scientific issues, Woodcock and Casciano wrote, including “the types of genetic loci or gene expression profiles being explored for pharmacogenomic testing; the test systems and techniques being employed; the problems encountered in applying pharmacogenomic tests to drug development and to clinical outcomes; and the ability to transmit, store, and process large amounts of complex pharmacogenomic data streams with retention of fidelity.”
 
DNA microarrays are expected to be a primary source for pharmacogenomic data, but progress has been hampered in the field due to concerns about the lack of reproducibility and accuracy of the derived data, Woodcock and Casciano noted.
 
The MAQC results go a long way toward resolving many of those concerns, and should “help improve microarray technology and foster its appropriate application in discovery, development, and review of FDA-regulated products,” they wrote.
 

“Ultimately,” they continue, “exploitation of microarray-based biomarkers will help bring about the transition from population-based medical treatment to true personalized medicine.”

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