Government and Society: Government and Society: US FDA extends

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PROTEOMICS PROJECTS

Metabolomics Standards Initiative: standards under construction Like proteomics and genomics before it, the metabolomics field is undergoing a growth spurt, according to Rima Kaddurah Daouk, who is at Duke University Medical Center and is the president of the Metabolomics Society. Researchers are becoming more interested in studying metabolites to identify perturbations in biochemical pathways, as well as to define drug-response phenotypes and biomarkers of disease. As the field has progressed, however, researchers have realized that standards are necessary to guide the reporting of how metabolomics experiments were conducted and the results of those experiments. To address this issue, ~150 metabolomics researchers gathered at a meeting held in 2005 at the National Institutes of Health in Bethesda, Md., where they discussed how to develop and implement standards (J. Proteome Res. 2005, 4, 1483). Among the attendees were members of two groups that were making some initial progress in the standards area. The Standard Metabolic Reporting Structure group, which was composed of researchers from six large pharmaceutical companies, was investigating variability in drug metabolite studies. The other group was formed by the Food Standards Agency (U.K.) to assess the quality of genetically modified foods. The topic of how to systematically report the results of such studies was discussed. By the end of the meeting, “the participants said that we

needed to continue this effort in a more coherent way,” explains Oliver Fiehn of the University of California, Davis. And so the Metabolomics Standards Initiative (MSI) was born. The two previous standards efforts were folded into MSI, and Fiehn became the chair of the initiative under the umbrella of the Metabolomics Society. MSI is composed of five working groups that are concerned with different aspects of metabolomics standardization. Members of the Biological Context working group discuss how researchers should report details about the animal, plant, or microbe used in an experiment. For example, in a mouse experiment to measure drug metabolites, the group recommends that researchers document which mouse strain was used, the sample collection method, and the type of diet that was fed to the mice. Another working group called Chemical Analysis deals with statistical and chemometric techniques. Members of the Data Processing group define standards for the description of validation methods and algorithms that are used to handle data. A controlled vocabulary is under development in the Ontology working group. Finally, the Exchange Format group is concerned with data formats for reporting the recommended ­i nformation. Because metabolomics is such a young field, it can benefit from the knowledge already gained from other disciplines, says Fiehn. Some MSI participants also are members of proteomics and genomics standards

groups, so they can keep an eye on what other scientists are doing with regard to this topic. “We just see what’s out there and give our input if we have any or just harvest the fruits,” says Fiehn. He adds that MSI members also try to address topics that other groups have not spent a lot of time on. For example, Fiehn notes that proteomics groups have not emphasized statistical measures, so members of MSI are paying special attention to this need. The current goal for each MSI working group is to produce a checklist of minimal requirements that authors and journal editors could use as a guide for writing and evaluating manuscripts. As these documents are developed, they will be posted on MSI’s website (http:// msi-workgroups.sourceforge.net). Summaries that describe the checklists will be published in an upcoming issue of the Metabolomics Society’s journal, Metabolomics, so that researchers in the field can assess the guidelines and offer feedback, says Fiehn. “The idea is not that these are reporting requirements that will stand for eternity, but rather, we want to be provocative in terms of what we see as minimal requirements and what we see as good practices,” he explains. The future looks bright for metabolomics, and the efforts of MSI participants will get everyone on the same page. For Kaddurah Daouk, the future also includes partnerships with proteomics researchers. “We look forward to building bridges with the proteomics community,” she says. —Katie Cottingham

GOVERNMENT AND SOCIETY

U.S. FDA extends comment period on proposed algorithm regulation The U.S. Food and Drug Administration (FDA) has extended the deadline for receiving comments on its draft guidelines for the regulation of in vitro diagnostic multivariate index assays (IVDMIAs) by an additional 90 days to March 5, 2007. If approved, the guidelines will mandate that algorithms included in assays for the diagnosis, treatment, or prevention of illnesses meet certain pre- and postmarket requirements set forth by FDA before being used in a clinical setting. Many

IVDMIAs have been developed for the analysis of genetic, protein, or metabolic data. Therefore, if the guidance is approved, it will have ramifications for researchers in the —omics fields. The draft is posted at www.fda.gov/ cdrh/oivd/guidance/1610.html, and comments may be sent to www.fda. gov/dockets/ecomments. —Katie Cottingham

NIH releases dbGaP The National Institutes of Health (NIH) has announced the availability of dbGaP, the database of genotype and phenotype. Developed by the National Center

440 Journal of Proteome Research • Vol. 6, No. 2, 2007

for Biotechnology Information (known as NCBI), the database includes data from genomewide association studies in which the link between specific genes and traits are reported. At its launch, dbGaP will house data from two largescale projects: the Age-Related Eye Diseases Study and the National Institute of Neurological Disorders and Stroke Parkinsonian Study. Most of the data is freely available, but to protect patients’ privacy, preauthorization is required to view results for individuals. The database can be accessed at www.ncbi.nlm. nih.gov/entrez/query.fcgi?db=gap. —Katie Cottingham