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tion of the study (component) performed

• The pharmacogenomic (PG) and pharamacogenomics results (PR) domains will support submission of summarized genomic (genotypic data).

• A new imaging (IM) domain will include a mapping of the relevant DICOM metadata fields required to summarize an imaging submission.

The PG domain belongs to the findings class and is designed to store panel ordering information. The detailed test-level information (such as Genotype/SNP summarized results) is reported in the PR domain. Figure 6 shows what a typical genotype test might look like in terms of data content and use of the HUGO [14] nomenclature. The PG domain supports the hierarchical nature of pharmacogenomic results, where for a given genetic test (such as EGFR, CYP2D6, etc.) from a patient sample (listed in the parent domain), multiple Genotypes/SNPs can be reported (listed in the child domain). To support the use of imaging biomarkers, DICOM metadata tags have to be mapped into the fields of the new IM domain. Table 1 illustrates this mechanism.

While the FDA has proposed the SDTM data model for submission data, it is clear that this is only an interchange format for sponsors to submit summary clinical study data to the FDA in a standardized fashion. The FDA identified a need for an additional relational repository model to store the SDTM data sets. The requirement was to design a normalized and extensible relational repository model that would scale up to a huge collection of studies going back into the past and supporting those in the future. Under a CRADA, the FDA and IBM jointly developed this submissions repository called Janus (named after the two-headed Roman God) that can look backward to support historic retrospective trials and look forward to support prospective trials. The data classification system of CDISC such as interventions, findings, and events was leveraged in the Janus model with linkages to the subjects (for the patients enrolled in the clinical trial) to facilitate the navigation across the different tables by consolidating data in three major tables. Benefits resulting from this technique include reduced database maintenance and a simpler data structure that is easier to understand and can support cross-trial analysis scenarios. The ETL (extract-1ransform-1oad) process for loading the SDTM domain data sets instantiates the appropriate class table structure in Janus without requiring any structural changes.

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