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ArrayTrack™ Overview

DNA microarray is a key technology in pharmacogenomics (PGx) and toxicogenomics (TGx), a field that has been identified in the FDA Critical Path document as a major opportunity for advancing medical product development and personalized medicine. FDA issues “Guidance for Industry” on PGx data submission, where industry would be able to interact with the agency in the early stage of drug development by submitting PGx/TGx data, DNA microarray data predominately, through the Voluntary Genomics Data Submission (VGDS) process. It is expected that the regulation of microarray-based medical diagnostics and the review of microarray data submitted as part of an investigational new drugs (IND) or new drug application (NDA) will become an essential regulatory responsibility for the FDA. ArrayTrack, developed at NCTR/FDA, is being integrated and further refined at the US FDA as a review tool for this program.

A single microarray experiment generates a large volume of data. The management, analysis and interpretation of this vast amount of data are the most critical components in realizing the value of the technology. Many solutions are available, but, unfortunately, most of them, if not all, deal with these components separately, posing a great challenge for reviewers to efficiently handle microarray data. ArrayTrack provides a single solution for reviewers to independently analyze data, interpret the information and verify the results submitted by sponsors.

ArrayTrack is logically constructed of three linked components:

a) a database (MicroarrayDB) that stores microarray experiment information;

b) tools (TOOL) for data visualization and analysis; and

c) libraries (LIB) that provide curated functional data from public databases for data interpretation.

Specifically, ArrayTrack is MIAME (Minimum Information About A Microarray Experiment) supportive for storing both microarray data and experiment parameters associated with a toxicogenomics study. A quality control mechanism is implemented to assess the quality of entire expression data as well as quality of each spot on the chip. In addition, many data analysis and visualization tools are available with ArrayTrack, including four normalization methods, several statistical approaches for identification of differentially expressed genes, clustering/classification methods (e.g., PCA, HCA) and so forth.

The current challenge of bioinformatics in microarray is no longer to identify a list of differentially expressed genes, but to develop an effective bioinformatics process and tools for data interpretation and knowledge discovery. Thus, ArrayTrack also provides a rich collection of functional information (in LIB) about genes, proteins and pathways drawn from various public biological databases for facilitating data interpretation. The primary emphasis of ArrayTrack is the direct linking of analysis results with functional information for facilitating the interaction between the choice of analysis methods and the biological relevance of analysis results. Using ArrayTrack, we can select an analysis method from the TOOL and apply the method to selected microarray data stored in the MicroarrayDB; the analysis results can be linked directly to pathways, gene ontology and other functional information stored in LIB.

ArrayTrack is a client-server system. The ORACLE server stores and integrates DNA microarray data (MicroarrayDB) and data from public resources about genes, proteins and pathways (LIB). The JAVA language was used to construct the entire user interface, query mechanism, and data visualization and analysis tools (TOOL).