Precision and Standardization Issues Need to Be Resolved for Wider Acceptance of Microarrays.

PALO ALTO, Calif. -- The precision of microarray assays has been a significant concern among end users, since the tests can produce a high level of false positives and false negatives. Standardization is also receiving a lot of attention from researchers-especially with the need to compare data obtained from the different platforms now available.

This lack of reliability and standardization can be a significant barrier to the adoption of microarrays in industries that traditionally require robust and cost-effective test platforms with a high degree of precision.

Standardization can be achieved if developers can agree on a unified technology platform to design, process, read, and analyze DNA arrays. One innovation is "gene expression mark-up language" (GEML), an open-standard format that preserves expression profile information even when used under different database schemes.

The Microarray Markup Language (MAML) Working Group has created the Microarray Gene Expression Database (MGED) to provide a standard platform for submitting and analyzing the vast amounts of microarray expression data generated by different laboratories.

MAML's goal is to facilitate the adoption of standards for DNA-array annotation and data representation, as well as the introduction of standard experimental controls and data normalization methods.

"The goal of MAML is to enable the establishment of gene data repositories, so that data from different sources can be compared and analyzed, and so that the different software and database platforms can be made to be interoperable," says Technical Insights Research Analyst Katherine Austin.

Both academic and commercial researchers have realized that the huge amounts of data on a single chip can be cumbersome to manage and use. This problem grown with researchers beginning to study the proteins produced by the genes. The quantity of data generated could soon swamp the systems used to analyze them.

Advances in bioinformatics expect to help in the standardization of storage, sharing, and publishing platforms to aid developers in coping with the profusion of data. This technology deals with the design of computer hardware/software and data-storage and analysis platforms that enable researchers to access and evaluate their results.

Sophisticated microarray technologies expects to see increased uptake, especially within the healthcare sector, once physicians and patients are made aware of their benefits. Promoting microarrays' portability, rapid assay times, and smaller sample requirements could be major factors in enhancing demand, despite their high costs.

"Awareness campaigns are likely to involve networking, advertising, and convincing scientists to test the technology," notes Austin.

Microarray technologies expect to find significant use in genomics and proteomics, with miniaturization enabling high-throughput processing. Applications include genotyping, mutation screening, gene expression, and protein-interaction studies. They can also aid clearer understanding of coordination among genes and their inter-relation.

Emerging Technologies in Lab-on-a-Chip: Microarrays and Biochips, part of the Drug Discovery Subscription Service, examines various technology developments in the microarray industry. These include applications, design, fabrication, new detection methods, microfluidic arrays, and further miniaturization down to the nanoarray level. The research deliverable also summarizes the research conducted by top scientists and companies as well as start-ups. Furthermore, it discusses the drivers and challenges in way of commercial success of the technology. Interviews are available to the press.

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Emerging Technologies in Lab-on-a-Chip: Microarrays and Biochips D322

Keywords in this release: lab-on-a-chip, LOC, microarray, biochip, gene expression mark-up language, GEML, microarray markup language, MAML, microarray gene expression database, MGED, genomics, proteomics, glycomics, metabolomics, metabonomics, systems biology, genotyping, mutation screening, gene expression, single nucleotide polymorphism, SNP, personalized medicine, diagnostics, point-of-care, biomarkers, high-throughput screening, HTS.