Microarray Analysis Market: Key Growth Drivers, Opportunities And Challenges

Key players in the microarray analysis market include Thermo Fisher Scientific, Inc. (US), Agilent Technologies, Inc. (US), Molecular Devices (US), PerkinElmer Inc. (US), Illumina, Inc. (US), GE Healthcare (US), and Bio-Rad Laboratories Inc. (US).
The global microarray analysis market is expected to reach USD 5.52 billion by 2023 from USD 3.82 billion in 2018, at a CAGR of 7.6%. The major factors driving the growth of this market are the increasing incidence of cancer, increasing funding for genomic and proteomic research, and growing application areas of microarrays.

By product and service, the market is segmented into consumables, software & services, instruments. In 2018, the consumables segment is estimated to command the largest share of the microarray analysis market. The large share of this segment can be attributed to the growing applications of microarray in various fields and the regular, repeated, & bulk purchases of consumables.

Drivers:

1. Increasing incidence of cancer

DNA microarrays are used for the diagnosis of various types of cancers. As a result, the rising incidence of cancer across the globe is expected to support the growth of the microarray analysis market during the forecast period. According to the WHO, cancer is the second-leading cause of death globally and accounted for 8.8 million deaths in 2015. Also, globally, the incidence of cancer is expected to increase from 14.1 million in 2012 to 21.7 million by 2030. As of 2015, 15.2 million cancer cases were diagnosed globally, with 57.0% of them being reported across developing countries in Africa, Latin America, and Asia (Source: GLOBOCAN, 2012).

2. Growing application areas of microarrays

The microarray technology is primarily used in genome mapping and sequencing applications. However, over the last few years, this technology is increasingly being used in the diagnosis of infectious and genetic diseases, drug discovery, pharmacogenomic research, cancer diagnostics, and forensic applications. Additionally, the microarray technology is also used in immunology research such as the study of the relation between phenotype and gene expression, activation and differentiation of immune cells, regulation of immune responses, analysis of the molecular mechanisms of allergy, and immunological pharmacology.

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Opportunities:

-Personalized medicine enables medical practitioners to identify the exact needs of a patient and then prescribe medicines and treatments accordingly. This approach guarantees better care outcomes. Moreover, advancements in the field of gene therapy are believed to hold the potential for replacing traditional drugs and surgeries by enabling doctors to treat a disorder by inserting a gene into a patient’s cell. DNA microarray and protein microarray are some of the technologies used in the development of personalized medicine. For instance, in the field of personalized cancer management, testing for disease-causing mutations in the BRCA1 and BRCA2 genes is done using the DNA microarray technology. Also, DNA microarray chips enable researchers to analyze patients for the expression of genes associated with a good response to various anti-cancer drugs. For instance, Thermo Fisher Scientific’s GENE CHIP products offer solutions for cancer research on a standard microarray platform.

Challenges:

–  Growing adoption of next-generation sequencing

Over the last decade, the adoption of next-generation sequencing (NGS) has increased significantly in genomic applications. This can primarily be attributed to the technological advancements in NGS platforms and the significant reduction in the cost of sequencing. Moreover, as NGS offers more accurate data, better analysis, and faster results, its demand is increasing among laboratories of all sizes for genomic applications.

Though NGS offers various advantages over microarrays, the latter is an established technology preferred by several researchers as they have gained proficiency in its operation and analysis of results. Also, microarrays involve easier operations, less-complicated sample preparation, and easier data analysis. Hence, though NGS has emerged as a strong alternative to microarrays, various end users will still prefer the use of microarrays for different applications.

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