Market Challenges And Opportunities
Global Single-cell Omics Market Drivers
- Growing Application Areas: Global single-cell omics market is experiencing significant growth due to expanding application areas of Omics technologies. Single omics refers to the study of various biological molecules including genomics, proteomics or metabolomics in isolation. Traditionally, these Omics areas were studied separately to gain insights into life sciences challenges. However, with advancement in high-throughput technologies, researchers are able to apply single Omics approaches to real-world problems more comprehensively.
- Increasing R&D Funding: Increasing funding and grant from the market players and governments is expected to aid in the market growth. For instance, on September 12, 2023, Fluent BioSciences, a cutting edge life sciences company, announced the award of an NIH Small Business Innovation Research (SBIR) Phase II grant, funded by the National Institute of General Medical Sciences (NIGMS, 1 R44 GM1376648). This funding will advance the commercialization of groundbreaking methods and reagents for high-throughput single cell analysis.
Global Single-cell Omics Market Opportunities
- Collaboration and Partnerships: Market players are focusing on inorganics strategies such as merger and collaboration which is expected to drive the market growth over the forecast period. For instance, on June 17, 2022, Fluent BioSciences, a biotechnology company focused on making single-cell analysis simple and accessible and NanoCellect Biomedical, Inc., which provides solution for solutions for cell sorting, announced a collaboration to improve resolution and efficacy of single cell ribonucleic acid (RNA) sequencing analysis of rare cell populations.
Global Single-cell Omics Market Restraints
- Technical challenges: The growth of the global single-cell omics market is facing considerable technical challenges which are restraining its trajectory. One of the major hurdles is the limitation of single-cell omics approach itself where it examines only one type of biomolecule such as deoxyribonucleic acid (DNA), ribonucleic acid (RNA) or proteins in isolation. This provides an incomplete picture of complex biological systems as various omics data such as genome, transcriptome, proteome and metabolome influence each other. Studying them separately through traditional single omics methods make it difficult to understand how biological pathways interact as a whole network. This is a significant drawback in the post-genomic era where understanding the system-wide level interplay between different biomolecules is critical.
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