Spatial Genomics Transcriptomics MarketSize and Trends
The market for global spatial genomics transcriptomics is expected to be valued at US$ 262.7 million in 2023 and is forecasted to reach a value of US$ 618.9 million by 2030, with a CAGR of 13.0% from 2023 to 2030. Factors contributing to market growth include advancements in drug discovery & development technologies, increasing funding for research & development in the field of genomics, and growth in the demand for spatial omics.
Spatial Genomics Transcriptomics Market Trends:
- Shift towards single-cell analysis: There is a growing trend in focusing on single-cell spatial genomics to obtain a more detailed understanding of individual cellular functions and their roles in complex tissues
- Automation of spatial genomics workflow: The automation of spatial genomics workflows is poised to significantly impact the spatial genomics transcriptomics market over the forecast period. Automation allows for higher throughput analysis which enables processing greater numbers of samples simultaneously. This increases efficiency and reduces costs per sample analyzed. It also helps address the current bottleneck of labor-intensive manual sample processing in spatial genomics.
Figure 1. Global Spatial Genomics Transcriptomics Market Share (%), by Type, 2023
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Market Trends:
- Shift towards single-cell analysis: There is a growing trend in focusing on single-cell spatial genomics to obtain a more detailed understanding of individual cellular functions and their roles in complex tissues.
- Automation of spatial genomics workflow: The automation of spatial genomics workflows is poised to significantly impact the spatial genomics transcriptomics market over the forecast period.
- Technological advancements in spatial genomics transcriptomics: Advancement in the field of spatial genomics and spatial transcriptomics are enabling researchers to more comprehensively map gene expression within tissue samples at an unprecedented resolution. Technologies, such as spatial transcriptomics, utilize microscopic imaging techniques combined with nucleic acid probes or sequencing to characterize the transcriptomes of thousands of individual cells simultaneously while still spatially resolved within a tissue section.