The single cell analysis (SCA) market, which is fast growing and increasingly more established, is comprised of sequencing (i.e., that assess nucleic acids such as DNA or RNA) and proteomic technologies that assess analytes at the level of single cells, rather than at the level of an entire cell population.
The fifth edition of this report takes a completely updated and comprehensive look at the SCA market. We assess the SCA market across 6 segments and 31 subsegments: customer (academia, biopharma, applied markets, clinical), workflow step (e.g., tissue dissociation, sample preparation, downstream analysis), analyte (e.g., RNA, DNA, epigenetic, protein, multiomic, other), field-of-study (e.g., oncology, basic cell biology, stem cell biology, microbiology, neurology, immunology, other, non-specific), product type (e.g., instruments, reagents, services, other) and geography (e.g., U.S., Europe, China, Asia-Pacific, ROW). For each of these segments, we provide an estimated market size and growth from 2019 to 2025, as well as key growth drivers and moderators.
We review key factors driving future growth including 1) 10x Genomics driving additional applications (e.g., FFPE-compatibility) on a large and growing install base (>4,250 installs); new applications, namely multiomics approaches, are increasing utility 2) Growing utilization by biopharma, where single cell methods are used to support drug discovery; the advent of FFPE-compatible single cell analysis allows biopharma to tap into archived samples 3) Newer offerings targeting both low-throughput and high-throughput customers (e.g., 10x Genomics’ Chromium X/iX, Parse Biosciences’ Evercode), expanding the user base) 4) Falling sequencing costs are lowering the barrier for new users of SCA and facilitating existing users to increase their throughput / scale of experiments 5) Emerging instrument-free approaches (e.g., Parse, Fluent, Scale) are likely to attract new users to single cell analysis. On the other hand, we discuss key factors moderating growth including 1) High assay costs and associated sequencing costs limit adoption / throughput of users 2) Potential competition with spatial-omics, another expensive research tool, might compete for spend with single cell methods 3) Challenges in data analysis and data integration as throughput and data complexity grows 4) Limited short-term clinical applications.
In addition, we include output from a primary research campaign across 25 single cell researchers in academia, biopharma, and clinical settings. We capture current and anticipated spend, analyte trends (e.g., RNA,DNA, multiomics), platform acquisition trends (i.e., plans on buying additional instruments), and purchasing criteria.
