April 21, 2024

Cell Surface Markers Detection Market driven by Growing Applications of Cell Surface Markers in Research and Clinical Applications

The cell surface markers detection market plays a vital role in biomedical research and clinical diagnosis by enabling the identification and isolation of specific cell populations. Cell surface markers are proteins or sugars that are expressed on the outer surface of a cell and help identify the specific cell type. Some of the major applications of these markers include identification of stem cells, immunophenotyping of lymphocytes, cancer diagnosis and prognosis. Techniques such as flow cytometry, immunohistochemistry and polymerase chain reaction are widely used for detecting cell surface markers.

With the rising incidence of chronic diseases like cancer and neurological disorders, the use of cell surface markers in disease diagnosis and therapeutic selection has gained significant traction in recent years. Cell surface markers help in detecting minimal residual disease and monitoring treatment response in cancer. They also aid in customized treatment selection based on the molecular characteristics of individual tumors. In neuroscience research, cell surface markers are useful for identifying discrete classes of neurons and their roles in diseases like Alzheimer’s and Parkinson’s.

The global Cell Surface Markers Detection Market is estimated to be valued at US$ 5,459.5 Mn in 2023 and is expected to exhibit a CAGR of 9.1% over the forecast period 2023 to 2030, as highlighted in a new report published by Coherent Market Insights.

Market key trends:

One of the key trends in the cell surface markers detection market is the development of biomarkers for various diseases. Biomarkers aid in early disease detection, prognosis, monitoring treatment response and recurrence. For instance, prostate specific membrane antigen (PSMA) has emerged as an important biomarker for detecting prostate cancer recurrence after initial treatment. Autoimmune disease biomarkers detected using cell surface markers are enabling development of personalized treatment approaches. Nanoparticles conjugated with antibodies against disease specific cell surface markers represent another developing area with potential to improve disease detection. These nanobioconjugates offer enhanced sensitivity and specificity compared to conventional detection methods. Their application in liquid biopsy for non-invasive cancer monitoring holds significant promise.

Porter’s Analysis

Threat of new entrants: Low. High capital requirements and established competitors pose barriers to entry.

Bargaining power of buyers: Moderate. Buyers have some negotiating power due to differing supplier options.

Bargaining power of suppliers: Low. Suppliers lack bargaining power due to fragmented nature of suppliers.

Threat of new substitutes: Low. Limited substitutes exist for cell surface markers detection.

Competitive rivalry: High. Intense competition amongst existing players to gain market share.

Key Takeaways

The global cell surface markers detection market is expected to witness high growth. The global Cell Surface Markers Detection Market is estimated to be valued at US$ 5,459.5 Mn in 2023 and is expected to exhibit a CAGR of 9.1% over the forecast period 2023 to 2030.

North America is expected to dominate the global market during the forecast period. Factors such as increasing funds for cancer research, high adoption of cell surface markers in clinical diagnosis are expected to drive market growth in the region.

Key players operating in the cell surface markers detection market are Grifols SA, Abbott Laboratories, Sysmex Corporation, Agilent Technologies Inc., Nexcelom Bioscience, Thermo Fisher Scientific Inc. Grifols SA specializes in producing blood plasma proteins and develops tools to help doctors diagnose and treat patients. Abbott Laboratories develops and commercializes health care solutions through four business segments.

*Note:

  1. Source: Coherent Market Insights, Public sources, Desk research
  2. We have leveraged AI tools to mine information and compile it

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