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C-Reactive Protein Testing Companies Market Position Advancements, Value Creation, Cross-border Expansion, Patent Expansions, Financial Performance Evaluation, Risk Mitigation, Licensing and Monetization, Efficiency Metrics

Date: November 2024

C-Reactive Protein Testing Manufacturers and Market Growth

The global C-reactive protein testing market size is calculated at USD 5.58 billion in 2024, grew to USD 5.6 billion in 2025, and is projected to reach around USD 5.75 billion by 2034. The market is expanding at a CAGR of 0.3% between 2024 and 2034.

C-Reactive Protein Testing Market Companies

Top Companies in the C-Reactive Protein Testing are:

  • Abbott Laboratories
  • Beckman Coulter
  • Boditech Med, Inc.
  • Danaher Corporation
  • F. Hoffman-La Roche
  • Horiba, Ltd.
  • LabCorp Holdings, Inc.
  • Merck
  • Ortho Clinical Diagnostics
  • Quest Diagnostics
  • Randox Laboratories
  • Siemens Healthcare Pvt. Ltd.
  • Thermo Fisher Scientific
  • Trinity Biotech
  • Zoetis

Latest Announcements by Industry Leaders

Dr. Paul M. Ridker, MD, Harvard Medical School, in an interview, highlighted the significance of the high-sensitivity CRP (hs-CRP) test as a risk marker for various forms of cardiovascular disease. He said that the increased levels of hs-CRP in healthy individuals are predictive of the future risk of a heart attack, stroke, sudden cardiac death, and peripheral arterial disease, even when the cholesterol levels are low.

Recent Developments in the C-Reactive Protein Testing Market

  • In August 2024, researchers from the Institute of Physical Chemistry, Polish Academy of Sciences developed a novel diagnostic tool using simple electrochemical biosensors with near-field communication technology embedded in a microfluidic device to measure CRP levels precisely.
  • In August 2024, research published in Scientific Reports journal presented a binary biophotonic sensor designed for the rapid and sensitive detection of CRP in human urine. The sensor was based on advanced optical fiber technology with machine learning algorithms to enhance the efficiency and accuracy of the test.

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