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The antimicrobial susceptibility testing (AST) market is poised for significant growth from 2022 to 2028, driven by the rising prevalence of infectious diseases, increased antimicrobial resistance (AMR), and a growing demand for advanced diagnostic tools. AST plays a vital role in determining the effectiveness of antibiotics against microorganisms, assisting healthcare professionals in selecting the most appropriate treatment for bacterial infections.

Market Size

The Antimicrobial Susceptibility Testing Market was estimated at US$ 3.4 billion in 2021 and is expected to grow at a CAGR of 5.86% during 2022-2028 to reach US$ 6.28 billion in 2028.

Market Trends

The demand for rapid and accurate diagnostic tools has spurred technological advancements in AST. Automated systems, such as VITEK 2, Phoenix, and MicroScan, have gained popularity due to their ability to deliver faster results. Furthermore, the adoption of molecular diagnostic techniques, including polymerase chain reaction (PCR) and next-generation sequencing (NGS), is growing, offering quicker and more precise detection of microbial resistance patterns.

Another key trend is the integration of artificial intelligence (AI) and machine learning in AST, which enhances the analysis of large data sets and improves decision-making in clinical settings.

Competitive Landscape

Key players in the AST market include bioMérieux, Becton Dickinson, Thermo Fisher Scientific, Danaher Corporation, and Bio-Rad Laboratories. These companies are focusing on product innovation, mergers and acquisitions, and strategic partnerships to strengthen their market position.

Growth Opportunities

The rising burden of AMR worldwide presents significant growth opportunities for the AST market. Increased investments in research and development (R&D) and government initiatives aimed at combating AMR are expected to further propel market growth. Additionally, expanding healthcare infrastructure in emerging markets presents new avenues for AST adoption, offering immense growth potential during the forecast period.