New Delhi, Sept. 15, 2022 (GLOBE NEWSWIRE) -- The growing demand for process analytical technology market in the drug manufacturing industry is driving the development of new, innovative and reliable technologies. The key drivers of this trend are the rising costs of manufactured drugs and increased scrutiny from regulatory agencies. PAT plays an important role in ensuring the quality and safety of drug products. It is used to determine the purity, potency, identity and structure of drugs.
PAT also helps identify potential problems with drug manufacturing processes, such as contamination or foreign material. In a recent study in the global process analytical technology market, it was found that process analytical technology can identify contaminations present at levels as low as 0.1 parts per million. This could save significant amounts of time and money during production.
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Top 5 Players Hold Around 30% Share of Global Process Analytical Technology Market
As per Astute Analytica, Agilent Technologies, Inc. (U.S.), Thermo Fisher Scientific, Inc. (U.S.), Danaher Corporation (U.S.), PerkinElmer, Inc. (U.S.)., and Bruker Corporation (U.S.), ABB Ltd, and Shimadzu Corporation are some of the players in the global process analytical technology market. Wherein, the top 5 players held around 30% share of the global market in 2021.
These companies are focused on developing innovative technologies that primarily improve the quality assurance and diagnostic processes of the pharmaceutical industry. Some of the key products offered by these companies include biochemical analysis tools, flow cytometry instruments, and mass spectrometers.
One of the leading providers in the global process analytical technology market is Thermo Fisher. It offers a range of solutions that include liquids chromatography-mass spectrometry (LC-MS), gas chromatography-tandem mass spectrometry (GC-MS/MS), optical detection and nuclear magnetic resonance (NMR). The company is known to offers absolute confirmation of product quality and help manufacturers avoid expensive recalls.
As per Astute Analytica, one of the primary ways that players are advancing their technology is by acquiring new patents. Many big names in the industry have secured patents on various processes and technologies, which gives them a competitive advantage. For smaller companies in the process analytical technology market, this can be a major challenge, as it requires a significant investment in research and development to stay ahead of the curve. However, some startups have been able to innovate more quickly by relying on Patents from other industries.
Other methods that players are using to improve their products include acquisitions and partnerships. Some large companies have been willing to pay large sums of money for smaller firms with promising technology, while others have formed partnerships with other companies in order to collaborate on projects. For instance, in March 2022, Danhar acquired biopharma business of GE Healthcare. Moreover, in March 2022, Thermo Fisher acquired Max Analytical Technologies. This type of teamwork can be essential for innovation, as it allows different parts of the company to share their expertise and allow for faster progress.
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AI to Revolutionize the Process Analytical Technology in Pharmaceutical Manufacturing
Process analytical technologies (PAT) play an important role in the pharmaceutical manufacturing process by providing data that support decision making, quality control, and product development and manufacturing implementation. In recent years, Astute Analytica has observed that artificial intelligence (AI) has been increasingly used in PAT to improve the accuracy, speed, and efficiency of data analysis.
There are various types of AI including rule-based AI, pattern recognition AI, natural language processing AI, and machine learning AI in the process analytical technology market. Some common applications of these types of AI in PAT include intelligent sensor fusion, traceability analysis, predictive maintenance planning and execution, synthetic biology research, and efficacy prediction.
Some of the most popular applications of AI in PAT include Machine Learning for Inspection (MLI), Process Identification (PI), and Process Optimization (PO). MLI is a technique used to identify problems with a production process using data streaming. PI uses regression analysis to identify the cause of failures and then develops corrective action plans. PO helps manufacturers optimize their processes by identifying bottlenecks and mapping out the necessary changes to improve overall plant performance.
AI is also being used to create predictive models for new products. Predictive modeling is a method used to develop models that can predict future events or behaviors. This allows manufacturers in the process analytical technology market to test different product formulations before finalizing them for production. AI is also being used to measure how human observers would perform on inspection tasks.
Top Trends in Global Process Analytical Technology Market
As the pharmaceutical industry moves from discovery to development and eventually to marketing of new drugs, there is constant pressure on researchers and manufacturers alike to shorten the time it takes to get a product to patients. This pressure has led drug manufacturers and researchers alike to explore new ways to improve drug process timing. In this article, we take a look at some of the top trends in drug process analytical technology.
- Focus on Robust Automation: As the pace of drug development increases, so too does the need for quick and accurate results. This necessitates the use of robust automation in drug process laboratories. The use of robotics, manufacturing automations, and data analytics helps speed up and improve sample processing, assay generation, and MAID operations, which is expected to boost the growth of process analytical technology market.
- Transformation to Lab-on-Demand: For many companies, turning their discovery labs into production Lines isn't an option due to space constraints or regulatory limitations. Instead, they turn to services that provide dedicated lab space on-demand – often referred to as Lab-on-Demand (LOD). LOD solutions allow companies to outsource all or part of their R&D pipeline including chemical synthesis, purification, characterization, and sample testing, among others.
- Precision Medicine: As technologies continue to improve, it is becoming possible to provide more targeted treatments for patients. This precision medicine approach relies on using drug process analytical data to identify patient profiles and predict how they will respond to various treatments. By understanding how a drug impacts different populations, manufacturers can develop better drugs.
Top Players in Global Process Analytical Technology Market
- ABB Limited
- Agilent Technologies Inc.
- Agilent Technologies Inc.
- Bruker Corporation
- Carl Zeiss AG
- Danaher Corporation
- Emerson Electric Co.
- Mettler-Toledo International Inc.
- PerkinElmer Inc.
- Sartorius AG
- Shimadzu Corporation
- Statgraphics Technologies Inc
- Thermo Fisher Scientific Inc.
- Other Prominent Players
Global Process Analytical Technology Market Scope
| Report Attribute | Details |
| Market Size Value in 2021 | US$ 2,638.9 Million |
| Market Outlook for 2030 | US$ 7828.0 Million |
| Expected CAGR Growth | 13.2% |
| Historic Data | 2017-2020 |
| Base Year | 2021 |
| Forecast Period | 2022-2030 |
| Companies Profiled | ABB Limited , Agilent Technologies Inc., Agilent Technologies Inc., Bruker Corporation, Carl Zeiss AG, Danaher Corporation, Emerson Electric Co., Mettler-Toledo International Inc., PerkinElmer Inc., Sartorius AG, Shimadzu Corporation, Statgraphics Technologies Inc, Thermo Fisher Scientific Inc., Other Prominent Players |
| Segments Covered | By Offering, By Measurement, By Technique, By Applications, By End-User, By Region |
| Geographies Covered | North America, Europe, Asia Pacific, South America, Middle East and Africa |
| Customization Options | Get your customized report as per your preference. Ask for customization |
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