Aiming to get Zero Defect: PROCESS ANALYTICAL TECHNOLOGY

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Introduction:
Process Analytical Technology (PAT) is defined by the USFDA as “a system for designing, analyzing and controlling manufacturing through timely measurements (i.e. during processing) of critical quality and performance attributes of raw and inprocess
materials and processes with the goal of ensuring final product quality.” Advances in analytical technology provide the opportunity to develop a “total quality management
system (TQMS)” for the implementation of PAT in a working manufacturing facility. TQMS has the potential to provide significant improvements in product quality and manufacturing efficiency.
Now-a-days pharmaceutical manufacturers are taking a closer look at how they can continue to produce the highest quality products and at the same time generate profit. For this aspect, pharmaceutical industry as a whole - with encouragement from the USFDA - is seeking to accelerate the pace of manufacturing innovation to meet ever increasing cost, efficiency and time-to-market demands Thus, PAT is a new USFDA initiative that aims to faster improvements in manufacturing efficiency and product quality while creating a harmonization of regulatory expectations.
What is PAT?
PAT is a system for designing, analyzing and controlling manufacturing processes based on two important things:
Ü An understanding of the scientific and engineering principles involved, and
Ü Identification of the variables which affect product quality.
PAT initiative is consistent with the current USFDA belief that quality cannot be tested into products, but should be built-in or by design. But currently, quality is built into pharmaceutical products through a comprehensive understanding of: & Intended therapeutic objectives; patient population; route of administration; and pharmacological, toxicological, and pharmacokinetic characteristics of a drug. & chemical, physical and biopharmaceutical characteristics of a drug. & Selection of product components and packaging based on drug attributes listed above. Design of manufacturing processes using principles of engineering, material science and quality assurance to ensure acceptable and reproducible product quality and performance throughout product’s shelf life. PAT keeps on working to design and develop processes that can consistently ensure a pre-defined quality at the end of the manufacturing process. Such procedures would be consistent with the basic tenet of quality by design and could reduce risks to quality and
regulatory concerns while improving efficiency. USFDA also states that PAT involves optimal application of process analytical chemistry (PAC) tools, feedback process-control strategies, and information management tools and/or product-process optimization strategies for the manufacture of pharmaceuticals.
Goals of PAT:
The primary goal of PAT is to provide processes which consistently generate products of pre-determined quality. In doing so, improved quality and efficiency are expected from lower costs; reduction of cycle times using on-, in-, or at-line measurements and controls;
prevention of reject product and waste; real time product release; increased use of automation; facilitation of continuous processing using small-scale equipment, resulting in improved energy and material use and increased capacity; using small-scale equipment (to eliminate certain scale-up issues) and dedicated manufacturing facilities; improving energy and material use and increasing capacity; increased efficiency and batch-to-batch consistency; and process finger-printing (signature) that would be useful for validation, scale-up, and confirming acceptable handling of changes.
Different Principles and Tools for PAT:
PAT focusses on the principles of building quality into the product and process as well as continuous process improvement. A few examples of PAT tools and strategies are collected as follows:
PAC
According to Hailey et al., PAC is the technique of “gathering analytical information in real time at the point of manufacture”. Although, the approaches and instrumentation currently being discussed are in some cases categorized as being novel or new, real-time
measurement has existed for some time (e.g. real-time temperature monitoring of reaction vessels during the synthesis of active pharmaceutical ingredients). One particular industry-university partnership, the Center for PAC (C-PAC) at the University of Washington, has been in existence since 1986.
Chemometrics and principle component analysis
In 1974, Sante Wold from the Institute of Chemistry at Umea University (Umea, Sweden) described “the art of extracting chemically relevant information from data provided in chemical experiments” as chemometrics. In 1996, Wise and Gallagher stated chemometrics as “the science of relating measurements made on a chemical system to the state of the system via application of mathematical or statistical methods.” Similarly, Hardy noted that data are “raw information, both qualitative and quantitative.” Principle Component Analysis (PCA) is a technique used to express variations of many variables by a small number of indices. Wise and Gallagher described PCA as a favorite tool of chemometricians for data compression and information extraction and noted that “PCA finds combinations of variables or factors that describe major trends in a data set.” Wise and Gallagher studied data obtained from a slurry-fed ceramic reactor using thermocouples placed at 20locations. They found a great deal of correlation as the data generated followed a saw-tooth pattern. In addition, the study revealed the following:
• PCA performed on this data found three factors that captured approximately 97% of the variance in the data set.
• This previously noted finding allowed 16 variables to be replaced with three new ones, which were linear combinations of the original variables.
• Saw-tooth pattern was attributed to changes in the level of molten glass, which was a controlled variable.
• Three factors (PCs) were identified as the level of molten glass in the reactor, the variation between two groups of measured locations, and the variation of overall process temperature (also a controlled variable). An analog of PCA is what is known as Multi-way PCA (M-PCA), which is “equivalent to performing PCA on a very large two-dimensional matrix formed by unfolding the three-way array X into one of six possible ways, only three of which are mathematically unique.”
Process analytical monitoring at-on-in
Process analytical monitoring (PAM) can be taken one of three ways: at-line, where the sample is removed and analyzed close to the process stream; on-line, where the sample is diverted from the manufacturing process to an analyzer and possibly returned to the stream; and in-line, an invasive or non-invasive process that analyzes the sample while it’s part of the process stream.
Quality counts
The last few years has seen the USFDA steer industry further in the direction of a quality-by-design (QbD) approach, and away from the quality-by-testing (QbT) approach traditionally taken by the pharma sector. Both QbD and QbT are fundamentally different to one another, and there are good reasons for the emerging focus on QbD. The traditional QbT approach is wasteful and inefficient, and some have been critical of the approach for failing to evaluate the quality of the product until it has already been produced. “The basis of QbT is that the finished product is tested for quality.” But “the basis of QbD is that the product is tested for quality before finished.”
Near Infra Red Spectroscopy in PAT:
After gaining a wide acceptance in agricultural, food, and petrochemical industries as a powerful analytical technique, recently Near Infra Red (NIR) spectroscopy has found increasing use in pharma analysis for identification and quality testing of raw materials, monitoring of blending, granulation, roller compaction, drying operations, and many other applications. One of the most promising pharma applications of NIR spectroscopy is the analysis of solid oral-dosage forms. NIR spectra are rich in chemical and physical information. When used in conjunction with appropriate chemometric modeling techniques (multivariate analyses) NIR spectroscopy can be used to measure a variety of tablet properties. NIR is effective in transmission or reflection modes as a non-invasive and non-destructive technique for the simultaneous measurement of a variety of tablet properties. Achieving PAT principles identified by the USFDA, such as process understanding and real-time releases, require a change in technology and techniques currently employed in many pharmaceutical operations.
The real path to execute PAT is as follows:
• Identify the process which we have to measure.
• Select the exact critical process parameter (CPP) for that process.
• Search the place from where we have to measure the CPP like at/on/in-line.
• Calculate the real time to collect the data.
• Find out the analytical procedure to analyze the data.
• Achieve a product with maximum efficiency and zero defect.
Conclusion:
Conventional pharmaceutical manufacturing is generally accomplished using batch processing with laboratory testing conducted on collected samples to ensure quality. This conventional approach has been successful in providing quality pharmaceuticals to the public in its way. But, now pharmaceutical manufacturing will need to employ innovation, cutting edge scientific and engineering knowledge, along with the best principles of quality management to respond to the challenges of new discoveries (e.g. novel drugs and nanotechnology) and ways of doing business (e.g. individualized therapy, genetically tailored treatment). Pharmaceutical manufacturing continues to evolve with increased emphasis on science and engineering principles. Effective use of the most current pharmaceutical science and engineering principles and knowledge - throughout the life cycle of a product - can improve the efficiencies of both the manufacturing and regulatory processes. For this, it is very much essential to adopt PAT and its implementation will definitely bring real-life benefits and improvements to many pharmaceutical processes, which will give a “Zero Defect” pharma product with more efficacies.
References:
1. CDER, Office of Pharmaceutical Sciences, “Process and Analytical Technologies Initiative,” http://www.fda.gov/cder/OPS/ PAT.htm.
2. A. Hussain and J. Famulare, “FDA’s PAT Initiative and its Role in the Proposed Drug Quality System for the 21st Century,” presented at the AAPS Arden House Conference, 27 January 2003.
3. T. Layloff, “PAT Subcommittee Report,” presented at the ACPS meeting 21 October 2002.
4. FDA, “Pharmaceutical cGMPs for the 21st Century: A Risk- Based Approach,” http://www.fda.gov/cder/gmp/index. htm
5. P. Hailey et al., “Automated System for the Online Monitoring of Powder Blending Processes Using Near-Infrared Spectroscopy Part I. System Development and Control,” J. Pharma. Biomed.Analysis, 14, 551-559 (1996).
6. D. Illman, “CPAC: An Industry-University Cooperative Research Center for Process Analytical Chemistry,” TrAC: Trends in Analytical Chemistry 5 (7), 164-172 (1986).
7. S. Wold, “Chemometrics: What do we mean with it and What do we want from it?” presented at InCINC ‘94, Institute of Chemistry, Umea University (Umea, Sweden, 1994).
8. B. Wise and N. Gallager, “The Process Chemometrics Approach to Process Monitoring and Fault Inspection,” J. Proc. Ctrl. 6 (6), 329-348 (1996).
9. J. Hardy, “Special Topics: Chemometrics,” lecture presentation associated with 3150: 710 (University of Akron, 2000), available at http://ull.chemistry.uakron.edu/chemometrics/ introduction
10. FDA, “Emerging Issues in Pharmaceutical Manufacturing: Process Analytical Technology,” science board meeting presentation (16 November 2001).
11. N. Sugakkai, “Iwanami Sugaku Ziten,” original publication by Iwanami Shoten Publishers (Tokyo, Japan, 1954), copyright by Nihon Sugakkai (Mathematics Society of Japan); English translation provided by the Massachusetts Institute of Technology
(1977).
12. D. Sans, R. Nomen, and J. Sempere, “Interactive Self- Modelling of Chemical Reaction System Using Multivariate Data Analysis,” supplement to Comput. Chem. Eng. 21, S631-S636 (1997).
13. W. Wu et al., “The Star-Plot: an Alternative Display Method for Multivariate Data in the Analysis of Food and Drugs,” J.Pharma. Biomed. Analysis, 17 (6-7), 1001-1013 (September 1998).
14. P. Nomikos and J. MacGregor, “Multiway Partial Least Squares in Monitoring Batch Processes,” Chemometrics and Intelligent Laboratory Systems 30, 97-108 (1995).
15. FDA Global Harmonization Task Force Study Group #3, Draft Process Validation Guidance, 1 June 1998.
16. PAT Tool box, Pharmaceutical Process Control gets inline, by Thomas E. Persons, Sr. President and CEO of South Carolina Tech Alliance (Columbia, S.C).
17. FDA Advisory Committee for Pharmaceutical Science transcripts, 23 October 2002.
18. PAT Initiative Expected to Invigorate Pharmaceutical Industry with Improved Quality, Better Efficiency and Improved Profits. White Paper, Nov 2004.
19. Guidance for Industry PAT-A Framework for Innovative Pharmaceutical Manufacturing and Quality Assurance, http://www.fda.gov/cder/OPS/PAT.htm, September 2, 2003.
20. Quality counts by Ali M. Afnan of the FDA and OPS, 2005.
21. Pharma’s process analytical technology, Today’s analytical chemists in the pharmaceutical industry are trading lab coats for hard hats, Corrinne A, Career and employment, February 21, 2005 Volume 83, Number 8 pp. 201, 204, 206.

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