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Quality by design approach in drying process organization
19th European Symposium on Computer Aided Process Engineering – ESCAPE19 J. JeĪowski and J. Thullie (Editors) © 2009 Elsevier B.V. All rights reserved.
291
Quality by design approach in drying process organization a
a
a
Alexander Troyankin, Anton Kozlov, Alexander Voynovskiy, Natalia Menshutina a a
Mendeleyev University of Chemical-Technology of Russia, High technology department, 125047, Miusskaya sq. 9, Moscow, Russia, [email protected]
Abstract With the rapid implementation of the PAT initiatives, the role of quality control systems in pharmaceutics is going to be extremely important. The operation of such systems is closely connected with the use of various mathematical methods and information technologies directed to the achievement and maintaining required quality at every step of the production process and therefore guarantee the quality of final product. This forms a base for quality by design approach in process organization. This paper presents an approach to process organization using PAT and design of information system that can be capable to use and process data from different production levels and therefore provide production process monitoring and control. Three technological processes, with drying stage included (freeze-drying, granulation, coating) is taken as an example of the described approach application. Keywords: PAT, quality management, drying, pharmaceutics 1. Introduction Nowadays there is a great need in implementation of new innovative power saving, environmental-friendly technologies. Growth of production rates and energy consumption, high costs of raw materials, environmental pollution – all these factors force us to make efforts to the development of new green technologies and to the optimization of the current ones. Pharmaceutics always pays great attention to product quality. It is the key factor and all steps of the process should serve to provide required quality of the final product. Such shift in ideology happened when GMP were implemented in the US and Europe. Similar process is now observed in Russia. In comparison with microelectronics where the percentage of waste product is very low this value in pharmaceutical industry is relatively high and every year companies waste huge amount of money. That is why a quality management nowadays becomes a more and more important question. Organization and control of any quality management systems is closely connected to information technologies.
292
A. Troyankin et al.
IT and Quality management
Among all quality management systems three major levels of them can be discerned (See Fig. 1): ERP (Enterprise Resource planning) – manufacture level; LIMS (Laboratory Information Management System) – laboratory level; PAT (Process analytical technology) – process level. Each level is separated and can be represented by several modules, or a whole system.
Fig 1. Quality management information systems
ERP systems attempt to integrate several data sources and processes of an organization into a unified system. A typical ERP system will use multiple components of computer software and hardware to achieve the integration. A key ingredient of most ERP systems is the use of a unified database to store data for the various system modules. LIMS is computer software that is used in the laboratory for the management of samples, laboratory users, instruments, standards and other laboratory functions such as invoicing, plate management, and workflow automation. LIMS connects laboratory with other enterprise control systems, it increases data processing and research work automation. Process analytical technology is considered to be a system for designing, analyzing and controlling manufacturing through timely measurements of critical quality and performance attributes of raw and in-process materials and processes, with the goal of ensuring final product quality [1]. 2. PAT and Quality by design PAT ideology implies product quality to be considered from the very beginning in process design and optimization. In other words, the process needs to be designed and optimized taking into account continuous quality control.
Quality by Design Approach in Drying Process Organization
293
Offline process monitoring
Raw material
Mixing, Preparation
Drying
Packing
Quality assessment at the end of each stage
Fig 2. Offline quality control
For example, classic approach (See Fig. 2) to the production process organization (e.g. drying) implies offline (after the end of the stage) quality measurements. In case of any mistakes or deviations happened during processing on intermediate stages, it can results in non-quality or waste product. One of the aspects of PAT is Continuous quality assurance. System monitoring and control is being carried out in real-time (See Fig. 3) using noninvasive and indirect analysis technologies. On-line and in-line process monitoring Quality management as control element
Raw material
Mixing, Preparation
Drying
Packing
On-line quality assessment
Fig 3. Continuous quality control
All product characteristics measurements and investigations are carried out inline and on-line. Process control should be oriented to the providing stable and continuous quality of the final product. Quality control should be real-time organized and be based on dynamic quality characteristics measurements. Modern analytical equipment makes possible to collect and process huge amount of data real-time. Information technologies help to integrate gathered information and by means of modern computers and software, it is possible to apply complicated mathematical methods to analyze it. One of the relatively new and remarkable methods for process control is Multivariate Statistical Process Control (MSPC). MSPC can be defined as a set of modern mathematical and stochastical methods, algorithms for process control and optimization. Among these methods are Factor analysis (Principal Component Analysis, Partial Least Squares), process modeling (Multivariate Curve Resolution, Process Simulation), Classification methods (PLS-Discrimination, Soft Independent Modeling of Class Analogy, Hierarchical Cluster Analysis) etc. For the application of the MSPC detailed investigation of the technological process is needed. During this investigation process parameters and quality factors should be defined. Process conditions are represented as a set of parameters that can be changeable. These parameters are also particular for each type of process (drying, granulation, coating etc.) Number of them can be varied, but it is necessary to choose parameters that have influence on the product quality. Sometimes an additional task is to investigate which process conditions are vital and should be taken into account, and which are not important and can be ignored.
A. Troyankin et al.
294
The description of product quality can be done by means of quality factors, which are particular for each product (e.g. moisture content, color, density etc). All factors should be measurable and full set of them should describe product quality to a certain extent. One main quality factor can be defined, which is the most important for particular product, other factors can be ranged according to their importance or they can be equally important. After quality factors or attributes and process parameters are chosen and defined, next step is establishing a link between process parameters and product quality. Knowing these links it is possible to control or predict the quality of final product by changing process conditions and maintaining them in proper limits. This links can be established by means of various mathematical methods. This makes possible to search for alternatives that can provide required values of quality factors and therefore provide the quality product. However, the investigation of dependence between quality factors (initial raw material and final product) and process conditions can be very expensive and sometimes is not possible. Analysis of correlations of all parameters and factors is very complicated because of high dimensionality. This problem can be solved using multivariate calibration method. Data reduction (compression) and dimensionality decrease is possible by using latent projections. Now it is clear that designing the production line it is very important to pay attention and provide following facilities: facilities for monitoring of observed technological parameters; facilities for monitoring and control of adjustable technological parameters; facilities for complex and noninvasive analysis such as NIR spectroscopy. Some features of PAT Quality by Design (QbD) approach are shown in Fig. 4. Noninvasive analysis technologies
Design PAT (QbD)
Indirect measurements
Optimization Multivariate statistical process control (MSPC)
NIR / XFR / FBRM ... Calibration and quality factors assessment
Prediction and calculation of technological parameters
Fig 4. Features of PAT QbD approach
It should be noted that to provide stable product quality and to increase process efficiency data analysis from three major production levels is required. That can be possible if information systems at Manufacture level (ERP), Laboratory level (LIMS) and Process level (PAT) will be integrated and into connected. This makes a base for computer system design that is capable to use and process data from different production levels and therefore provide whole production process monitoring and control.
Quality by Design Approach in Drying Process Organization
295
3. System design and practical application Described approach to PAT Quality by design was applied to three apparatus and three processes: freeze-drying, encapsulation, coating. Each process included drying stage that is why we focused on it as an example of our approach application. Freeze-drying was carried out in special atmospheric fluid bed freeze dryer with active hydrodynamics [2], Granulation and Encapsulation processes in Huttlin Mycrolab and Mini-Glatt. As mentioned before the analysis of the process includes the definition of technological process parameters and quality factors. Gathered data is represented in Table 1. Technological parameters obtained directly from the installed equipment. Information about quality of the product comes from the analytical equipment in real-time. For discussed case special software that is integrated with process monitoring and control systems, and provides real-time quality-based processing is being developed. One-wire technology form Dallas Semiconductor, built-in equipment facilities and additional analytical equipment were used. Table 1. Process properties
Process parameters Freeze drying Air flow , Moisture content, Air temperature, Concentration and quantity of the dried product Granulation (inc. drying) Air flow, Air temperature, Dispersed liquid flow, Concentration, Microclimate pressure, Distance between nozzle and the bed Coating (inc. drying) Air flow, Air temperature, Dispersed liquid flow, Concentration, Microclimate pressure, Distance between nozzle and the bed
Quality factors Weight, Identity of the composition, Moisture Weight, Identity of the composition, Particle size
Identity of the composition, Particle size
The idea is that it is capable to monitor any deviation of critical process parameters during technological process, analyze the occurred deviation and decide if it is necessary and how to adjust the process by changing proper process parameters. So that in relatively short time the process is returned to its normal state. This allows avoiding the loss of the quality on intermediate steps and during the whole process. Described approach makes possible to create the structure of the QC Information system for pharmaceutical industry, it can be used in adaptation of the existed equipment layout, and using supposed methods of analysis and control, it is possible to implement online quality control [3]. An approach to design of such Information systems that can be capable to process and unite data from different production levels is shown in Fig. 5. This can be the base for creation knowledge base systems containing particular cases and patterns of behavior. Application of such systems can help to reduce the costs of new process and product development.
A. Troyankin et al.
296
Data acquisition from different production levels
Manufacturing level
ERP
Workflow, Input control
Laboratory level
LIMS
Results of laboratory tests
Process level
PAT
Quality by Design Continuous quality assurance
Data acquisition cycle
Data analysis cycle Process control level
Quality factors assessment
MSPC
Calibration of process parameters Prediction of process parameters values
Fig 5. General scheme of design integrated quality management intellectual system
The implementation of described tools and methods for quality management in a production scale is closely dependent on scientific research and experimental work, and thus is relatively complicated and expensive. However, it is clear that quality by design ideology is a way to provide stable quality, minimum waste product, so that the return of investment is very clear. References [1] U.S. FDA, Guidance for Industry. PAT - A Framework for Innovative Pharmaceutical Development, Manufacturing, and Quality Assurance, (2004), http://www.fda.gov/cder/guidance/6419fnl.htm [2] Menshutina N., Korneeva A., Goncharova S. and H. Leuenberger, Modeling of freeze drying in fluidized bed, Proceedings of the 14th International Drying Symposium, Sao Paolo, Brazil, 22-25 August, vol. A, (2004) pp. 680-686 [3] Degtyarev E.V., Pharmaceutical drug analysis in production and quality management, Russian Chemical Society magazine, vol. 46(4), (2002), pp. 46-51
291
Quality by design approach in drying process organization a
a
a
Alexander Troyankin, Anton Kozlov, Alexander Voynovskiy, Natalia Menshutina a a
Mendeleyev University of Chemical-Technology of Russia, High technology department, 125047, Miusskaya sq. 9, Moscow, Russia, [email protected]
Abstract With the rapid implementation of the PAT initiatives, the role of quality control systems in pharmaceutics is going to be extremely important. The operation of such systems is closely connected with the use of various mathematical methods and information technologies directed to the achievement and maintaining required quality at every step of the production process and therefore guarantee the quality of final product. This forms a base for quality by design approach in process organization. This paper presents an approach to process organization using PAT and design of information system that can be capable to use and process data from different production levels and therefore provide production process monitoring and control. Three technological processes, with drying stage included (freeze-drying, granulation, coating) is taken as an example of the described approach application. Keywords: PAT, quality management, drying, pharmaceutics 1. Introduction Nowadays there is a great need in implementation of new innovative power saving, environmental-friendly technologies. Growth of production rates and energy consumption, high costs of raw materials, environmental pollution – all these factors force us to make efforts to the development of new green technologies and to the optimization of the current ones. Pharmaceutics always pays great attention to product quality. It is the key factor and all steps of the process should serve to provide required quality of the final product. Such shift in ideology happened when GMP were implemented in the US and Europe. Similar process is now observed in Russia. In comparison with microelectronics where the percentage of waste product is very low this value in pharmaceutical industry is relatively high and every year companies waste huge amount of money. That is why a quality management nowadays becomes a more and more important question. Organization and control of any quality management systems is closely connected to information technologies.
292
A. Troyankin et al.
IT and Quality management
Among all quality management systems three major levels of them can be discerned (See Fig. 1): ERP (Enterprise Resource planning) – manufacture level; LIMS (Laboratory Information Management System) – laboratory level; PAT (Process analytical technology) – process level. Each level is separated and can be represented by several modules, or a whole system.
Fig 1. Quality management information systems
ERP systems attempt to integrate several data sources and processes of an organization into a unified system. A typical ERP system will use multiple components of computer software and hardware to achieve the integration. A key ingredient of most ERP systems is the use of a unified database to store data for the various system modules. LIMS is computer software that is used in the laboratory for the management of samples, laboratory users, instruments, standards and other laboratory functions such as invoicing, plate management, and workflow automation. LIMS connects laboratory with other enterprise control systems, it increases data processing and research work automation. Process analytical technology is considered to be a system for designing, analyzing and controlling manufacturing through timely measurements of critical quality and performance attributes of raw and in-process materials and processes, with the goal of ensuring final product quality [1]. 2. PAT and Quality by design PAT ideology implies product quality to be considered from the very beginning in process design and optimization. In other words, the process needs to be designed and optimized taking into account continuous quality control.
Quality by Design Approach in Drying Process Organization
293
Offline process monitoring
Raw material
Mixing, Preparation
Drying
Packing
Quality assessment at the end of each stage
Fig 2. Offline quality control
For example, classic approach (See Fig. 2) to the production process organization (e.g. drying) implies offline (after the end of the stage) quality measurements. In case of any mistakes or deviations happened during processing on intermediate stages, it can results in non-quality or waste product. One of the aspects of PAT is Continuous quality assurance. System monitoring and control is being carried out in real-time (See Fig. 3) using noninvasive and indirect analysis technologies. On-line and in-line process monitoring Quality management as control element
Raw material
Mixing, Preparation
Drying
Packing
On-line quality assessment
Fig 3. Continuous quality control
All product characteristics measurements and investigations are carried out inline and on-line. Process control should be oriented to the providing stable and continuous quality of the final product. Quality control should be real-time organized and be based on dynamic quality characteristics measurements. Modern analytical equipment makes possible to collect and process huge amount of data real-time. Information technologies help to integrate gathered information and by means of modern computers and software, it is possible to apply complicated mathematical methods to analyze it. One of the relatively new and remarkable methods for process control is Multivariate Statistical Process Control (MSPC). MSPC can be defined as a set of modern mathematical and stochastical methods, algorithms for process control and optimization. Among these methods are Factor analysis (Principal Component Analysis, Partial Least Squares), process modeling (Multivariate Curve Resolution, Process Simulation), Classification methods (PLS-Discrimination, Soft Independent Modeling of Class Analogy, Hierarchical Cluster Analysis) etc. For the application of the MSPC detailed investigation of the technological process is needed. During this investigation process parameters and quality factors should be defined. Process conditions are represented as a set of parameters that can be changeable. These parameters are also particular for each type of process (drying, granulation, coating etc.) Number of them can be varied, but it is necessary to choose parameters that have influence on the product quality. Sometimes an additional task is to investigate which process conditions are vital and should be taken into account, and which are not important and can be ignored.
A. Troyankin et al.
294
The description of product quality can be done by means of quality factors, which are particular for each product (e.g. moisture content, color, density etc). All factors should be measurable and full set of them should describe product quality to a certain extent. One main quality factor can be defined, which is the most important for particular product, other factors can be ranged according to their importance or they can be equally important. After quality factors or attributes and process parameters are chosen and defined, next step is establishing a link between process parameters and product quality. Knowing these links it is possible to control or predict the quality of final product by changing process conditions and maintaining them in proper limits. This links can be established by means of various mathematical methods. This makes possible to search for alternatives that can provide required values of quality factors and therefore provide the quality product. However, the investigation of dependence between quality factors (initial raw material and final product) and process conditions can be very expensive and sometimes is not possible. Analysis of correlations of all parameters and factors is very complicated because of high dimensionality. This problem can be solved using multivariate calibration method. Data reduction (compression) and dimensionality decrease is possible by using latent projections. Now it is clear that designing the production line it is very important to pay attention and provide following facilities: facilities for monitoring of observed technological parameters; facilities for monitoring and control of adjustable technological parameters; facilities for complex and noninvasive analysis such as NIR spectroscopy. Some features of PAT Quality by Design (QbD) approach are shown in Fig. 4. Noninvasive analysis technologies
Design PAT (QbD)
Indirect measurements
Optimization Multivariate statistical process control (MSPC)
NIR / XFR / FBRM ... Calibration and quality factors assessment
Prediction and calculation of technological parameters
Fig 4. Features of PAT QbD approach
It should be noted that to provide stable product quality and to increase process efficiency data analysis from three major production levels is required. That can be possible if information systems at Manufacture level (ERP), Laboratory level (LIMS) and Process level (PAT) will be integrated and into connected. This makes a base for computer system design that is capable to use and process data from different production levels and therefore provide whole production process monitoring and control.
Quality by Design Approach in Drying Process Organization
295
3. System design and practical application Described approach to PAT Quality by design was applied to three apparatus and three processes: freeze-drying, encapsulation, coating. Each process included drying stage that is why we focused on it as an example of our approach application. Freeze-drying was carried out in special atmospheric fluid bed freeze dryer with active hydrodynamics [2], Granulation and Encapsulation processes in Huttlin Mycrolab and Mini-Glatt. As mentioned before the analysis of the process includes the definition of technological process parameters and quality factors. Gathered data is represented in Table 1. Technological parameters obtained directly from the installed equipment. Information about quality of the product comes from the analytical equipment in real-time. For discussed case special software that is integrated with process monitoring and control systems, and provides real-time quality-based processing is being developed. One-wire technology form Dallas Semiconductor, built-in equipment facilities and additional analytical equipment were used. Table 1. Process properties
Process parameters Freeze drying Air flow , Moisture content, Air temperature, Concentration and quantity of the dried product Granulation (inc. drying) Air flow, Air temperature, Dispersed liquid flow, Concentration, Microclimate pressure, Distance between nozzle and the bed Coating (inc. drying) Air flow, Air temperature, Dispersed liquid flow, Concentration, Microclimate pressure, Distance between nozzle and the bed
Quality factors Weight, Identity of the composition, Moisture Weight, Identity of the composition, Particle size
Identity of the composition, Particle size
The idea is that it is capable to monitor any deviation of critical process parameters during technological process, analyze the occurred deviation and decide if it is necessary and how to adjust the process by changing proper process parameters. So that in relatively short time the process is returned to its normal state. This allows avoiding the loss of the quality on intermediate steps and during the whole process. Described approach makes possible to create the structure of the QC Information system for pharmaceutical industry, it can be used in adaptation of the existed equipment layout, and using supposed methods of analysis and control, it is possible to implement online quality control [3]. An approach to design of such Information systems that can be capable to process and unite data from different production levels is shown in Fig. 5. This can be the base for creation knowledge base systems containing particular cases and patterns of behavior. Application of such systems can help to reduce the costs of new process and product development.
A. Troyankin et al.
296
Data acquisition from different production levels
Manufacturing level
ERP
Workflow, Input control
Laboratory level
LIMS
Results of laboratory tests
Process level
PAT
Quality by Design Continuous quality assurance
Data acquisition cycle
Data analysis cycle Process control level
Quality factors assessment
MSPC
Calibration of process parameters Prediction of process parameters values
Fig 5. General scheme of design integrated quality management intellectual system
The implementation of described tools and methods for quality management in a production scale is closely dependent on scientific research and experimental work, and thus is relatively complicated and expensive. However, it is clear that quality by design ideology is a way to provide stable quality, minimum waste product, so that the return of investment is very clear. References [1] U.S. FDA, Guidance for Industry. PAT - A Framework for Innovative Pharmaceutical Development, Manufacturing, and Quality Assurance, (2004), http://www.fda.gov/cder/guidance/6419fnl.htm [2] Menshutina N., Korneeva A., Goncharova S. and H. Leuenberger, Modeling of freeze drying in fluidized bed, Proceedings of the 14th International Drying Symposium, Sao Paolo, Brazil, 22-25 August, vol. A, (2004) pp. 680-686 [3] Degtyarev E.V., Pharmaceutical drug analysis in production and quality management, Russian Chemical Society magazine, vol. 46(4), (2002), pp. 46-51