Quality by Design

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  • definition of operating parameters depends on the engineering systems installed on a process equipment e.g., one fluid bed dryer may define the product temperature as an operating parameter and have a thermostat that maintains that temperature, while another fluid bed dryer may have inlet air flow rate and inlet air temperature indicated as operating parameters batch record for the first unit might indicate a fixed temperature, while the second unit would have a design space that indicated the combination of inlet air flow rate and inlet air temperature that would insure the appropriate product temperature
  • Quality by Design

    1. 1. Quality by Design Bhaswat Chakraborty, PhD Senior VP & Chair, R&D Core CommitteeCadila Pharmaceuticals Ltd, Ahmedabad1
    2. 2. Theory of Inventive Problem Solving• Systems engineering and some related fields formally identifies and solves problems • by appropriately resolving system tradeoffs or • effectively evaluating alternatives• Consequence of not proper resolution, • system performance is hindered, or • suboptimal technologies are chosen• Theory of Inventive Problem Solving, TRIZ, offers tools and methods to identify and resolve tradeoffs (which it terms contradictions or conflicts)• TRIZ recognizes that fundamental performance limits arise when one or more unresolved tradeoffs exist in a system • eliminating or reducing the effects of the conflicts is necessary to move to improved system performance • there are various levels of decomposition to compare options and optimize how the system performs. 2
    3. 3. Innovative Problem Solving3
    4. 4. 4
    5. 5. ARIZ 85C (version of 1985) ARIZ  is an algorithm designed by Genrich Altschuller to tackle more complicated problem. It combines the whole of TRIZ methodologies, techniques and databases. A very quick overview: 1. Quick analysis: Zoom in to the problem situation and formulate a mini-problem. Find the 2 technical contradictions, exaggerate their effects and convert your problem into a functional model. Compare this functional model with the 76 inventive standards. If it is not solved yet, proceed to step 2 2. Gather data: Zoom and lock to time (operational time) and space (operational zone), define the super- and subsystems and complete the list of substance field resources. 3. The bigger picture: Use the previously gathered data to derive the ideal final result and physical contradictions. Compared this new model with the 76 Inventive standards. Proceed to the next step if there is still no match 4. Scanning resources and elimination contradictions: use techniques like modeling with little dwarves, step back from ideal final result, challenge resources with substances and voids or use ways to eliminate physical contradictions (principles are at hand). The solution should be available now. If not, continue to step 5. 5. Refer to the TRIZ knowledge data base for similar problems previously dealt with. 6. Reformulate the problem if it is not solved by now, by returning to step 1 7. Feasibility: step 7 checks if the solution can indeed be implemented 8. Extraction: extract the solution in abstract form to implement it in the TRIZ database. 9. Compare you walked path to solution with ARIZ and upgrade missing links. 5
    6. 6. Quality by Design (QbD) Quality by Design (QbD) is a concept first outlined by well- known quality expert Joseph M. Juran Juran believed that quality could be planned, and that most quality crises and problems relate to the way in which quality was planned in the first place Juran’s Philosophy: Trilogy of planning, control, and improvement Proactive & risk based approach for predictable & predefined quality Planning quality into the process A leading indicator for better controls & to handle quality crises and problems early in the cycle 6
    7. 7. Application of QbD to Pharma R&D andManufacturing Motivation mainly comes from the fact that current product quality is not state-of-art and yet very expensive A target product profile can be constructed that describes the use, safety and efficacy of the product Critical process and material characteristics can be understood for the drug and the product Elements of QbD can be developed and examined Critical quality attributes, critical process parameters, critical material attributes and control strategies can be implemented batches after batches Applicable to generics and is cost effective7
    8. 8. State of PharmaceuticalManufacturing In many cases, not state-of-art as compared to other industries Able to achieve reasonable product quality – but at a great effort and cost Little emphasis on manufacturing –mainly on development although manufacturing is approximately 25% of expenses For some products, waste as high as 50% Inability to predict effects of scale up on final product Inability to analyze or understand reasons for manufacturing failures Globally fragmented8 Source: Winkle H, US FDA
    9. 9. Overview of Pharmaceutical QbD Begin with a target product profile that describes the use, safety and efficacy of the product Define a target product quality profile that will be used by formulators and process engineers as a quantitative surrogate for aspects of clinical safety and efficacy during product development Gather relevant prior knowledge about the drug substance, potential excipients and process operations into a knowledge space. Use risk assessment to prioritize knowledge gaps for further investigation Design a formulation and identify the critical material (quality) attributes of the final product that must be controlled to meet the target product quality profile Design a manufacturing process to produce a final product having these critical material attributes. 9
    10. 10. Overview of PharmaceuticalQbD.. Identify the critical process parameters and input (raw) material attributes that must be controlled to achieve these critical material attributes of the final product. Use risk assessment to prioritize process parameters and material attributes for experimental verification. Combine prior knowledge with experiments to establish a design space or other representation of process understanding. Establish a control strategy for the entire process that may include input material controls, process controls and monitors, design spaces around individual or multiple unit operations, and/or final product tests. The control strategy should encompass expected changes in scale and can be guided by a risk assessment. Continually monitor and update the process to assure consistent quality 10 Lionberger et al. (2008). AAPS J. 10: 268–276.
    11. 11. Overview of QbD11 Lionberger et al. (2008). AAPS J. 10: 268–276.
    12. 12. Relationship of Process and MaterialCharacteristics to TPQP and to TPP The Target Product Profile TPP provides an overall intent of the drug development program.  TPP is a patient and labeling centered concept, it can be thought of as the “user interface” of the drug product  TPP links drug development activities to specific concepts intended for inclusion in the drug labeling  attributes that are critical to the quality of the drug product, taking into consideration intended usage and route of administration The target product quality profile (TPQP) is a quantitative surrogate for aspects of clinical safety and efficacy that can be used to design and optimize a formulation and manufacturing process Critical quality attributes (CQAs) are physical, chemical, biological or microbiological properties or characteristics that should be within an appropriate limit, range, or distribution to ensure the desired product quality 12 Lionberger et al. (2008). AAPS J. 10: 268–276.
    13. 13. Identification of Critical Process Parametersand Critical Material Attributes13 Lionberger et al. (2008). AAPS J. 10: 268–276.
    14. 14. Process Parameters and MaterialAttributes Prior to PharmaceuticalDevelopment Critical process parameter (CPPs): the input operating parameters (mixing speed, flow rate) and process state variables (temperature, pressure) of a process or unit operation For a given unit operation, there are four categories of parameters and attributes  input material attributes  output material attributes  input operating parameters  output process state conditions the state of a process depends on its CPPs and the CMAs of the input materials  monitoring and controlling output material attributes can be a better control strategy than monitoring operating parameters especially for scale up  a material attribute, such as moisture content, should have the same target value in the pilot and commercial processes.  an operating parameter, such as air flow rate, would be expected to change as the process scale changes. 14
    15. 15. Classification of ProcessParameters A parameter is critical when a realistic change in thatparameter can cause the product to fail to meet the TPQP Thus, whether a parameter is critical or not depends on howlarge of a change one is willing to consider15 Lionberger et al. (2008). AAPS J. 10: 268–276.
    16. 16. [Non]-Uniqueness of Critical ProcessParameters Different sets of CPP can have several origins. 1. definition of operating parameters depends on the engineering systems installed on a process equipment  e.g., one fluid bed dryer may define the product temperature as an operating parameter (a thermostat maintaining that temp.) while another fluid bed dryer may have inlet air flow rate & inlet air temperature indicated as operating parameters  batch record for the first unit might indicate a fixed temperature, while the second unit would have a design space that indicated the combination of inlet air flow rate and inlet air temperature that would insure the appropriate product temperature 1. differences in the set of CPP comes from the balance between control of operating parameters and material attributes 2. in fact, a set of CPP and CMA (which he refers to as process critical control points (PCCP)) can affect the scale up process 16
    17. 17. Process Parameters and Material AttributesPrior to Pharmaceutical Development17 Lionberger et al. (2008). AAPS J. 10: 268–276.
    18. 18. Control Strategies A control strategy may include input material controls, process controls and monitoring, design spaces around individual or multiple unit operations, and/or final product specifications used to ensure consistent quality A sponsor uses to ensure consistent quality as they scale up their process from the exhibit batch presented in the ANDA to commercial production Every process has a control strategy right now Next slide shows a simplified QA diagram under the current regulatory evaluation system.  here, product quality is ensured by fixing the process to produce the active ingredient, raw material testing, performing the drug product manufacturing process as described in a fixed batch record, in- process material testing, and end product testing. 18
    19. 19. Control Strategy for Pre-QbDProcess19 Lionberger et al. (2008). AAPS J. 10: 268–276.
    20. 20. A QbD based Control Strategy Next slide shows a QbD based control strategy Here the quality is assured by understanding and controlling formulation and manufacturing variables to assure the quality of the finished product The end product testing only confirms the quality of the product. In this example, PAT provides tools for realizing the real time release of the finished product although its use is not required under the paradigm of the QbD The classification of process parameters as critical or non-critical is essential to evolve the control strategy toward the QbD based goal Full classification of all parameters as either non-critical or critical can lead to reduced end-product testing  it is the uncertainty about the uncclassified process parameters, UPP, that leads to extensive testing 20
    21. 21. An Example of Control Strategy21
    22. 22. Impact of Classification of ProcessParameters22
    23. 23. Design Space Design space is one approach to ensure product quality is not a check-box requirement.  especially in the presence of interacting critical process parameters  it is “The multidimensional combination and interaction of input variables (e.g., material attributes) and process parameters that have been demonstrated to provide assurance of quality.”  evolved from “the established range of process parameters that has been demonstrated to provide assurance of quality”  the change emphasizes the multidimensional interaction of input variables and closely binds the establishment of a design space to a conduct of a DOE that includes interactions among the input variables  a design space may be constructed for a single unit operation, multiple unit operations, or for the entire process 23
    24. 24. Design Space.. Identify the unclassified parameters and carry out a DOE on some of the unclassified parameters with the other unclassified parameters fixed The idea is to have some space for the selected parameters but no flexibility for the other parameters This operating parameter based design space is limited to the equipment used to develop the design space  might change on scale up or equipment changes In the development of a design space, the key issue to efficiency is demonstrating or establishing that the unclassified parameters left out of the DOE are truly non-critical process parameters  They are non-interacting  First reduce the number of unclassified process parameters.  Screen DOE to rule out significant interactions between process parameters.  Non-interacting univariates can be added to the design space without additional studies 24
    25. 25. Case Study: US FDA’s QbD for MR Products25
    26. 26. Initial Risk Assessment of the DrugProduct Manufacturing Process A risk assessment of the overall drug product manufacturing process is performed to identify the high risk steps that could affect the final drug product CQAs; for an MR product CQAs could be:  Physical attributes ((size and splitability)  Assay, content uniformity  Drug Release – whole tablets  Drug Release – split tablets  Drug Release – alcohol induced dose dumping Subsequently, intermediate CQAs that are directly linked to the identified final drug product CQAs were identified The process variables that could impact the intermediate CQAs become the focus of the risk assessment of variables that have the highest potential to cause a CQA failure. 26
    27. 27. Initial Risk Assessment of the DrugProduct Manufacturing Process.. These variables are then investigated in order to optimize the drug product manufacturing process and reduce the risk of failure.  E.g., the overall risk assessment of the manufacturing process found assay of the tablets to be at high risk of failure due to the drug layering step  Subsequently, assay of the layered beads is directly linked to final tablet assay and was identified as the CQA of the drug- layered beads.  Process variables that could directly impact the assay of the drug-layered beads were assessed to identify which of the variables could have the highest potential to cause a bead assay failure.27
    28. 28. Initial Risk Assessment28 Source: US FDA Guidance
    29. 29. Updated Risk Assessment of the DrugProduct Manufacturing Process During process development, high risks for each unit operation were addressed. Experimental studies were defined and executed in order to establish additional scientific knowledge and understanding, to allow appropriate controls to be developed and implemented, and to reduce the risk to an acceptable level. After detailed experimentation, the initial manufacturing process risk assessment was updated in-line with the current process understanding.29
    30. 30. Updated Risk Assessment30 Source: US FDA Guidance
    31. 31. 31
    32. 32. Conclusions Quality by design is an essential part of the modern approach to pharmaceutical quality Usefulness of QbD include the importance of the Target Product Quality Profile as a quantitative performance target for QbD Critical material attributes provide a mechanistic link of the product quality to the manufacturing process Critical process parameters are operating parameters and should be combined with critical material attributes to describe the relation between unit operation inputs and outputs Non-critical, unclassified, and critical process parameters provide a true understanding of in-process quality Control strategy serves as a mechanism for incremental implementation of QbD elements into practice QbD also provides for a design space through the identification of non-interacting process variables and their exclusion from formal 32 experimental designs
    33. 33. Thank You Very Much

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