1. Quality by Design
Bhaswat Chakraborty, PhD
Senior VP & Chair, R&D Core Committee
Cadila Pharmaceuticals Ltd, Ahmedabad
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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.
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3. Innovative Problem Solving
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4. 4

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.
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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
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7. Application of QbD to Pharma R&D and
Manufacturing
 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 effective
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8. State of Pharmaceutical
Manufacturing
 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 fragmented
8 Source: Winkle H, US FDA

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.
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10. Overview of Pharmaceutical
QbD..
 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. Overview of QbD
11 Lionberger et al. (2008). AAPS J. 10: 268–276.

12. Relationship of Process and Material
Characteristics 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. Identification of Critical Process Parameters
and Critical Material Attributes
13 Lionberger et al. (2008). AAPS J. 10: 268–276.

14. Process Parameters and Material
Attributes Prior to Pharmaceutical
Development
 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.
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15. Classification of Process
Parameters
A parameter is critical when a realistic change in that
parameter can cause the product to fail to meet the TPQP
Thus, whether a parameter is critical or not depends on how
large of a change one is willing to consider
15 Lionberger et al. (2008). AAPS J. 10: 268–276.

16. [Non]-Uniqueness of Critical Process
Parameters
 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
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17. Process Parameters and Material Attributes
Prior to Pharmaceutical Development
17 Lionberger et al. (2008). AAPS J. 10: 268–276.

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.
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19. Control Strategy for Pre-QbD
Process
19 Lionberger et al. (2008). AAPS J. 10: 268–276.

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
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21. An Example of Control Strategy
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22. Impact of Classification of Process
Parameters
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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
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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
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25. Case Study: US FDA’s QbD for
MR Products
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26. Initial Risk Assessment of the Drug
Product 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.
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27. Initial Risk Assessment of the Drug
Product 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.
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28. Initial Risk Assessment
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Source: US FDA Guidance

29. Updated Risk Assessment of the Drug
Product 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.
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30. Updated Risk Assessment
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Source: US FDA Guidance

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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
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experimental designs

33. Thank You Very Much