The Forgotten Origins of Quality by Design

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Analysis and Control of Variation.
John McConnell, Coordinator
The Forgotten Origins of
Quality by Design
John McConnell, Brian K. Nunnally, and Bernard McGarvey
“Analysis and Control of Variation” is dedicated
to revealing weaknesses in existing approaches to
understanding, reducing, and controlling variation
and to recommend alternatives that are not only
based on sound science, but also which demonstrably work. Case studies will be used to illustrate both
problems and successful methodologies. The objective of the column is to combine sound science with
proven practical advice.
Reader comments, questions, and suggestions
will help us fulfill our objective for this column. Case
studies illustrating the successful reduction or control of variation submitted by readers are most welcome. Please send your comments and suggestions
to column coordinator John McConnell at john@
wysowl.com.au or journal coordinating editor Susan
Haigney at [email protected].
KEY POINTS DISCUSSED
The following key points are discussed:
•Quality by design can be traced to the original
work of Dr. Joseph M. Juran.
•Juran believed that nearly all problems (e.g., deviations, quality defects, etc.) are built into the system,
and that they can be traced to inadequate design
of the process. Therefore, if addressed during the
design phase, they can be largely designed out.
•QbD starts with the quality target product profile.
Juran calls this defining the customer needs.
•QbD then proceeds with identification of critical quality attributes (CQAs). Juran calls this
development of product features. These should
be reviewed by both customer and producer.
•Internal service groups must feel competition from
outsourced services to continually improve their
services, reduce variation, and positively impact
product throughout the product lifecycle.
•Once CQAs have been defined, the manufacturing process to meet these CQAs can be designed
including technology and human components
•Sampling and sample handling variability should
be quantified and minimized.
•Capability (CpK) is the measure of a process’ ability
to meet its targets or specifications.
•The final aspect of QbD is designing a control
strategy, which Juran called developing process
controls.
•Understanding the impact of variation, and designing it out wherever possible is an important part
of QbD.
•The dominant variables of a process can be
described as set-up, components, time, and
worker elements.
•Knowing which is likely to be dominant significantly impacts on design.
•Designing a control strategy that ensures a robust
process depends on understanding the sources of
variation for each step (or assay) and controlling
them. Understanding which category a variable
helps to determine how best to attack variability.
•Juran’s work, the basis for QbD, is now described
in ICH Q8 (R2), Pharmaceutical Development.
INTRODUCTION
The US Food and Drug Administration and the International Conference on Harmonisation (ICH) have
[
ABOUT THE AUTHORS
For more Author
information,
go to
gxpandjvt.com/bios
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John McConnell is owner and director at Wysowl Pty Ltd in Queensland, Australia. He may be
reached at [email protected]. Brian K. Nunnally, Ph.D., is in charge of process validation at
Pfizer in Sanford, NC. He may be reached at [email protected]. Bernard McGarvey, Ph.D.,
is process modelling group leader, Process Engineering Center at Eli Lilly and Company in Indianapolis,
IN. He may be reached at [email protected].
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Validation T echnology [Summer 2010]
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John McConnell, Coordinator.
embraced the concept of building quality into pharmaceutical manufacturing processes. This has been
called quality by design (QbD). Many pharmaceutical
scientists are not aware of the origins of QbD, nor are
they familiar with its originator, Dr. Joseph Juran.
The QbD concept was originally published in 1985.
The seminal work is Juran on Quality by Design (1). This
book outlines the reasons and methodology for planning
quality into a manufacturing process. Juran did not use
pharmaceuticals or medical devices in his book, but all
of the principles are present and have been adapted into
ICH Q8 (R2), Pharmaceutical Development (2).
Figure 1: The Juran trilogy (adapted from 1).
BASICS OF QBD
For Juran, quality problems are planned that way (i.e.,
they are built into the system) (1). He believed that all
quality defects were a result of a poorly planned quality
system. The Juran trilogy is shown in Figure 1. We
have shown this as an interlocking sequence, as we are
sure Juran believed it to be. The corollary to this, and
the most important aspect for the pharmaceutical and
medical device industry, is that the quality problems
can be prevented by understanding the process better
for the determination of design space, identification of
critical quality attributes, and defining an appropriate
control strategy.
Quality Target Product Profile
QbD starts with an understanding of the quality target
product profile (QTPP). This is defined as a prospective
summary of quality characteristics of a drug product
(or medical device, drug substance, etc.) that ideally
will be achieved to ensure the desired quality, taking
into account safety and efficacy of the drug product (or
medical device, drug substance, etc.) (2). Juran would
call this defining the customer needs. Juran states, “the
goal should be customer satisfaction rather than mere
conformance to stated needs” (1). Translated for the
pharmaceutical industry (note: medical devices are
included but will not be further explicitly discussed),
this would mean a focus on producing medicines that
improve the lives of the patients we serve. Our industry
is not involved in the production of widgets; we produce
life-saving and life-enhancing medicines designed to
improve, save, and elongate the lives of our customers.
In this light, the best way to serve our customers is to
be a customer, as Juran would probably say. We need
to think like a patient and not forget the patient in all
of our work. The quality cannot be built into the drug
until the parameters needed are defined (e.g., the route
of administration, dosage, strength, etc.)
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Critical Quality Attributes
Once the QTTP is defined, work on defining the critical
quality attributes (CQAs) can commence. Juran would
call this process the development of product features. His
advice rings true with today’s development. “Product
development requires not only functional expertise; it
also requires the use of a body of quality-related knowhow” (1). Development scientists need a thorough understanding of manufacturing and quality as their data and
experiments form the basis of the processes and methods
used during commercial manufacture. Juran would
be supportive of the efforts made by manufacturing
to have influence on the development process and by
development to better understand the needs of commercial manufacturing and the product released to the
marketplace. It is the job of both to ensure the planned
approach includes work to guard against external failures. These include product and process design-related
issues, carryover from previous processes, and degradation (2). The carryover of previous processes (think
toolbox technologies) can contribute to future quality
issues by embedding these into new processes.
The CQAs are those product (or drug substance)
characteristics having an impact on product quality and
should be studied and controlled (2). Juran advises that
this criticality needs to be reviewed by both customer
and supplier (1). This means both the patient and the
business are stakeholders. The patient benefits from
a robust process that ensures those attributes central
to the safety and efficacy of the drug are predictable.
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Analysis and Control of Variation.
Figure 2: Pharmaceutical adapted Juran process model (adapted from 1).
and controlled to ensure patient and business success.
This is not an end, but should be considered to be a
process encompassing the entire lifecycle history of
the product and process.
Critical Process Parameters
Likewise, the business benefits through reduction of
cost and increase in volume (see Little’s Law [3,4]),
lowered frequency of deviations, improved utilization
of human capital and fixed assets, and less rework and
waste. The CQAs will be dependent on the various
inputs to the process—Juran predicted this as well (1).
Minimizing the variability in these inputs (including
process parameters and raw materials, sampling, and
analytical) will improve the ability to determine and
maintain the CQAs.
Internal Monopolies
In his discussions of the development of product
features, Juran has an interesting sidebar on internal
monopolies. Internal monopolies were once the rule in
the pharmaceutical industry. Services such as clinical
trial management, active pharmaceutical ingredient
(API) manufacture, and testing were all done in-house
by the company’s employees. With the increase in
outsourcing, there is really no such thing as an internal
monopoly. All of the services mentioned previously
are being performed by contract organizations. Juran
predicted the beginnings of this when he advised that
competitive information from outside suppliers of
similar services could be acquired to ensure the highest
quality, speed, and value are being obtained (1). This
put pressure (used in its least pejorative sense) on the
internal monopoly to demonstrate its competitiveness.
This benchmarking is critical to the survival of the
internal monopoly. A word of caution on outsourcing:
While it seems to be all benefit with no “cost,” this is
not always the case. Part of the agreement between
the company and the service providers has to include
tough variability reduction (per Deming’s approach
to quality) of operating parameters, output characteristics, and assays. Variability should be identified
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Once CQAs have been defined, the manufacturing
process to meet these CQAs can be selected or designed
(2). This process includes both technology as well as
the human components (1). The human factor is built
into the process and must be considered in the design to
error proof the human element. Too many deviations
are seen that are blamed on human root causes when,
in fact, these are process design elements that could
have designed the problem out. We have been told
about companies where up to 50% of the root causes
are human error. For these situations, we predict these
same 50% of the deviations will happen again due to
inadequate corrective and preventative actions.
Juran offered that process design should be goal oriented, systemic, capable, and legitimate (1). A pharmaceutical adapted Juran model of process development
is shown in Figure 2. A process cannot meet a target
not specified. The following are examples:
•What are the quality goals to be met?
•How much variation can be tolerated from
the process?
•Sampling?
•Analytical methods?
•What output is needed?
•How can the process be scaled to meet demand
(higher or lower)?
All of these questions (and more) must be discussed to prepare a comprehensive set of goals for
the process. The process is a series of interconnected
systems; each one having an impact on the other.
For instance, variability in analytical results used by
the process as part of the manufacture (e.g., used by
the process to determine how the next step will be
run) have a larger impact on the overall variability
than those that are not used to run the process. It
is important to remember that the laboratory tests
the sample, not the process. Sampling (and sample
handling) variability cannot be ignored and should
be quantified and minimized as it ultimately affects
the overall variability of the process. Capability is
crucial to meeting the process goals. Capability is
the measure of a process’ ability to meet its targets or
specifications. The key aspect of capability (CpK) is
variability, as shown in the following equation:
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John McConnell, Coordinator.
where
USL is the upper specification limit
LSL is the lower specification limit
x is the mean
σ is a standard deviation.
There are only three ways to improve capability,
as follows:
•Move the specification away from the mean.
This is a difficult task to accomplish in the pharmaceutical industry without significant data and
lengthy regulatory agency discussions.
•Move the mean away from the specification. For
double-sided specifications, this only works if
the mean is not centered.
•Decrease the variability. Given the fact that this
is multiplied by three, this has the greatest power
to improve capability. In an extreme understatement, Juran suggested this evaluation had
“merit” (2). More than this, it is a critical part
of process understanding.
It is important to remember that it is impossible to
know or understand the capability of an unpredictable
process. Finally, the process must be legitimate. Juran
states, “...if there is the approval of those to whom
responsibility has been delegated” (1). This is not
a common concern in the pharmaceutical industry
where clear accountability is often present.
These are critical steps that are important to the
determination of the CQAs. The planning associated
with these steps should also include planning of the
quality system. This plan includes alarm strategy,
redundancy, and design to improve robustness and
decrease variability. The final process including manufacturing, sampling, and analytical should be designed
and demonstrated to be in control (e.g., predictable),
appropriate for its intended use, and capable of meeting
the defined CQAs (and thus the QTPP).
Control Strategy
The final aspect is designing a control strategy (2)
that Juran called developing process controls (1).
This should be done in concert with process development. The concept of design space comes into play at
this point. So much has been written and presented
on design space that we will not discuss this in great
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detail in this article. Design space is the relationship
of the process inputs to the CQAs (2). Juran did not
utilize the terminology, but did describe the different
types of variables present in a process. He described
the concept of dominant variables, defined as those
variables that are more important than others. The
variables described include the following:
•Set-up dominant variables. These are variables
affecting processes that are dependent on the setup
and confirmation of the setup to provide stability and reproducibility. Equipment and supplier
differences can contribute to variability for these
operations. Automated assays and packaging
machines fall into the set-up dominant category.
•Time dominant variables. These are variables
affecting processes that change over time and
need to be adjusted based on evaluation of control
parameters. An example of this variable is ultra
filtration operations. It is important to be vigilant
against over-control (e.g., needlessly adjusting the
process based on the last result obtained).
•Component dominant variables. These are
variables affecting processes in which the main
variable is the quality of the inputs or materials.
The variability in drug substance can be a large
source of variability for a drug product process.
Many chemical reactions fall in this category
as well. In these instances reducing variability
upstream is critical (Little’s law).
•Worker dominant variables. These are variables affecting processes where the quality attributes are determined by the skill of the worker.
Many types of assays fit into this category. Nonautomated processes can be included here as well.
Ensuring operators or analysts performing the
same functions or on different shifts have identical practices is important to reducing variability
in this category.
Designing a control strategy that ensures a robust
process depends on understanding the sources of variation for each step (or assay) and controlling them.
Understanding which category a variable helps to
determine how best to attack variability.
The closest comparison to the design space concept
is what Juran referred to as the “Data Base” (1). He
described this as a compendium of lessons learned
from human experiences. He referred to the exercise of
reviewing the information as “the Santayana Review”
named after George Santayana who stated, “those who
cannot remember the past are doomed to repeat it”
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Analysis and Control of Variation.
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(1). The purpose of this process is to improve decision-making by using the lessons of the past. For the
pharmaceutical industry, the design space is reviewed
and documented into process experience reports that
are summarized in the development history section
of the common technical document format of the
dossier. Having this information codified in a single
location is critical to resolve process upsets and to
continue process improvements post marketing.
REFERENCES
FINAL THOUGHTS
ARTICLE ACRONYM LISTING
The concept initially developed by Joseph Juran is
the origin of the modern QbD movement in the
pharmaceutical industry. All of the relevant parts
are there; long before they were published in the ICH.
A review of these lessons forms the first principles
understanding of QbD.
CQA
FDA
ICH
QbD
QTPP
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Validation T echnology [Summer 2010]
1. Juran, Joseph M., Juran on Quality by Design, The Free
Press, 1992.
2. ICH, Q8 (R2), Pharmaceutical Development, 2009.
3. Nunnally, Brian K, and J.S. McConnell, Six Sigma in the
Pharmaceutical Industry, Taylor and Francis, 2007.
4. McConnell, John, Brian K. Nunnally, and Bernard McGarvey, “Having It All,” Journal of Validation Technology,
Vol. 16, No. 2, Spring 2010. JVT
Critical Quality Attributes
US Food and Drug Administration
International Conference on Harmonisation
Quality by Design
Quality Target Product Profile
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