The chief advantage of the PDCA cycle—flexibility in moving through each phase of the cycle—is also its biggest challenge,
because it left the door open for subjectivity. Subjectivity has long been the downfall of our industry. Without a clear vision
for success or a defined method for evaluation, the potential exists to rely on unscientific process development and characterization
activities, which can lead to incorrect or incomplete conclusions. For example, univariate analysis methods—often called One-Factor-at-a-Time
(OFAT) studies5 —have been the backbone of the small-molecule pharma industry, as well as the biopharm industry. Such studies, however,
do not possess the power to fully characterize a process. The result is a false sense of security that the process characteristics
are understood.
Figure 2. Cube Plot for Protein Recovery
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An analogy would be that of trying to solve the popular "Rubik's Cube" puzzle. It may be relatively simple to get one side
of the cube all one color, thus providing the impression of progress towards your goal. However, the reality is that you are
actually further from success than when you started the exercise (Figure 2). Because of these limitations, other industries
abandoned the OFAT approach 30 years ago, deeming it ineffective for process characterization and verification.
The biopharmaceutical industry, too, has come to recognize that the OFAT approach is insufficient. The industry has also realized
that to be successful in combining quality, technical, and business requirements in the drug development lifecycle, it must
realign not only its scientific approach to process understanding, but also its thinking within the organization. As a result,
Operation Excellence initiatives have moved to frameworks such as Six Sigma to provide a roadmap that can meet this need.
SIX SIGMA AND ITS ROADMAP
Figure 3. Six Sigma as an organizational development and leadership tool
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In 1986, Motorola established a framework designed to integrate quality, process, and business requirements into the product
development lifecycle. Motorola recognized that variation is the death knell of any process, so the company set out to establish
a methodology to identify and eliminate variation. They called this approach Six Sigma6 (Figure 3).
Figure 4. The DMAIC Roadmap
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In the late 1990s, CEOs Jack Welch from GE and Larry Bossidy from Allied Signal adapted the Motorola model to a set methodology
called the DMAIC roadmap. DMAIC is an acronym for Define, Measure, Analyze, Improve and Control. These are the five phases
necessary to measure, characterize, and control a process (Figure 4).
Within each step of the road-map, a defined set of tools is applied. Each phase in the DMAIC process is intended to guide
the members of an improvement team through the project in a manner that provides relevant data and in-depth process understanding.
The DMAIC project management approach allows businesses to make the best possible decisions with the available data and resources.
The five-steps of the DMAIC process are as follows:
1. Define: Clearly define the problem and relate it to the customer's needs (generally, with a cost benefit to the organization identified).
2. Measure: Measure what is key to the customer and know that the measurement is good.
3. Analyze: Search for and identify the most likely root causes.
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