Move Toward a Mechanistic Model
The knowledge gained now provides an opportunity to work toward a general mechanistic model. Working with subject matter experts,
the model is recast from the empirical model into a mechanistic form.8
Continuous Improvement: Integrating QbD and Related Approaches into Process Development
Recognizing that organizations and individuals are in various states of maturity regarding QbD greatly facilitates the transition
to the new development process.
For organizations that already have experience with QbD, improved use will result from periodic review (quarterly, semi-annually,
and annually, depending on the organization) of its use of QbD and what changes need to be made. This review should include
the QbD strategy, methods used, and results obtained. The assessment should also evaluate how QbD has been used at the various
stages of development ranging from initiating development of a new drug, to regulatory submission, to product launch, to manufacturing
scale-up, and long-term production.
For organizations just starting QbD, one approach is to use a strategy of "starting small, thinking big"; i.e., start with
a modest plan, but have clear goals, milestones, and long-term goals. Behavior change will be needed; pay attention to the
principles of organizational change.
In any new initiative, it is helpful to have a set of principles to guide the effort. We have found the principles summarized
in Table 1 to be useful. We must begin with a sense of urgency that the new approach is essential to our success.9 Senior management must establish the sense of urgency, see that a systematic approach is developed and used, and keep emphasizing
the importance of developing process understanding and its relation to process variation.
Top management also has to keep the organization focused on using the new approach in high impact areas and should request
supporting data and measures of all results. Management also must lead efforts to ensure that management systems are in place
to sustain the approach and results over time, and celebrate successes to recognize results and reinforce the desired behaviors.
The lessons learned highlight what is necessary to increase the time value of data: getting the right data at the right time
in the right amount. Table 2 presents some principles that can be used to guide the applications of this approach. These principles
generally teach a holistic, end-to-end view. You must keep an eye on what the end result looks like, follow a systematic,
structured approach, and remember the measurement system. This will speed up downstream development by getting the right data,
in the right amount, at the right time.
Anthony Lonardo is the associate vice president of statistics and quantitative sciences, and Bo Qi is the director of process development, both at ImClone Systems, 908.541.8240, email@example.com
Ronald D. Snee, PhD, is the founder and president of Snee Associates, LLC.
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