Biomedical Engineering Reference
In-Depth Information
support continued learning about the relationship between raw material variation and
manufacturing consistency.
Last, the examples described in this chapter point to limitations in the tools used to
fuse data from several tests each with noise and to project these guesses into the future in
some rational way. Estimation of process risk for unchartered variables—raw materials
that will be received in the future—will be evaluated usingmore powerful statistical tools
such as Bayes' theorem in the future. Bayes' theorem based calculations result in more
stable and accurate estimates of errors than simple frequency-based results used in this
chapter [23]. By combining types of analytical tests with different statistical and
chemical sensitivities with a Baysian analysis framework, the prospective design space
concept mapped out by QbD can be mapped onto future conditions of rawmaterials with
more predictable risks and, therefore, an ability to highlight shortcomings that may creep
into a control strategy as time passes.
ACKNOWLEDGMENTS
Dr. Julie Yu Wei, Biogen Idec, contributed Figure 11.7, experimental results and many
helpful discussions.
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