Coming to a Biotech Near You: Quality by Design Part 2: Design Space in Development and Manufacturing - In a time of necessary speed and robustness, Quality by Design and Design Space are useful tools

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Coming to a Biotech Near You: Quality by Design Part 2: Design Space in Development and Manufacturing
In a time of necessary speed and robustness, Quality by Design and Design Space are useful tools for companies to use.


BioPharm International
Volume 21, Issue 7

This "contour profiler matrix plot" was created using the optimum settings for each of the three significant variables in the PharmaCo example. This tool brings together three-dimensional response surface plots, each of which was originally created in the modeling software. The X and Y axes are made up of the DoE variables, and the Z axis (the contour curves) represent yield (the response variable). In the white regions, yield is in specification, and in the shaded regions it falls outside specification.

Each of the cells is a three-dimensional plot in which the Y variable is to the left of the cell, the X variable is below the cell, and the Z variable is the measured response, yield. For example, the top left cell has raw material attribute 1 as the Y axis and raw material attribute 2 as the X axis; the surface depicted in the plot represents yield.

The goal is to find an available Design Space in which the variables can produce in-specification yield. That is: what values for the variables offer the optimum path to achieving the desired yield? The "contour matrix profiler" shows the areas (in white) in which you can operate successfully and those (shaded) in which you cannot. Those white areas are the Design Space for PharmaCo's fermentation process. In that Design Space, one can identify an area in the center as the operating space, in which the process or outcome will be in control. By choosing this "sweet spot" for yield, and again for the other CQAs as the operating space, they can be sure that the process won't drift into inoperable regions.

THE ADVANTAGES OF UNDERSTANDING DESIGN SPACE

Successfully defining the Design Space means you have achieved a full understanding of the various permutations of input variables and process parameters that ensure an in-specification product. As a result, you gain far more flexibility in changing process parameters and other variables. For example, when raw material batches vary, PharmaCo can make the necessary adjustments in the manufacturing process to compensate for the effects of differing properties and be confident that the resulting product will achieve the desired results.

Despite the significant operational and business benefits that the FDA's QbD initiative offers, only a small number of organizations know how to take full advantage of it. Many continue to use one-variable-at-a-time analysis, even though critical pro- cesses may depend on the complex interactions of several variables. The result: poorly understood processes, an inability to demonstrate adequate control, costly delays in development, and many processes that are neither robust nor reliable. But with carefully structured data analysis through statistical tools, biotech organizations can achieve the robust and reliable processes required to streamline scale-up, technology transfer, and validation, and produce high-quality biologic products. At a time when the pharmaceutical industry is under intense pressure to make safe products and reduce costs, these tools and approaches offer tremendous value.

As illustrated in the PharmaCo example, it's never too late to apply these statistical tools to a process. In fact, it's a straightforward process and can be accomplished in a relatively short period of time. It offers significant enhancement to process understanding, improves scientific rigor, and typically results in significantly enhanced qualitative and quantitative performance as well as cost savings.

Jason Kamm is managing consultant and Conrad J. Heilman, Jr., PhD, is senior vice president, both at Tunnell Consulting, King of Prussia, PA, 610.337.0820,

REFERENCES

1. International Conference on Harmonization. Q8, Pharmaceutical development. Geneva, Switzerland; 2005.


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