OTHER CONCERNS

Other comments by skeptics have been used to deflect encouragement to implement QbD and DOE. Here are some of the more common ones with replies.

"This is just the latest fad, the flavor-of-the-month. Just watch, this will be replaced by some other new corporate initiative by the next VP or CEO." This could be the case in some companies. Progressive companies that have a long-term view of success, however, recognize the benefits of embedding QbD into the company culture.

"Our development is more art than science. Designed experiments don't work for this. It takes years and years of experience to develop our products." This is an admission that sources of variability are not known and are not being controlled. Process understanding is a key concept in QbD and PAT. Without control of material and process variabilities, the process capability of any new product is just a guess. A foundation of variation control is fundamental to any development.

"Statistics was my most difficult class in college." Unfortunately, many university statistics classes are too theoretical and are often intended for mathematics majors. The field of statistics was born at the junction of biology, genetics, and mathematics in the mid-to-late 1800s as practical way to deal with variability and large amounts of data. Applied statistics courses, however, can be very helpful, particularly if they are sufficiently pragmatic and data oriented. Most applied courses require only algebra. The root cause of the problems is that most students are not exposed to any statistical concepts until they are adults in college. If the process development staff lack a solid foundation in statistics, management must support inhouse training or send staff out for applied courses.

"If my major professor didn't think this (QbD, DOE) was important enough to teach it to me, then it must not be anything I need." This is understandable, regrettable, and self-perpetuating. There can be two reasons for the professor's failure to promote QbD. First, the professor's goal is to teach the science subject, not statistics. Like knowing algebra or grammar, the professor assumes the student has the background or will get it later. The second reason is that for most courses, the focus is on theory and not on applying or implementing the concepts using data.

Finally, we must acknowledge two human failings—the failure to get expert help and the lack of willingness to endure failure. It can be difficult for successful people to ask for help in a subject they don't know. They feel that they should be able to master the topic themselves. Again, management needs to step in with support and encouragement. Encouragement and money are further needed to weather the inevitable failures.

Not all endeavors succeed and not all experiments are breakthroughs, but we learn from the failures. Experimentation should be seen as guided learning that builds the knowledge base of the company and thus competitive advantage. QbD is a process, not an event. Knowledge gained in one set of experiments is used to refine and design the next set of experiments. QbD is an investment, not an expense.

SUMMARY

It is human nature to resist new and different ways of thinking and working. Given past management fads, skeptics have a legitimate concern about the long-term sustainability of QbD. But the 50-plus years of its application in the major chemical companies is an assurance that it can be implemented successfully. QbD offers future benefits to companies and management willing to invest in the time and effort to be competitive.

If QbD really is the competitive future, how can we learn more about it? The key industry organizations delivering education and training in the principles and tools for successful QbD implementation are the American Society for Quality, the Parenteral Drug Association, the American Association of Pharmaceutical Scientists, and the International Society for Pharmaceutical Engineering. The courses, seminars, and workshops sponsored by these organizations have demonstrated that projects using QbD approaches can be more efficient, less costly, and data rich in the development of new products. Process scientists have also learned how to mine data using these tools to improve existing products and processes.

Take advantage of this opportunity. Learn more about QbD and use the tools to enhance the products delivered to patients and also improve the financial bottom line.

REFERENCES

1. Neway J. How to make the business case for Quality by Design. BioPharm Int. 2008:21(12):42–47.

2. The Problem of Process Validation," J. R. Sharp, The Pharmaceutical Journal, January 11, 1986.

3. PharmaQbD web cast; 2008 Oct 14. Available from http://www.PharmaQbD.com/.

4. Gryna FM. Quality and Costs. Juran JM. Godfrey AB, editors. Juran's Quality Handbook. 5th ed. New York: McGraw Hill; 1999. p. 8.1–8.26.

5. Dwyer T, Keresty G, Sherry B. The cost of non-conformance: the linkage between quality performance and business results. Pharmaceutical Eng. 2000 Sept/Oct:8-18.

6. Design Ease, Inc. Design Expert, Version 7.1. Available from: http://www.statease.com/.

7. Fisher RA. The arrangement of field experiments. J Ministry Agriculture, England. 1926;33:503–513.

8. Torbeck LD, Branning RC. Designed experiments-a vital role in validation. Pharm Technol. 1996;20(6):108-114.

9. Fisher RA. The design of experiments. London: Oliver and Boyd;1935.

10. Box GEP, Wilson KB. On the experimental attainment of optimum conditions. J Royal Statistical Society. 1951(13):1–45.

11. Rathore AS, Branning R, Cecchini D. Quality: design space for biotech products. BioPharm Int. 2007;21(4):36–40.

Lynn Torbeck is a statistician at Torbeck and Assoc., Evanston, IL, 847.424.1314, Lynn@Torbeck.org
and Ronald Branning is the vice president of corporate quality assurance at Gilead Sciences, Inc., Foster City, CA, 650.522.5282, ron.branning@gilead.com