Statistical Implications of the CGMPs: A 30-Year Retrospective - Pharmaceutical Technology

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Statistical Implications of the CGMPs: A 30-Year Retrospective
This article looks at the current good manufacturing practice regulations from a statistical perspective while addressing their requirements and implications and inviting the industry to assess its past performance in meeting the regulations.

Pharmaceutical Technology

Industry performance

How well has the industry achieved this task and met this challenge? It is hard to say or to tabulate. The pharmaceutical industry has at times been reluctant to share its status and progress in some areas, statistics being one. Clearly, some of the larger pharmaceutical companies have been implementing statistical techniques for a long time. The 1974 third edition of Juran's Quality Control Handbook had the first and only chapter on "Drug and Allied Industries" written by H. Latham Breunig of Lilly (11). Some companies have sustained very early efforts and others have come to it later under such names as "total quality management (TQM)," "Deming," "zero defects," "quality function deployment, QFD," "quality circles," Taguchi, Ishikawa, Kaizen, "value analysis," "just-in-time, JIT," and Six Sigma/Lean manufacturing.

More specific to pharmaceuticals has been the new USP chapter on statistics <1010> (12) and the ICH documents that contain statistical requirements or implications: stability with Q1, method validation with Q2, setting specifications with Q6 (13), pharmaceutical development, quality by design, and design space with Q8 (14), and risk management with Q9 (15).

Most recently, FDA has been encouraging the industry relative to statistics by issuing guidances related to its process analytical technology (PAT) framework (16) as well as supporting ICH documents by providing presentations on related topics such as quality by design and design space. FDA officials have done the industry a great service by attending and presenting at the many conferences and seminars.

In conclusion, we have made progress in applying statistics under the CGMPs, but it may be spotty with the large companies leading the way. Each company should reevaluate its current position with respect to the statistics in the CGMPs, OOS, ICH, and PAT.

Lynn D. Torbeck is a statistician and consultant at Torbeck and Associates, 2000 Dempster Plaza, Evanston, IL 60202, tel. 847.424.1314,

Mr. Torbeck also is a member of Pharmaceutical Technology's Editorial Advisory Board.

Where were you 30 years ago?

"I was supervisor of quality control and manufacturing applications, a statistical position with G.D. Searle in Skokie, Illinois, supervising two statisticians and a secretary. My group provided statistical consultation and long-range planning to the directors of quality control and manufacturing. We were doing statistical data analysis and designed experiments in support of the two departments and also provided training and support for statistical software."


1. L. Torbeck, "Statistical Implications of the New Current Good Manufacturing Practices Regulations," presented at the 20th Annual Quality Clinic, University of Tennessee, Knoxville, Tennessee, Mar. 8–10, 1979.

2. FDA, "Current Good Manufacturing Practice in Manufacturing, Processing, Packing or Holding of Drugs and Finished Pharmaceuticals," Fed. Regist. Feb. 13, 1976.

3. ANSI/ASQ 1.4, "Sampling Procedures and Tables for Inspection by Attributes" (2003).

4. USP 30–NF 26 (United States Pharmacopeial Convention, Inc. Rockville, MD).

5. T.N. Olson and I. Lee, "Application of Statistical Methodology in Quality Control Function of the Pharmaceutical Industry," J. Pharm. Sci. 55 (1) p. 1 (1966).

6. ANSI/ASQ Z1.9, "Sampling Procedures and Tables for Inspection by Attributes" (1993).

7. ICH Q1 Stability Testing of New Drug Substances and Products (International Conference on Harmonization, Geneva, Switzerland, 2003).

8. Chapter <1225> "Validation of Compendial Procedures," in USP 30–NF 26 (United States Pharmacopeial Convention Rockville, MD).

9. ICH Q2, Validation of Analytical Procedures (International Conference on Harmonization, Geneva, Switzerland, 1994, 1996).

10. FDA, Center for Drug Evaluation and Research, Guidance for Industry, Investigating Out-of-Specification (OOS) Test Results for Pharmaceutical Production (Rockville, MD, Oct. 2006).

11. Quality Control Handbook, J. Juan, Ed. (McGraw Hill, New York, NY, 1974).

12. Chapter <1010> "Analytical Data–Interpretation and Treatment," in USP 30–NF 26 (United States Pharmacopeial Convention, Rockville, MD).


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