Conclusion
Logistic regression was demonstrated to be a better approach than the current method for estimating accurate and statistically
justifiable VRLs based on discrete responses. It has the advantage of always making biologically meaningful predictions and,
in most cases, its predictions closely reflect observations. Logistic regression should be used to determine VRLs rather than
current method. Because the model may provide a much larger VRL than the current method does, the quality of visual inspection,
in terms of the discrete response, can be improved by properly controlling the experimental variables and defining the acceptance
criterion for the estimation of VRL.
Based on the modeling procedure, VRL can be defined as a scientifically justifiable residue concentration that, when viewed
with the unaided eye, as measured by a specific method, would be detected by the observers with a predefined acceptance criterion.
Once established, the VRL could then be used for CV and routine monitoring purposes. It would be appropriate to define the
VC criterion as the absence of all particulate and nonparticulate contaminants above the established VRL from the surface
when viewed with the unaided eye under preverified viewing conditions.
M. Ovais is a senior pharmaceutical scientist at Xepa-Soul Pattinson, 1-5, Cheng Industrial Estate, 75250 Melaka, Malaysia, tel. +60
63351515, fax +60 63355829, mohammad@xepasp.com
.
References
1. PIC/S, "Recommendations on Validation Master Plan, Instal-lation and Operational Qualification, Non-Sterile Process Validation,
Cleaning Validation," (PIC/S, Geneva, Aug. 2002).
2. PDA Pharmaceutical Cleaning Validation Task Force, PDA J. Pharm. Sci. Technol.
52
(6), 1–23 (1998).
3. W. Hall, J. Val. Technol.
14
(1), 42–49 (2007).
4. R.J. Forsyth, J. Hartman, and V. Van Nostrand, Pharm. Technol.
30
(9), 104–114 (2006).
5. R.J. Forsyth and J. Hartman, Pharm. Eng.
28
(3), 1–10 (2008).
6. European Chemical Industry Council, Guidance on Aspects of Cleaning Validation in Active Pharmaceutical Ingredient Plants, (CEFIC, Brussels, Dec. 2000)
7. G.L. Fourman and M.V. Mullen, Pharm. Technol.
17
(4), 54–60 (1993).
8. NASA, "Space Shuttle, Contamination Control Requirements (Lyndon B. Johnson Space Center, Houston, TX)," SN-C-0005, Rev.
D, 1–3 (July 20, 1998).
9. D. A. LeBlanc, Pharm. Technol.
22
(10), 136–148 (1998).
10. R.J. Forsyth, V. Van Nostrand, and G. Martin, Pharm. Technol.
28
(10), 58–72 (2004).
11. R.J. Forsyth and V. Van Nostrand, Pharm. Technol.
29
(10), 152–161 (2005).
12. R.J. Forsyth and V. Van Nostrand, Pharm. Technol.
29
(4), 134–140 (2005).
13. G. Hutcheson and N. Sofroniou, "Logistic Regression," in The Multivariate Social Scientist: Introductory Statistics Using Generalized Linear Models (Sage Publications, London, 1st ed., 1999), pp. 113–152.
14. J.L. Fleiss, B. Levin, and M.C. Paik, "Logistic Regression," in Statistical Methods for Rates and Proportions, W.A. Shewart and S.S. Wilks, Eds. (John Wiley and Sons, Hoboken, NJ, 3rd ed., 2003), pp. 284–339.
15. F.Y. Hsieh, D.A. Bloch, and M.D. Larsen, Stat. Med.
17
(14), 1623–1634 (1998).
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