A risk-based analysis of the AAPS conference report on quantitative bioanalytical methods validation and implementation.

The 3rd American Association of Pharmaceutical Scientists (AAPS)/Food and Drug Administration (FDA) Bioanalytical workshop in 2006 concluded with several new recommendations regarding the validation of bioanalytical methods in a report published in 2007. It was aimed to conciliate or adapt validation principles for small and large molecules and an opportunity to revisit some of the major decision rules related to acceptance criteria given the experience accumulated since 1990. The purpose here is to provide a "risk-based" reading of the recommendations of 3rd AAPS/FDA Bioanalytical Workshop. Five decision rules were compared using simulations: the proposed pre-study FDA and Total Error Rules, the rules based on the beta-Expectation Tolerance and beta-gamma-Content Tolerance Interval and, finally, the 4-6-20 rule for in-study acceptance of runs. The simulation results demonstrated that the beta-Expectation Tolerance Rule controls appropriately the risk. The beta-gamma-Content Tolerance Interval was found to be too conservative, depending on the objective, and to lead to a high rate of rejection of procedures that could be considered as acceptable. On the other side, the FDA and the AAPS/FDA workshop Total Error Rule, combined or not, did not achieve their intended objective. With these rules, the risk is high to deliver results in study that would not meet the targeted acceptance criteria. This can be explained because, first, there is confusion between the quality of a procedure and the fitness of purpose of the results it could produce and, second, between the initial performances of a procedure, for example evaluated during pre-study validation and the quality of the future results.

[1]  Robert W. Mee β-Expectation and β-Content Tolerance Limits for Balanced One-Way ANOVA Random Model@@@b-Expectation and b-Content Tolerance Limits for Balanced One-Way ANOVA Random Model , 1984 .

[2]  Robert O. Kringle,et al.  An Assessment of the 4-6-20 Rule for Acceptance of Analytical Runs in Bioavailability, Bioequivalence, and Pharmacokinetic Studies , 1994, Pharmaceutical Research.

[3]  Michael S. Hamada,et al.  Bayesian Prediction Intervals and Their Relationship to Tolerance Intervals , 2004, Technometrics.

[4]  S. S. Wilks Statistical Prediction with Special Reference to the Problem of Tolerance Limits , 1942 .

[5]  Robert W. Mee β-Expectation and β-Content Tolerance Limits for Balanced One-Way ANOVA Random Model , 1984 .

[6]  P. Chiap,et al.  An analysis of the SFSTP guide on validation of chromatographic bioanalytical methods: progress and limitations. , 2003, Journal of pharmaceutical and biomedical analysis.

[7]  Eric Ziemons,et al.  Analysis of recent pharmaceutical regulatory documents on analytical method validation. , 2007, Journal of chromatography. A.

[8]  Vinod P. Shah,et al.  Workshop/conference report—Quantitative bioanalytical methods validation and implementation: Best practices for chromatographic and ligand binding assays , 2007 .

[9]  Walthère Dewé,et al.  Risk management for analytical methods based on the total error concept: Conciliating the objectives of the pre-study and in-study validation phases , 2007 .

[10]  Robert W. Mee Estimation of the percentage of a normal distribution lying outside a specified interval , 1988 .

[11]  D. J. Finney Statistical Method in Biological Assay , 1966 .

[12]  M Laurentie,et al.  Harmonization of strategies for the validation of quantitative analytical procedures. A SFSTP proposal--part II. , 2004, Journal of pharmaceutical and biomedical analysis.

[13]  Anika Ashok,et al.  Guidance for Industry by U.S. Department of Health and Human Services—Food and Drug Administration—Center for Biologics Evaluation and Research (CBER)—February 1999 , 2009 .

[14]  I. Guttman,et al.  Statistical Tolerance Regions: Classical and Bayesian , 1970 .

[15]  Philippe Hubert,et al.  New advances in method validation and measurement uncertainty aimed at improving the quality of chemical data , 2004, Analytical and bioanalytical chemistry.

[16]  David Hoffman,et al.  TWO-SIDED TOLERANCE INTERVALS FOR BALANCED AND UNBALANCED RANDOM EFFECTS MODELS , 2005, Journal of biopharmaceutical statistics.

[17]  D L Massart,et al.  An analysis of the Washington Conference Report on bioanalytical method validation. , 1994, Journal of pharmaceutical and biomedical analysis.