Abstract
Purpose. To determine the statistical variability expected for a well designed HPLC assay of a bulk drug substance (BDS). The results are used to develop appropriate acceptance criteria for a method validation protocol as well as to evaluate the level of uncertainty expected for assay results using a variety of sampling/injection schemes.
Methods. Computer simulation was used to generate a large quantity of data and the variability of the mock results was evaluated. Error propagation was also calculated, whenever possible, to confirm results obtained from the simulations.
Results. Protocol acceptance criteria were developed that were consistent with the expected variability for data resulting from the execution of the validation protocol. In certain cases simulations provided the only avenue of obtaining results that could not otherwise be readily determined.
Conclusions. Computer modeling can be used to obtain suitable acceptance criteria for validation results which are consistent with method variability. This is particularly significant in the case of linearity where it has been difficult to develop acceptance criteria based on anything other than analyst intuition and experience. Assay simulations clearly demonstrated that the variability expected for a typical BDS assay is large relative to the average specification range and therefore little insight about relative purity can be gained comparing individual passing assay results.
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REFERENCES
USP 23, General Chapter 1225, pp. 1982–1984.
Federal Register, Vol. 60,No. 40, Wednesday, March 1, 1995.
ICH3 Announcement, Validation of Analytical Procedures: Methodology, Step 2 of the ICH Process, 29 November 1995.
Hugh D. Young. Statistical Treatment of Experimental Data, McGraw Hill, Inc., 1962.
USP 23, General Chapter 31, p. 1680.
Sanford Bolton. Pharmaceutical Statistics, Marcel Dekker, Inc., 2nd edition, 1990, Drugs and the Pharmaceutical Sciences Volume 44.
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Bunnell, R.D. Using Computer Simulated Results of a Bulk Drug Substance Assay to Determine Acceptance Criteria for Method Validation. Pharm Res 14, 156–163 (1997). https://doi.org/10.1023/A:1012088308307
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DOI: https://doi.org/10.1023/A:1012088308307