In vitro dissolution profile comparison--statistics and analysis of the similarity factor, f2.
ABSTRACT To describe the properties of the similarity factor (f2) as a measure for assessing the similarity of two dissolution profiles. Discuss the statistical properties of the estimate based on sample means.
The f2 metrics and the decision rule is evaluated using examples of dissolution profiles. The confidence interval is calculated using bootstrapping method. The bias of the estimate using sample mean dissolution is evaluated.
1. f2 values were found to be sensitive to number of sample points, after the dissolution plateau has been reached. 2. The statistical evaluation of f2 could be made using 90% confidence interval approach. 3. The statistical distribution of f2 metrics could be simulated using 'Bootstrap' method. A relatively robust distribution could be obtained after more than 500 'Bootstraps'. 4. A statistical 'bias correction' was found to reduce the bias.
The similarity factor f2 is a simple measure for the comparison of two dissolution profiles. But the commonly used similarity factor estimate f2 is a biased and conservative estimate of f2. The bootstrap approach is a useful tool to simulate the confidence interval.
- SourceAvailable from: Ahmed El-AshmawyInternational Journal of Pharmacy and Pharmaceutical Sciences 01/2014; · 1.59 Impact Factor
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ABSTRACT: The objective of present work was to construct nomogram for obtaining a value of similarity factor (f2) by employing the values of number of observations (n) and sum of squared difference of percentage drug dissolved between reference (R) and test (T) products . The steps for rearrangement of equation of similarity factor are presented. The values of f2 were selected in the range of 45 to 100 for 4 to 12 observations (n) for computing the values of Linear regression analysis was performed between number of observations and . Perfect correlation was observed in each case. Nomogram was constructed and later it was validated by using drug dissolution data from literature and our laboratory. The use of nomogram is recommended during research and development work to investigate effect of formulation or process variables. The nomogram can also be used during change in manufacturing site or change in equipment. It is concluded that the steps for calculation of f2 can be truncated in the middle (i.e. at the step of calculation of factor and a decision of similarity/dissimilarity can be taken employing the nomogram.Indian Journal of Pharmaceutical Sciences 05/2014; 76(3):245-51. · 0.34 Impact Factor