Similarity factor (f2) is a "logarithmic reciprocal square root transformation of one plus the mean squared (the average sum of squares) differences of drug percent dissolved between the test and the reference products"
There had been an introduction on similarity factor in the last blog
Various contents of this book page include
The FDA and EMEA defined similarity factor as a "logarithmic reciprocal square root transformation of one plus the mean squared (the average sum of squares) differences of drug percent dissolved between the test and the reference products"
In other words, the similarity factor ( f2) is a logarithmic transformation of the sum-squared error of differences between the test Tt and reference products Rtover all time points.It represents closeness of two comparitive formulations. Generally similarity factor in the range of 50-100 is acceptable according to US FDA.
Rtand Ttare the cumulative percentage dissolved at each of the selected n time points of the reference and test product respectively
Similarity factor Calculation Sheet ( Excel Sheet)
The primary purpose of f2 is to compare the closeness of two products under consideration.
4.1. Significance and applications of similarity factor
The wide application of similarity factor signifies it as an efficient tool for comparison of dissolution profiles.Similarity factor finds its main application as
- Response or dependent variable usually for optimization purposes, e.g. to compare manufacturing processes for establishing experimental conditions maximizing similarity between formulations.
- Part of a decision criterion to establish similarity of two formulations. The regulatory suggestion "decide similarity if (the sample) f2 exceeds 50" is applied in a literal sense.
5. Challenges for considering similarity factor as a tool for comparison of dissolution profiles2, 4, 5
- This method is more appropriate when more than three or four dissolution time points are available.
- The dissolution treatment is effective in the presence of at least 12 individual dosage units
- This method is applied only when the average difference between reference and test is less than 100.Normalization of the data may be required if the average difference between reference and test is higher than 100.
- The f2 may become invariant with respect to the location change and the consequence of failure to take into account the shape of the curve and the unequal spacing between sampling time points lead to errors.
- It is difficult to formulate a statistical hypothesis for the assessment of dissolution similarity since f2 is only a sample statistic that further complicates to evaluate false positive and false negative rates of decisions for approval of drug products based on f2 .
- It may be too liberal in concluding similarity between dissolution profiles.
- In addition, the range of f2 is from minus infinity to 100 and is not symmetric about zero. From these evidences it may be stated that f2 is convenience criterion and not a criterion based on scientific facts.
Nevertheless, with a slight modification in the statistical analysis, similarity factor would definitely serves as an efficient tool for reliable comparison of dissolution profiles.
"This book page doesn't include any plagiarized material"
2) An alternative method to the evaluation of similarity factor in dissolution testing by P. Costa,International Journal of Pharmaceutics Volume 220, Issues 1-2, 4 June 2001, Pages 77-83 3) In Vitro Dissolution Profile Comparison--Statistics and Analysis of the Similarity Factor, f2 Vinod Shah, Yi Tsong , Pradeep Sathe , and Jen-Pei Liu, Pharmaceutical ResearchVol. 15 Number 6, Jun 1998.
1. Yuksel N, Kanik AE, Baykara T, Comparison of in vitro dissolution profiles by ANOVA-based, model-dependent and -independent methods, Int J Pharm, 209, 2000, 57-67.
2. Costa P & Jose MSL, Modeling and comparison of dissolution profiles, Eur J Pharm Sci, 13, 2001, 123-133.
3. Ocana J, Frutos G & Sanchez O P, Using the similarity factor f2 in practice: A critical revision and suggestions for its standard error estimation, Chemometrics and Intelligent Laboratory Systems, 99, 2009, 49-56.
4. Costa P, An alternative method to the evaluation of similarity factor in dissolution testing, Int J Pharm, 220, 2001, 77-83.
5. O Hara T, Dunne A, Butler J & Devane J, A review of methods used to compare dissolution profile data, Pharmaceutical Science & Technology Today, 1(5), 1998, 214-223.
EMEA: Human Medicines Evaluation Unit of The European Agency for the Evaluation of Medicinal Products