![Definition :
It is graphical representation [in terms of
concentration vs. time] of complete release of drug from a dosage form in an
appropriate selected dissolution medium.
i.e. in short it is the measure of the release of A.P.I from a dosage form
with respect to time.
3](https://image.slidesharecdn.com/comparisionofdissolutionprofile-140209035958-phpapp02/85/Comparision-of-dissolution-profile-3-320.jpg)
![
Model Independent Approach Using a Similarity Factor:
• The difference factor (f1 ) calculates the percent (%) difference
between the two curves at each time point and is a measurement of
the relative error between the two curves:
f1= {[Σ t=1n |R-T|] / [Σ t=1n R]} ×100
where n is the number of time points, R is the dissolution value of
the reference (prechange) batch at time t, and T is the dissolution value
of the test (postchange) batch at time t.
20](https://image.slidesharecdn.com/comparisionofdissolutionprofile-140209035958-phpapp02/85/Comparision-of-dissolution-profile-20-320.jpg)
![The similarity factor (f2 ) is a logarithmic reciprocal square root
transformation of the sum of squared error and is a measurement of the
similarity in the percent (%) dissolution between the two curves.
f2= 50×log {[1+ (1/n) Σ t=1n (R-T) 2]-0.5 ×100
Limits for similarity and difference factors
Difference
factorf1
0
Similarity
factor f2
100
Inference
Dissolution profiles are similar
Similarity or equivalence of
two
≤15
≥50
profiles.
21](https://image.slidesharecdn.com/comparisionofdissolutionprofile-140209035958-phpapp02/85/Comparision-of-dissolution-profile-21-320.jpg)
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Uploaded byRanjith Karanam
Comparision of dissolution profile
This document discusses methods for comparing drug dissolution profiles, which provide information about how completely and quickly an active pharmaceutical ingredient is released from its dosage form. Graphical and statistical methods are described for directly comparing dissolution curves. Model-dependent approaches apply kinetic models like zero-order, first-order, and Higuchi models to the data. Model-independent methods calculate similarity factors f1 and f2 that provide single values for comparing profiles. Comparing dissolution profiles is important for evaluating drug release and bioequivalence of pharmaceutical formulations.
