COMPARISON OF DISSOLUTION PROFILE
Dissolution Profile:
Thus
for the release of a A.P.I. from a homogeneous polymer matrix-type delivery
system, Higuchi Equation indicates that the amount of A.P.I. released is
proportional to the square root of
Dissolution
profile is the complete dissolution behavior of a dosage form including
dissolution rate and extent of dissolution.
OR
It is
graphical representation (Concentration Vs Time) of complete release of A.P.I
from a dosage form in an appropriate
selected dissolution medium.
Important of dissolution profile
comparison:
- To study the variations of dissolution profile within a batch or from batch to batch of the same brand to assure uniformity of dissolution and thus bioavailability, specifically in law margin drugs.
- For optimizing the dosage formula by comparing the dissolution profile of the same A.P.I.
- Dissolution profile of an A.P.I. reflects its release pattern under the selected condition sets.
Methods for comparison:
Model
Dependent Method
Model
Independent Method
Model Dependent Method:
Zero
order A.P.I. release
First
order A.P.I. release
Hixson
Crowell cube root law
Takeru
Higuchi model
Weibull
model
Korsemeyar
and peppas model
ZERO ORDER A.P.I. RELEASE
Zero
order A.P.I. release contributes drug release from dosage form that is
independent of amount of drug in delivery system. (i.e., constant drug
release).
This
release is achieved by making:-
o
Reservoir Diffusional systems
o
Osmotically Controlled Devices
FIRST ORDER A.P.I. RELEASE
In
this type of release pattern, drug release from dosage form that is dependent
on the initial amount of drug in delivery system.
Where,
A
= Conc. at time‘t’
Ao=
Initial Conc. Of the drug
k
= Rate const.
HIXSON-CROWELL CUBE ROOT LAW
Applied
for: Powder dissolution study
This
law co-relates, the rate of dissolution of drug powder consisting of uniformly
sized particles with cube root of weight of particles.
where,
Mo =
original mass of A.P.I.particles
K =
cube-root dissolution rate constant
M =
mass of the A.P.I at the time „t‟
Equation
is called as Hixson Crowell Cube root law.
TAKERU HIGUCHI MODEL
Applied
for the suspension type of ointment & drug release from polymer matrix.
The
equation is derived for a system describe as follows:
o
Suspended drug is in a fine state.
o
The amount of drug A, present per unit volume is
substantially greater than the Cs, the solubility of the drug per unit volume
of vehicle.
o
The surface to which drug ointment is applied is
immiscible with respect to the ointment and consist of perfect sink for the
released drug.
Theoretical
concentration profile existing in an ointment containing suspended drug and in
contact with a perfect sink
Following
equation is known as Higuchi equation.
Under
normal conditions A >>Cs, and above equation reduces to
o
A = the total amount of A.P.I. in unit volume of
matrix,
o D
= the diffusion coefficient of the A.P.I. in the matrix
o Cs
= the solubility of A.P.I. in polymeric matrix and
o
t = time.
WEIBULL MODEL
Where
m =
% dissolved at time ‘t’
a = scale parameter which defines time scale of
the dissolution process
T1
= location parameters which represents lag period before the actual onset of
dissolution process (in most of the cases T1 = 0)
b =
shape parameter which quantitatively defines the curve i.e., when b =1, curve
becomes a simple first order exponential.
KORSEMEYAR AND PEPPAS MODEL
Empirical expression relates the function of
time for diffusion controlled mechanism.
It
is given by the equation
Where,
o
Mt / Ma is function of drug released
o
t = time
o
K=constant includes structural and geometrical
characteristics of the dosage form
o
n=release component which is indicative of drug
release mechanism.
Where,
n is diffusional exponent.
o
n = 1 , the release is zero order
o
n = 0.5 the release is best desribed by the
Fickian diffusion
o
0.5 < n < 1 then release is through
amnomalus diffusion or case two diffusion.
o
In this model a plot of persent drug release
versus time is liner.
Disadvantages
Violation
of underlying statistical assumption
Models
does not predict values with sufficient accuracy.
Model independent method
Classify
in two major classes
1)
Ratio test procedure
2)
Pair wise procedure.
Ratio test procedure:
1)
Ratio test of % dissolved
For
particular sample time, each of the two formulations being compared and mean %
dissolved and std. Error are to be compared.
Standard
Error of mean ratio (SET/R) can be determine by Delta method.
SET/R
= [λ (XT/XS)2 ]1/2
o
SET/R = The SE of the mean ratio of
test to ref. Std.
o
XT = The mean % dissolved of test
o
XS = The mean % dissolved of std.
o
SET = The std. Error of % dissolved
for test
o
SER = The std. Error of % dissolved
for std.
So
from mean ratio of % dissolved and SET/R, a 90% confidence interval
for XT/XR is to be considered.
Similar
procedure is followed for the ratio of AUC and MDT.
MDT
is calculated by following equation.
Where,
o
i = dissolution sample number (e.g. i=1 for 5
min.,i=2 for 10 min. data)
o
n = total number of dissolution sample time.
o
t mid = the time at mid point between
i and i – 1
o
M = addition amount of drug dissolved between i
and i –1
Time point approach:
In
this approach either the % drug released at a given time(e.g. Y60,Y300,Y480) or
the time required for a given % of drug to be released (e.g. t60%,t80%,t90%)
are often selected as responses.
Application: To distinguish good or bad
batches where some specific dissolution parameters are predetermined.
Disadvantages:
It
appears to be inadequate for complete characterization of the profile.
It
is not much problematic in IR pdts. But it has drastic effect with controlled
release pdts.
The
choice of single data points for the calculation of meaningful dissolution
value is questionable especially when it is related to BE procedure.
2)
Pair wise procedure.
DIFFERENCE
FACTOR (f1) & SIMILARITY FACTOR (f2)
o
These factors are introduced by MOORE and
FLANNER in 1996. This approach is
adopted by center for Drug Evaluation and Research (CDER) for USFDA and also by
Human Medicine.
o
Evaluation unit of European Agency for
evaluation of Medicinal products (EMEA) as criteria for assessment of
similarity between two dissolution profiles.
Difference Factor (Æ’1):
o
It calculates the percentage (%) difference
between two curves at each time point and is a measurement of the relative
error between two curves.
where,
n =
number of time points
Rt =
% dissolved at time t of reference product (prechange)
Tt =
% dissolved at time t of test product (postchange)
The
f1 equation is the sum of the absolute value of the vertical distance between
the test and reference mean values.
f1 =
zero(0) when the mean profile are identical and increases proportionally as the
difference between the mean profile increase
Similarity factor (Æ’2):
The
similarity factor (Æ’2) as defined by FDA is logarithmic reciprocal square root
transformation of sum of squared error and is a measurement of the similarity
in the percentage (%) dissolution between the two curves.
o
n = no. of withdrawal points
o
Rt = % dissolved of ref. At time t
o
Tt = % dissolved of test At time t
Determine
dissolution profile of 12 units of each of the test and ref. Pdt.
A
dissolution profile comparison between pre-change and post-change products for
SUPAC related changes, or with different strengths, helps assure similarity in
product performance.
In
dissolution profile comparisons, especially to assure similarity in product
performance, regulatory interest is in knowing how similar the two curves are,
and to have a measure which is more sensitive to large differences at any particular
time point. For this reason, the f2 comparison has been the focus in Agency
guidances.
Using
mean dissolution values for both curves at each time intervals and calculate Æ’1
and Æ’2.
Æ’1
close to 0 and Æ’2 close to 100 are considered as similar profiles.
Generally
Æ’1 is between 0-15 and Æ’2 is between 50-100 ensures equivalence.
Disadvantages:
•
Similarity factor(Æ’2) is dependent on sampling
scheme from apparatus means selection and determination of no. of dissolution
time points. So that when we have same
ref. And test pdt., but if no . And time of dissolution time points are differ,
they show different results.
Example:
Comparison
of dissolution profile of PURE IBU with different formulation of IBUPROFEN.
Diff.
Formulation of IBU are
o
IBUGESIC
o
BRUFEN
o
IBUPROFEN
Then
calculate dissimilarity and similarity factor from data available of the
dissolution of these formulation.
Two
formulations exhibiting the different dissolution profiles.
Data
collected from the dissolution as per following procedure.
Acc.
To equation we have find dissimilarity factor Æ’1 = 46.05 and f2 = 34.57
Results:
PURE IBU and IBUGESIC are of different formulation.
PURE IBU and IBUGESIC are of different formulation.
Discussion:
Because if f1 = 0-15 and f2 = 50-100, it gives similar dissolution profiles between two formulations.
Because if f1 = 0-15 and f2 = 50-100, it gives similar dissolution profiles between two formulations.
Two
formulations exhibiting the similar dissolution profiles.
Data collected from the dissolution as per following procedure.
Data collected from the dissolution as per following procedure.
Acc.
To equation we have find similarity factor Æ’2 = 85.87
and f1 = 11.76
and f1 = 11.76
Results
:
Both
the formulation have similar dissolution profile.
Discussion :
Here
differencial factor Æ’1 = 11.76 and Æ’2 = 85.87
As
per specification if f1 is close to zero and Æ’2 is close to 100 then it is
considered as similar profile.
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