Seminar on dissolution profile comparison

Comparison of dissolution profile by
different methods

Guided by: Presented by:
Jignesh Ahalgama
Dr. R. K. Parikh Maulik Patel
Department of Pharmaceutics and
Sachi Patel
Pharmaceutical Technology
L. M .College of pharmacy
M.Pharm Sem-1(2011-12)
Ahmedabad-380009 Roll no.

Jignesh, Maulik, Sachi/ M.pharm sem-
1/14
1(2011-'12)/ LMCP/ Paper code:910102

Contents….
 Definition
 Objectives
 Important
Different methods used for dissolution
comparison
 Comparison of different methods
 References

Jignesh, Maulik, Sachi/ M.pharm sem- 2/14
1(2011-'12)/ LMCP/ Paper code:910102

Dissolution Profile Comparison
 Definition:
It is graphical representation [in terms of concentration
vs. time] of complete release of A.P.I. 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.

1(2011-'12)/ LMCP/ Paper code:910102

 Objective:
 To Develop invitro-invivo correlation which can help to reduced
costs, speed-up product development and reduced the need of
perform costly bioavailability human volunteer studies.

 To stabilize final dissolution specification for the pharmacological
dosage form

 Establish the similarity of pharmaceutical dosage forms, for
which composition, manufacture site, scale of manufacture,
manufacture process and/or equipment may have changed within
defined limits.

1(2011-'12)/ LMCP/ Paper code:910102

IMPORTANCE OF DISSOLUTION PROFILE
 Dissolution profile of an A.P.I. reflects its release pattern under the
selected condition sets. i.e. either sustained release or immediate
release of the formulated formulas.

 For optimizing the dosage formula by comparing the dissolution
profiles of various formulas of the same A.P.I

 Dissolution profile comparison between pre change and post change
products for SUPAC (scale up post approval change ) related changes
or with different strengths, helps to assure the similarity in the
product performance and green signals to bioequivalence.

1(2011-'12)/ LMCP/ Paper code:910102

IMPORTANCE OF DISSOLUTION PROFILE
 FDA has placed more emphasis on dissolution profile comparison in
the field of post approval changes and biowaivers (e.g. Class I drugs
of BCS classification are skipped off these testing for quicker approval
by FDA ).

 The most important application of the dissolution profile is that by
knowing the dissolution profile of particular product of the BRAND
LEADER, we can make appropriate necessary change in our
formulation to achieve the same profile of the BRAND LEADER.

1(2011-'12)/ LMCP/ Paper code:910102

METHODS TO COMPARE DISSOLUTION PROFILE

Graphical method Statistical Model Dependent Model Independent
Analysis method Method

t- Test ANOVA

Zero order First Hixson- Higuchi Weibull Korsemeyar Baker-
order crowell law model model and peppas Lonsdale
model model

Ratio Test Pair Wise Multivariate Index of Rescigno
Procedure Procedure Confidence Region
Procedure
1(2011-'12)/ LMCP/ Paper code:910102

Graphical method
 In this method we plot graph of Time V/S concentration of solute
(drug) in the dissolution medium or biological fluid.

 The shape of two curves is compared for comparison of dissolution
pattern and the concentration of drug at each point is compared for
extent of dissolution.

 If two or more curves are overlapping then the dissolution profile is
comparable.

 If difference is small then it is acceptable but higher differences
indicate that the dissolution profile is not comparable.

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Graphical comparison of dissolution
profile

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Statistical Analysis
1. Student’s t-Test:
Following testes are commonly used…
a) One sample t-test
b) Paired t-test
c) Unpaired t-test
 Equation for the t is,
Where,X=sample mean,
N=sample size,
S=sample standard deviation ,
µ=population standard deviation ,

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2. ANOVA method (ANALYSIS OF VARIENCE)
 This test is generally applied to different groups of data. Here we
compare the variance of different groups of data and predict weather
the data are comparable or not.
 Minimum three sets of data are required. Here first we have to find
the variance within each individual group and then compare them
with each other.
Steps to perform ANOVA : There are five steps
1) calculate the total sum of the squares of variance (SST)
SST = Σxij2 – T2/N;
xij denote the observation
T2/N is known as correction factor (C.F.)
2) calculate the variance between the samples
SSC = (ΣCj2/h) – T2/N
Where Cj = sum of jth column & h = No. of rows.
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3) Calculate the variance within the samples
SSE = SST – SSC

4) calculate the F-Ratio
Fc= (SSC / k-1)/ (SSE/ N-k)
k-1= Degree of Freedom

5) Compare Fc calculated with the FT (table value)

If Fc< FT, accepted H0. If H0 is accepted, it can be concluded
that the difference is not significance and hence could have
arisen due to fluctuations of random sampling.

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All the information about tahe analysis of variance is summarized
in the following ANOVA table:

Sources of Sum of Degree of Mean Variance
Variation Square Freedom square Ratio of MSC = Mean sum of
(SS) (d.f.) (M.S.) F squares between
Between SS k-1 MSC MSC/MS samples
the C = E MSE = Mean sum of
Samples SS squares within samples
C/
k-
1
Within the SS N-k MSE
Samples E =
SS
E/
N-
k
Total SS N-1
T

1(2011-'12)/ LMCP/ Paper code:910102

Model dependent methods

1) Zero order kinetics (osmotic system ,transdermal system)
 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)i.e.,
A0-At = kt
Where ,A0 = initial amount of drug in the dosage form;
At = amount of drug in the dosage form at time‘t’
k = proportionality constant
 This release is achieved by making:-
Reservoir Diffusion systems
Osmotically Controlled Devices
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2) First order kinetics (Water soluble drugs in porous matrix)

 Using Noyes Whitney’s equation, the rate of loss of drug from dosage
form (dA/dt) is expressed as;
-dA/dt = k (Xs – X)
Assuming that,
sink conditions = dissolution rate limiting step for in-vitro study
absorption = dissolution rate limiting step for in-vivo study.
Then (1) turns to be:
-dA/dt = k (Xs ) = constant
So it becomes,
A = Ao × e-kt

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1(2011-'12)/ LMCP/ Paper code:910102

3) Hixon – Crowell model (Erodible matrix formulation)
 To evaluate the drug release with changes in the surface area and the
diameter of the particles /tablets
 The rate of dissolution depends on the surface of solvent - the larger
is area the faster is dissolution.
 Hixon-Crowell in 1931 ( Hixon and Crowell, 1931) recognized that the
particle regular area is proportional to the cubic root of its volume,
desired an equation as
Mo1/3-M1/3 = K × t
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’
 This model is called as “Root law”.

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4) Higuchi model (Diffusion matrix formulation)
 Higuchi in 1961 developed models to study the release of water
soluble and low soluble drugs incorporated in semisolid and solid
matrices.
 To study the dissolution from a planer system having a homogeneous
matrix the relation obtained was;
A = [D (2C – Cs)Cs × t]1/2
Where A is the amount of drug released in time‘t’ per unit area,
C is the initial drug concentration,
Cs is the drug solubility in the matrix media
D is the diffusivity of drug molecules in the matrix substance.

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5) Weibull model (Erodible matrix formulation)

m = 1 – e [- (t – T1)b/a]
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.
b > 1, the A.P.I. release rate is slow initially followed by an
increase in release rate

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1(2011-'12)/ LMCP/ Paper code:910102

6) Baker-Lonsdale model(microspheres , microcapsules)
 In 1974 Baker-Lonsdale (Baker and Lonsdale, 1974) developed the
model from the Higuchi model and describes the controlled release
of drug from a spherical matrix that can be represented as:

3/2 [1-(1-At/A∞)2/3]-At/A∞ = (3DmCms) / (r02C0) X t
Where At is the amount of drug released at time’t’
A∞ is the amount of drug released at an infinite time,
Dm is the diffusion coefficient,
Cms is the drug solubility in the matrix,
ro is the radius of the spherical matrix
Co is the initial concentration of the drug in the matrix.

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1(2011-'12)/ LMCP/ Paper code:910102

7) Korsmeyer-Peppas model (Swellable polymeric devices)
 The KORSEMEYAR AND PEPPAS empirical expression relates the function
of time for diffusion controlled mechanism.
It is given by the equation :
Mt/Ma = Ktn

where Mt / Ma is function of drug released
t = time
K=constant includes structural and geometrical characteristics of
the dosage form
n= release component which is indicative of drug release
mechanism
where , n is diffusion exponent.
If n= 1 , the release is zero order .
n = 0.5 the release is best described by the Fickian diffusion
0.5 < n < 1 then release is through amnomalus diffusion or case
two diffusion.
In this model a plot of present drug release versus time is liner.
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1(2011-'12)/ LMCP/ Paper code:910102

Guidance for Industry
To allow application of these models to comparison of dissolution
profiles, the following procedures are suggested:

1. Select the most appropriate model for the dissolution profiles from the
standard, prechange, approved batches. A model with no more than three
parameters (such as linear, quadratic, logistic, probit, and Weibull models)
is recommended.
2. Using data for the profile generated for each unit, fit the data to the most
appropriate model.
3. A similarity region is set based on variation of parameters of the fitted
model for test units (e.g., capsules or tablets) from the standard approved
batches.
4. Calculate the MSD (Multivariate Statistical Distance) in model parameters
between test and reference batches.
5. Estimate the 90% confidence region of the true difference between the two
batches.
6. Compare the limits of the confidence region with the similarity region. If the
confidence region is within the limits of the similarity region, the test
batch is considered to have a similar dissolution profile to the reference
batch. Jignesh, Maulik, Sachi/ M.pharm sem-
21/8
1(2011-'12)/ LMCP/ Paper code:910102

MODEL INDEPENDENT METHODS
1. Ratio test procedure
ratio of % dissolved ratio of area under the ratio of mean dissolution
dissolution curves (AUC) time (MDT)
Standard Error of mean
ratio (SET/R) can be
determine by Delta Trapezoidal Formula
method. rule method

where, Where,
SET/R is the SE of the t = dissolution sample
mean ratio of test to
number (e.g. t=1 for 5 min.
standard.
XT is the mean percentage t=2 for 10 min. data)
dissolved of test. n = total number of
XS is the mean percentage dissolution sample time.
dissolved of standard. tmid = the time at mid point
between t and t – 1
M = addition amount of
drug dissolved between t
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1(2011-'12)/ LMCP/ Paper code:910102
and t –1

2. Paired Wise Procedure
 DIFFERENCE FACTOR (f1) & SIMILARITY FACTOR (f2)
 The difference factor (f1) as defined by FDA calculates the %
difference between 2 curves at each time point and is a
measurement of the relative error between 2 curves.

 n 
  Rt  Tt  
f1 =   t 1  × 100
 n 


 Rt 

 t 1 

where, n = number of time points
Rt = % dissolved at time t of reference product (pre change)
Tt = % dissolved at time t of test product (post change)

23/7
1(2011-'12)/ LMCP/ Paper code:910102

 The similarity factor (f2) 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

 0.5

 1   100
n
f2 = 50 × log 1  wt ( Rt Tt )
 


n r 1  


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Guidance for Industry
• A specific procedure to determine difference and similarity factors is as
follows:
1. Determine the dissolution profile of two products (12 units each) of the
test (postchange) and reference (prechange) products.
2. Using the mean dissolution values from both curves at each time
interval, calculate the difference factor (f1 ) and similarity factor (f2)
using the above equations.
3. For curves to be considered similar, f1 values should be close to 0, and
f2 values should be close to 100. Generally, f1 values up to 15 (0-15)
and f2 values greater than 50 (50-100) ensure equivalence of the two
curves and thus, of the performance of the test (postchange) and
reference (prechange) products.
 This model independent method is most suitable for dissolution profile
comparison when three to four or more dissolution time points are
available.
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The following recommendations should also be considered:

 The dissolution measurements of the test and reference batches should
be
made under exactly the same conditions.
 The dissolution time points for both the profiles should be the same
(e.g., 15, 30, 45, 60 minutes).
 The reference batch used should be the most recently manufactured
prechange product.
 Only one measurement should be considered after 85% dissolution of
both the products.
 To allow use of mean data, the percent coefficient of variation at the
earlier
time points (e.g., 15 minutes) should not be more than 20%, and at
other time points should not be more than 10%.
 The mean dissolution values for R can be derived either from
(1) last prechange (reference) batch or
(2) last two or more consecutively manufactured prechange
batches. Jignesh, Maulik, Sachi/ M.pharm sem-
26/7
1(2011-'12)/ LMCP/ Paper code:910102

3. MULTIVARIATE CONFIDENCE REGION
PROCEDURE
 In the cases where within batch variation is more than 15% CV, a
Multivariate model independent procedure is more suitable for dissolution
profile comparison.
 It is also known as BOOT STRAP Approach.
 The following steps are suggested.
 Determine the Similarity limits in terms of Multivariate Statistical Distance
(MSD) based on interbatch differences in dissolution from reference
(standard approved) batches.
 Estimate the MSD between the test and reference mean dissolutions.
 Estimate 90% confidence interval of true MSD between test and reference
batches.
 Compare the upper limit of the confidence interval with the similarity limit.
The test batch is considered similar to the reference batch if the upper limit
of the confidence interval is less than or equal to the similarity limit.
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Research Article
DEVELOPMENT OF PROPRANOLOL HYDROCHLORIDE MATRIX TABLETS: AN
INVESTIGATION ON EFFECTS OF COMBINATION OF HYDROPHILIC AND
HYDROPHOBIC MATRIX FORMERS USING MULTIPLE COMPARISON
ANALYSIS
 Analysis of release profiles

• The rate and mechanism of release of Propranolol Hydrochloride from the
prepared matrix tablets were analyzed by fitting the dissolution data into
the zero-order, first-order, Higuchi model and Korsmeyer-Peppas model.

• Tablets were subjected to In-Vitro drug release in 0.1 N HCl (pH 1.2) for first
2 hours followed by phosphate buffer (pH 6.8) for remaining hours. In-vitro
drug release data were fitting to Higuchi and Korsmeyer equation indicated
that diffusion along with erosion could be the mechanism of drug release.
1(2011-'12)/ LMCP/ Paper code:910102

Composition of Sustain Release Matrix Tablets of
Propranolol hydrochloride (80 mg)
Formulation Ingredients (mg/tablet)

Propranolol HPMC (mg) Ethyl Cellulose MCC (mg) TALC (mg)
HCl (mg) (mg)
F1 80 20 - 95 5

F2 80 40 - 75 5

F3 80 60 - 55 5

F4 80 - 20 95 5

F5 80 - 40 75 5

F6 80 - 60 55 5

F7 80 20 20 75 5
1(2011-'12)/ LMCP/ Paper code:910102

Kinetics of Drug Release from Propranolol hydrochloride
Matrix Tablets
Formula Drug release kinetics, Coefficient of Korsmeyer Higuchi Release t1/2
tion determination ‘r2’ model- Rate exponent (hr)
diffusion Constant
Zero First order Higuchi
exponent (K)
Order equation
F1 0.961 0.913 0.962 0.995 6.278 0.575 0.73

F2 0.943 0.911 0.993 0.995 4.769 0.545 1.71

F3 0.916 0.814 0.984 0.999 4.510 0.537 3.21

F4 0.944 0.931 0.982 0.991 4.786 0.590 2.68

F5 0.899 0.809 0.990 0.986 3.885 0.665 3.63

F6 0.954 0.948 0.997 0.987 2.932 0.799 4.63

F7 0.937 0.924 0.991 Maulik, Sachi/ M.pharm sem-
Jignesh,
0.997 3.465 0.540 4.04
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Conclusion From In-Vitro Study
 Zero order, First order and Higuchi equation fail to explain drug
release mechanism due to swelling (upon hydration) along with
gradual erosion of the matrix. Therefore, the dissolution data was
also fitted to the well-known exponential equation (Peppas
equation), which is often used to describe the drug release behavior
from polymeric system.

 It was observed that combination of both the polymers- HPMC and
Ethyl cellulose exhibited the best release profile and able to sustain
the drug release for prolong period of time. Swelling study suggested
that when the matrix tablets come in contact with the dissolution
medium, they take up water and swells, forming a gel layer around
the matrix and simultaneously erosion also takes place.

1(2011-'12)/ LMCP/ Paper code:910102

Comparison of different methods
 Evident from the literature that no single approach is widely accepted
to determine if dissolution profiles are similar.
 Statistical methods are more discriminative and provide detailed
information about dissolution data.
 Model-dependent methods investigate the mathematical equations
that describe the release profile in function of some parameters related
to the pharmaceutical dosage forms so the quantitative interpretation
of the values is easier. These methods seem to be useful in the
formulation-development stage.
 The f1 and f2 are sensitive to the number of dissolution time points and
the basis of the criteria for deciding the difference or similarity between
dissolution profiles is unclear.
 Model independent methods were found to be very simple, but
discrimination between dissolution profiles can be found using model
dependent approach.

1(2011-'12)/ LMCP/ Paper code:910102

 Gompertz and second-order models were rejected, however,
because the %Rmax estimates for these models were
significantly greater than the measured potency of the drug
product batch .
 These models had relatively low Model Selection
Criterion (MSC) values.
 The MSC is a modified form of the Akaike Information Criterion
(AIC), which is widely used to select the best-fitting model when
those under consideration do not contain the same number of
parameters .
 The model with the largest MSC value is considered the most
appropriate one.

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References
 Biopharmaceutics and Pharmacokinetics by D. M. Brahmankar, 2nd
edition 2009, page no. 432 to 434
 M. George, I. V. Grass, J. R. Robinson. Sustained and controlled release
delivery systems, Marcel Dekker, NY, 124 (1978)
 Mathematical models of dissolution- Master’s thesis by Jakub ˘
Cupera May 4, 2009 Masarykova Univerzita
 By Madhusmruti Khandai Research article of International Journal of
Pharmaceutical Sciences Review and Research Volume 1, Issue 2,
March – April 2010; Article 001
 By T Soni, N Chotai Assessment of dissolution profile of marketed
aceclofenac formulations of Journal of Young Pharmacist 2010;
Volume-2: Page no.21-6
 Release kinetics of modified pharmaceutical dosage forms: a review
article of J. Pharmaceutical Sciences Volume1: 30 - 35, 2007

1(2011-'12)/ LMCP/ Paper code:910102

References
 Guidance for Industry Dissolution Testing of Immediate Release Solid
Oral Dosage Forms U.S. Department of Health and Human Services
Food and Drug Administration Center for Drug Evaluation and
Research (CDER), August-2011
 By INDRAJEET D. GONJARI, AMRIT B. KARMARKAR, AVINASH H.
HOSMANI - Research Article Journal of Nanomaterials and
Biostructures Vol. 4, No. 4, December 2009, p. 651 - 661
 By Jakub Cuperaab, Petr Lanskya- “Homogeneous diffusion layer
model of dissolution incorporating the initial transient phase” -
International Journal of Pharmaceutics, 416 (2011) 35– 42
 Seminar on Comparison of dissolution profile by Model independent
& Model dependent methods by SHWETA IYER
 International Journal of Pharmaceutical Science Vol-1, Issue-1, page
no.57-64, 2010

1(2011-'12)/ LMCP/ Paper code:910102

Seminar on dissolution profile comparison

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