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Presented by:
Karanam Ranjith Kumar
CONTENTS:
 INTRODUCTION
 IMPORTANCE OF DISSOLUTION PROFILE COMPARISON
 OBJECTIVE OF DISSOLUTION PROFILE COMPARISON
 METHODS USED TO COMPARE DISSOLUTION PROFILE
 GRAPHICAL METHOD
 STASTITICAL METHOD

 MODEL DEPENDENT METHODS
 MODEL INDEPENDENT METHODS
 CONCLUSION

 REFERENCES
2
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
Importance of dissolution profile Comparison :


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



FDA has placed more emphasis on dissolution profile comparison in the
field of post approval changes.



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.

4


Objective of dissolution profile Comparison :
 To Develop in-vitro in-vivo correlation which can help to reduce
costs, speed-up product development and reduce the need to perform
costly bioavailability human volunteer studies.

 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.

5
METHODS TO COMPARE DISSOLUTION PROFILE
Graphical
method

Statistical
method
t- Test

Model independent method
(Pair Wise Procedure)

ANOVA

f1 and f2 comparison

Model dependent methods

Zero order

First order

Hixsoncrowell law

Higuchi
model

Korsemeyar and
peppas model

6
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.

7
Statistical Analysis:

Calculated ‘t’ value is compared with tabulated value of ‘t’ if the
calculated value exceeds the tabulated value , then the null hypothesis
should be rejected and vice versa.

8
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 whether
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.
9
 ANOVA table.
Source of
variance

Between columns
Between rows
Within group/
error

Total



S2

df

M2

F value

No. of
columns-1

No. of rows -1
dfbetween
columns×
dfbetween rows
(No. of columns
×No. of rows)-1

Compare the calculated F- value with the tabulated value at particular degrees
of freedom and level of significance. If the calculated value is less than the
tabulated value, then degrees of variance is insignificant.
10
Model dependent methods:
 Zero order kinetics:
Qt = Q0 + K0t
Where,
Qt is the amount of drug dissolved in time t
Q0 is the initial amount of drug in the solution
K0 is the zero order release constant expressed in units of concentration/time.
Plot: Cumulative amount of drug released versus time.

Applications: Transdermal systems, as well as matrix tablets with low
solubility drugs in coated forms, osmotic systems, etc.
11
Zero order Plot:
100

cumulative percent of drug released

90

80

70

60

50

TEST

R² = 0.959

REFERENCE

40

R² = 0.965

30

20

10

0
0

5

10

Time (h)

15

20

25

12
 First order model:
log C = log C0 - Kt / 2.303
Where
C0 is the initial concentration of drug,

K is the first order rate constant, and
t is the time.

Plot: log cumulative percentage of drug remaining vs. time which would
yield a straight line with a slope of -K/2.303.

Application: This relationship can be used to describe the drug dissolution
in pharmaceutical dosage forms such as those containing water soluble drugs
in porous matrices.

13
First order plot:
101

100

log percent ARR



R² = 0.933

99

98

97

96

95

94
0

5

10

15

20

25

30

Time (h)
14
 Higuchi model (Diffusion matrix formulation)

15
Higuchi Plot:
100

90

cumulative percent of drug released

80

70

60

50

R² = 0.990

40

TEST

REFERENCE

30

R² = 0.992

20

10

0
0

1

2

3

4

5

6

√Time

16
17
 Korsmeyer - Peppas model:
• The KORSEMEYER AND PEPPAS described this method..
It is given by the equation :
Mt/Ma = Ktn
where Mt / Ma is fraction 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 anomalous diffusion or case
two diffusion. In this model a plot of percent drug release versus time
is linear.
18
Some models with linear equation for graphical presentation:
Model

Zero order

First order

Linear equation

Hixon crowell

Mt/Ma = Ktn

On Y-axis

Time

Cumulative
amount
of drug released

Time

log cumulative
percentage
of drug
cumulative
percentage
drug release

Time

log C = log C0 - Kt / 2.303

On X-axis

Square root of
Time

Qt = Q0 + K0t

Higuchi model

KorsmeyerPeppas model

Plot

cube root of
drug percentage
remaining

Log Time

log cumulative
percentage drug
release

19


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
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
Advantages:
(1) They are easy to compute
(2) They provide a single number to describe the comparison of
dissolution profile data.
Disadvantages
(1) The values of f1 and f2 are sensitive to the number of dissolution
time point used.
(2) If the test and reference formulation are inter changed , f2 is
unchanged but f1 Is not yet differences between the two mean profile
remain the same.
(3) The basis of the criteria for deciding the difference or similarity
between dissolution profile is unclear.
22
conclusion:
 Graphical method is first step in comparing dissolution profile and it
is easy to implement but it is difficult to make definitive conclusions
from the it.
 Various model dependent methods can be used to compare the
dissolution profile but selecting the model, interpretation of model
parameters and setting similarity limit is difficult.
 f1 and f2 comparison is easy and this is most widely used method to

compare dissolution profiles. This is also recommended by FDA.
by using all the above given models we can compare dissolution
profiles of drugs.
23
References:
1. Hussain L,Ashwini D,Sirish D. Kinetic modeling and dissolution

profiles comparison: an overview.Int J Pharm Bio Sci 2013; 4(1): 728
- 737.
2. Thomas O’H, Adrian D, Jackie B and John D. A review of methods
used to compare dissolution profile data. PSTT 1998; 1(5): 214-223.

24
3.

Jignesh A,Maulik P,Sachi P . Comparison of dissolution profile by
Model

independent

&

Model

dependent

methods.

http://pharmaquest.weebly.com/uploads/9/9/4/2/9942916/comparison_
of_dissolution_profile.pdf (accessed 15 November 2013).

4.

U.S. Department of Health and Human Services Food and Drug
Administration

Center

for

Drug

Evaluation

and

Research

(CDER). Guidance for Industry Dissolution Testing of Immediate
Release

Solid

Oral

Dosage

Forms.

http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatory
Information/Guidances/ucm070237.pdf (accessed 15 November 2013).
25
26

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Comparision of dissolution profile

  • 2. CONTENTS:  INTRODUCTION  IMPORTANCE OF DISSOLUTION PROFILE COMPARISON  OBJECTIVE OF DISSOLUTION PROFILE COMPARISON  METHODS USED TO COMPARE DISSOLUTION PROFILE  GRAPHICAL METHOD  STASTITICAL METHOD  MODEL DEPENDENT METHODS  MODEL INDEPENDENT METHODS  CONCLUSION  REFERENCES 2
  • 3. 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
  • 4. Importance of dissolution profile Comparison :  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  FDA has placed more emphasis on dissolution profile comparison in the field of post approval changes.  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. 4
  • 5.  Objective of dissolution profile Comparison :  To Develop in-vitro in-vivo correlation which can help to reduce costs, speed-up product development and reduce the need to perform costly bioavailability human volunteer studies.  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. 5
  • 6. METHODS TO COMPARE DISSOLUTION PROFILE Graphical method Statistical method t- Test Model independent method (Pair Wise Procedure) ANOVA f1 and f2 comparison Model dependent methods Zero order First order Hixsoncrowell law Higuchi model Korsemeyar and peppas model 6
  • 7. 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. 7
  • 8. Statistical Analysis: Calculated ‘t’ value is compared with tabulated value of ‘t’ if the calculated value exceeds the tabulated value , then the null hypothesis should be rejected and vice versa. 8
  • 9. 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 whether 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. 9
  • 10.  ANOVA table. Source of variance Between columns Between rows Within group/ error Total  S2 df M2 F value No. of columns-1 No. of rows -1 dfbetween columns× dfbetween rows (No. of columns ×No. of rows)-1 Compare the calculated F- value with the tabulated value at particular degrees of freedom and level of significance. If the calculated value is less than the tabulated value, then degrees of variance is insignificant. 10
  • 11. Model dependent methods:  Zero order kinetics: Qt = Q0 + K0t Where, Qt is the amount of drug dissolved in time t Q0 is the initial amount of drug in the solution K0 is the zero order release constant expressed in units of concentration/time. Plot: Cumulative amount of drug released versus time. Applications: Transdermal systems, as well as matrix tablets with low solubility drugs in coated forms, osmotic systems, etc. 11
  • 12. Zero order Plot: 100 cumulative percent of drug released 90 80 70 60 50 TEST R² = 0.959 REFERENCE 40 R² = 0.965 30 20 10 0 0 5 10 Time (h) 15 20 25 12
  • 13.  First order model: log C = log C0 - Kt / 2.303 Where C0 is the initial concentration of drug, K is the first order rate constant, and t is the time. Plot: log cumulative percentage of drug remaining vs. time which would yield a straight line with a slope of -K/2.303. Application: This relationship can be used to describe the drug dissolution in pharmaceutical dosage forms such as those containing water soluble drugs in porous matrices. 13
  • 14. First order plot: 101 100 log percent ARR  R² = 0.933 99 98 97 96 95 94 0 5 10 15 20 25 30 Time (h) 14
  • 15.  Higuchi model (Diffusion matrix formulation) 15
  • 16. Higuchi Plot: 100 90 cumulative percent of drug released 80 70 60 50 R² = 0.990 40 TEST REFERENCE 30 R² = 0.992 20 10 0 0 1 2 3 4 5 6 √Time 16
  • 17. 17
  • 18.  Korsmeyer - Peppas model: • The KORSEMEYER AND PEPPAS described this method.. It is given by the equation : Mt/Ma = Ktn where Mt / Ma is fraction 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 anomalous diffusion or case two diffusion. In this model a plot of percent drug release versus time is linear. 18
  • 19. Some models with linear equation for graphical presentation: Model Zero order First order Linear equation Hixon crowell Mt/Ma = Ktn On Y-axis Time Cumulative amount of drug released Time log cumulative percentage of drug cumulative percentage drug release Time log C = log C0 - Kt / 2.303 On X-axis Square root of Time Qt = Q0 + K0t Higuchi model KorsmeyerPeppas model Plot cube root of drug percentage remaining Log Time log cumulative percentage drug release 19
  • 20.  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
  • 21. 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
  • 22. Advantages: (1) They are easy to compute (2) They provide a single number to describe the comparison of dissolution profile data. Disadvantages (1) The values of f1 and f2 are sensitive to the number of dissolution time point used. (2) If the test and reference formulation are inter changed , f2 is unchanged but f1 Is not yet differences between the two mean profile remain the same. (3) The basis of the criteria for deciding the difference or similarity between dissolution profile is unclear. 22
  • 23. conclusion:  Graphical method is first step in comparing dissolution profile and it is easy to implement but it is difficult to make definitive conclusions from the it.  Various model dependent methods can be used to compare the dissolution profile but selecting the model, interpretation of model parameters and setting similarity limit is difficult.  f1 and f2 comparison is easy and this is most widely used method to compare dissolution profiles. This is also recommended by FDA. by using all the above given models we can compare dissolution profiles of drugs. 23
  • 24. References: 1. Hussain L,Ashwini D,Sirish D. Kinetic modeling and dissolution profiles comparison: an overview.Int J Pharm Bio Sci 2013; 4(1): 728 - 737. 2. Thomas O’H, Adrian D, Jackie B and John D. A review of methods used to compare dissolution profile data. PSTT 1998; 1(5): 214-223. 24
  • 25. 3. Jignesh A,Maulik P,Sachi P . Comparison of dissolution profile by Model independent & Model dependent methods. http://pharmaquest.weebly.com/uploads/9/9/4/2/9942916/comparison_ of_dissolution_profile.pdf (accessed 15 November 2013). 4. U.S. Department of Health and Human Services Food and Drug Administration Center for Drug Evaluation and Research (CDER). Guidance for Industry Dissolution Testing of Immediate Release Solid Oral Dosage Forms. http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatory Information/Guidances/ucm070237.pdf (accessed 15 November 2013). 25
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