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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.




                            Jignesh, Maulik, Sachi/ M.pharm sem-      3/14
                           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.




                           Jignesh, Maulik, Sachi/ M.pharm sem-   4/14
                          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.



                            Jignesh, Maulik, Sachi/ M.pharm sem-     5/14
                           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.




                            Jignesh, Maulik, Sachi/ M.pharm sem-    6/14
                           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
                                         Jignesh, Maulik, Sachi/ M.pharm sem-                        7/14
                                        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.

                            Jignesh, Maulik, Sachi/ M.pharm sem-
                                                                        8/2
                           1(2011-'12)/ LMCP/ Paper code:910102
Graphical comparison of dissolution
             profile




            Jignesh, Maulik, Sachi/ M.pharm sem-
                                                   9/2
           1(2011-'12)/ LMCP/ Paper code:910102
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 ,



                        Jignesh, Maulik, Sachi/ M.pharm sem-
                                                               10/4
                       1(2011-'12)/ LMCP/ Paper code:910102
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.
                          Jignesh, Maulik, Sachi/ M.pharm sem-
                                                                 11/4
                         1(2011-'12)/ LMCP/ Paper code:910102
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.


                    Jignesh, Maulik, Sachi/ M.pharm sem-
                                                           12/4
                   1(2011-'12)/ LMCP/ Paper code:910102
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

                                    Jignesh, Maulik, Sachi/ M.pharm sem-                            13/4
                                   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
                            Jignesh, Maulik, Sachi/ M.pharm sem-
                                                                   14/8
                           1(2011-'12)/ LMCP/ Paper code:910102
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




                          Jignesh, Maulik, Sachi/ M.pharm sem-
                                                                 15/8
                         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”.

                           Jignesh, Maulik, Sachi/ M.pharm sem-
                                                                  16/8
                          1(2011-'12)/ LMCP/ Paper code:910102
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.




                          Jignesh, Maulik, Sachi/ M.pharm sem-
                                                                 17/8
                         1(2011-'12)/ LMCP/ Paper code:910102
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



                           Jignesh, Maulik, Sachi/ M.pharm sem-
                                                                  18/8
                          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.


                            Jignesh, Maulik, Sachi/ M.pharm sem-
                                                                    19/8
                           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.
                               Jignesh, Maulik, Sachi/ M.pharm sem-
                                                                         20/8
                           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
                                                                                       22
                               Jignesh, Maulik, Sachi/ M.pharm sem-
                              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)

                              Jignesh, Maulik, Sachi/ M.pharm sem-
                                                                     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                
                                                      




                        Jignesh, Maulik, Sachi/ M.pharm sem-
                                                               24/7
                       1(2011-'12)/ LMCP/ Paper code:910102
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.
                             Jignesh, Maulik, Sachi/ M.pharm sem-
                                                                       25/7
                            1(2011-'12)/ LMCP/ Paper code:910102
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.
                              Jignesh, Maulik, Sachi/ M.pharm sem-
                                                                         27/7
                             1(2011-'12)/ LMCP/ Paper code:910102
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.
                                Jignesh, Maulik, Sachi/ M.pharm sem-        28/14
                               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
                             Jignesh, Maulik, Sachi/ M.pharm sem-                29/14
                            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
                                                                                            30/14
                                 1(2011-'12)/ LMCP/ Paper code:910102
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.

                           Jignesh, Maulik, Sachi/ M.pharm sem-   31/14
                          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.

                            Jignesh, Maulik, Sachi/ M.pharm sem-     32/14
                           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.



                           Jignesh, Maulik, Sachi/ M.pharm sem-
                                                                    33/14
                          1(2011-'12)/ LMCP/ Paper code:910102
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

                            Jignesh, Maulik, Sachi/ M.pharm sem-    34/14
                           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

                           Jignesh, Maulik, Sachi/ M.pharm sem-   35/14
                          1(2011-'12)/ LMCP/ Paper code:910102

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Seminar on dissolution profile comparison

  • 1. 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
  • 2. 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
  • 3. 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. Jignesh, Maulik, Sachi/ M.pharm sem- 3/14 1(2011-'12)/ LMCP/ Paper code:910102
  • 4.  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. Jignesh, Maulik, Sachi/ M.pharm sem- 4/14 1(2011-'12)/ LMCP/ Paper code:910102
  • 5. 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. Jignesh, Maulik, Sachi/ M.pharm sem- 5/14 1(2011-'12)/ LMCP/ Paper code:910102
  • 6. 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. Jignesh, Maulik, Sachi/ M.pharm sem- 6/14 1(2011-'12)/ LMCP/ Paper code:910102
  • 7. 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 Jignesh, Maulik, Sachi/ M.pharm sem- 7/14 1(2011-'12)/ LMCP/ Paper code:910102
  • 8. 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. Jignesh, Maulik, Sachi/ M.pharm sem- 8/2 1(2011-'12)/ LMCP/ Paper code:910102
  • 9. Graphical comparison of dissolution profile Jignesh, Maulik, Sachi/ M.pharm sem- 9/2 1(2011-'12)/ LMCP/ Paper code:910102
  • 10. 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 , Jignesh, Maulik, Sachi/ M.pharm sem- 10/4 1(2011-'12)/ LMCP/ Paper code:910102
  • 11. 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. Jignesh, Maulik, Sachi/ M.pharm sem- 11/4 1(2011-'12)/ LMCP/ Paper code:910102
  • 12. 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. Jignesh, Maulik, Sachi/ M.pharm sem- 12/4 1(2011-'12)/ LMCP/ Paper code:910102
  • 13. 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 Jignesh, Maulik, Sachi/ M.pharm sem- 13/4 1(2011-'12)/ LMCP/ Paper code:910102
  • 14. 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 Jignesh, Maulik, Sachi/ M.pharm sem- 14/8 1(2011-'12)/ LMCP/ Paper code:910102
  • 15. 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 Jignesh, Maulik, Sachi/ M.pharm sem- 15/8 1(2011-'12)/ LMCP/ Paper code:910102
  • 16. 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”. Jignesh, Maulik, Sachi/ M.pharm sem- 16/8 1(2011-'12)/ LMCP/ Paper code:910102
  • 17. 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. Jignesh, Maulik, Sachi/ M.pharm sem- 17/8 1(2011-'12)/ LMCP/ Paper code:910102
  • 18. 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 Jignesh, Maulik, Sachi/ M.pharm sem- 18/8 1(2011-'12)/ LMCP/ Paper code:910102
  • 19. 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. Jignesh, Maulik, Sachi/ M.pharm sem- 19/8 1(2011-'12)/ LMCP/ Paper code:910102
  • 20. 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. Jignesh, Maulik, Sachi/ M.pharm sem- 20/8 1(2011-'12)/ LMCP/ Paper code:910102
  • 21. 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
  • 22. 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 22 Jignesh, Maulik, Sachi/ M.pharm sem- 1(2011-'12)/ LMCP/ Paper code:910102 and t –1
  • 23. 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) Jignesh, Maulik, Sachi/ M.pharm sem- 23/7 1(2011-'12)/ LMCP/ Paper code:910102
  • 24.  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    Jignesh, Maulik, Sachi/ M.pharm sem- 24/7 1(2011-'12)/ LMCP/ Paper code:910102
  • 25. 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. Jignesh, Maulik, Sachi/ M.pharm sem- 25/7 1(2011-'12)/ LMCP/ Paper code:910102
  • 26. 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
  • 27. 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. Jignesh, Maulik, Sachi/ M.pharm sem- 27/7 1(2011-'12)/ LMCP/ Paper code:910102
  • 28. 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. Jignesh, Maulik, Sachi/ M.pharm sem- 28/14 1(2011-'12)/ LMCP/ Paper code:910102
  • 29. 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 Jignesh, Maulik, Sachi/ M.pharm sem- 29/14 1(2011-'12)/ LMCP/ Paper code:910102
  • 30. 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 30/14 1(2011-'12)/ LMCP/ Paper code:910102
  • 31. 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. Jignesh, Maulik, Sachi/ M.pharm sem- 31/14 1(2011-'12)/ LMCP/ Paper code:910102
  • 32. 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. Jignesh, Maulik, Sachi/ M.pharm sem- 32/14 1(2011-'12)/ LMCP/ Paper code:910102
  • 33.  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. Jignesh, Maulik, Sachi/ M.pharm sem- 33/14 1(2011-'12)/ LMCP/ Paper code:910102
  • 34. 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 Jignesh, Maulik, Sachi/ M.pharm sem- 34/14 1(2011-'12)/ LMCP/ Paper code:910102
  • 35. 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 Jignesh, Maulik, Sachi/ M.pharm sem- 35/14 1(2011-'12)/ LMCP/ Paper code:910102