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Seminar on dissolution profile comparison
 

Seminar on dissolution profile comparison

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Which is prepared by sachi patel,ahalgama jignesh and patel maulik and presented by sachi patel and guided by Dr.R.K.Parikh sir.

Which is prepared by sachi patel,ahalgama jignesh and patel maulik and presented by sachi patel and guided by Dr.R.K.Parikh sir.

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    Seminar on dissolution profile comparison Seminar on dissolution profile comparison Presentation Transcript

    • Comparison of dissolution profile by different methodsGuided by: Presented by: Jignesh AhalgamaDr. R. K. Parikh Maulik PatelDepartment of Pharmaceutics and Sachi PatelPharmaceutical TechnologyL. 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 ANOVAZero 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 Analysis1. 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 – SSC4) 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 summarizedin 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 methods1) 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 = ktWhere ,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 × twhere, 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 ofXS 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 ArticleDEVELOPMENT 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 TabletsFormula Drug release kinetics, Coefficient of Korsmeyer Higuchi Release t1/2tion determination ‘r2’ model- Rate exponent (hr) diffusion Constant Zero First order Higuchi exponent (K) Order equationF1 0.961 0.913 0.962 0.995 6.278 0.575 0.73F2 0.943 0.911 0.993 0.995 4.769 0.545 1.71F3 0.916 0.814 0.984 0.999 4.510 0.537 3.21F4 0.944 0.931 0.982 0.991 4.786 0.590 2.68F5 0.899 0.809 0.990 0.986 3.885 0.665 3.63F6 0.954 0.948 0.997 0.987 2.932 0.799 4.63F7 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 drugproduct 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 whenthose under consideration do not contain the same number ofparameters . The model with the largest MSC value is considered the mostappropriate 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