Skip to main content
UploadLanguage (EN)Support
BusinessMobileSocial MediaMarketingTechnologyArt & PhotosCareerDesignEducationPresentations & Public SpeakingGovernment & NonprofitHealthcareInternetLawLeadership & ManagementAutomotiveEngineeringSoftwareRecruiting & HRRetailSalesServicesScienceSmall Business & EntrepreneurshipFoodEnvironmentEconomy & FinanceData & AnalyticsInvestor RelationsSportsSpiritualNews & PoliticsTravelSelf ImprovementReal EstateEntertainment & HumorHealth & MedicineDevices & HardwareLifestyle
JF
Uploaded byJessica Fernandes
PPTX, PDF36,399 views

Similarity and difference factors of dissolution

The document discusses the importance and methodology of comparing dissolution profiles of pharmaceutical dosage forms to assess the release patterns of active pharmaceutical ingredients (APIs). It outlines both graphical and statistical methods for comparison, including the use of model-dependent and model-independent approaches such as f1 and f2 factors. The conclusion emphasizes the utility of these methods in ensuring product similarity and regulatory compliance, particularly in light of FDA recommendations.

Education◦
Similarity and Difference Factors in Dissolution Studies By: Jessica Fernandes Reg. No. 150617004 Department of Pharmaceutics Guided By Mr. Lalit Kumar Assistant Professor-senior scale Department of Pharmaceutics MCOPS, Manipal
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.  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 ANOVA Zero order First order Hixson- crowell law Higuchi model Korsemeyar and peppas model f1 and f2 comparison Model independent method (Pair Wise Procedure) Model dependent methods
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 1. Student’s t-Test Following tests are commonly used… a) Paired t-test b) Unpaired t-test 𝑡 = 𝐷 𝑆𝐸 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 Variance)  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 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.
10 R² = 0.9652 0 10 20 30 40 50 60 70 80 90 100 0 5 10 15 20 25 cumulativepercentofdrugreleased Time (h) Zero order Plot:
11 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 concentration 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.
12 R² = 0.9333 94 95 96 97 98 99 100 101 0 5 10 15 20 25 30 Logconcentration Time (h) First order plot
13 Higuchi model (Diffusion matrix formulation) • This is given by Higuchi. 𝑄 = 𝐾 𝑇 Where Q is the amount of drug released in time‘t’ per unit area, K is higuchi constant T is time in hr. Plot: The data obtained is to be plotted as cumulative percentage drug release versus Square root of time. Application: modified release pharmaceutical dosage forms, transdermal systems and matrix tablets with water soluble drugs.
15  Hixson-Crowell model Hixson and Crowell described this W0 1 3 − Wt 1 3 = Kt Where W0 is the initial amount of drug Wt is the remaining amount of drug at time t . Plot: Data is to be plotted as cube root of drug percentage remaining in matrix versus time. Application: This expression applies to pharmaceutical dosage form such as tablets, where the dissolution occurs in planes that are parallel to the drug surface if the tablet dimensions diminish proportionally in such a manner that the initial geometrical form keeps constant all the time.
17  Korsmeyer - Peppas model The KORSEMEYER AND PEPPAS described this method.. It is given by the equation : Mt /M∞ = Ktn where Mt / M ∞ 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.
19 Model Independent Approach Moore and Flanner proposed a model independent mathematical approach to compare the dissolution profile using two factors, f1 and f2. 1. Difference 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=1 n |R-T|] / [Σ t=1 n 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.
Applications • F1 is specially used to compare two dissolution profiles, being necessary to consider one of them as the reference standard product. • It can measure the percent of error between two curves over all time points.
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=1 n (R-T) 2]-0.5 ×100 2. Similarity Factor PARAMETERS VALUES Difference Factor (f1) 0 – 15 Similarity Factor (f2) 50-100
Applications • This method is more appropriate when more than three or four dissolution time points are available. • The f2 may become invariant with respect to the location change and the consequence of failure to take into account the shape of the curve and the unequal spacing between sampling time points lead to errors. • Nevertheless, with a slight modification in the statistical analysis, similarity factor would definitely serves as an efficient tool for reliable comparison of dissolution profiles.
23 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 points used. 2. The basis of the criteria for deciding the difference or similarity between dissolution profile is unclear.
24 Conclusion  Graphical method is first step in comparing dissolution profile and it is easy to implement but it is difficult to make definitive conclusions.  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 profile of drug.
25 References 1. Hussain L, Ashwini D, Sirish D. Kinetic modelling 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.
26 3. U.S. Department of Health and Human Services Food and Drug Administration Centre for Drug Evaluation and Research (CDER). Guidance for industry dissolution testing of immediate release solid oral dosage forms. http://www.fda.gov/downloads/Drugs/GuidanceComplianceR egulatoryInformation/Guidances/ucm070237.pdf. Accessed on 15 November 2015. 4. 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/com parison_of_dissolution_profile.pdf. Accessed on 15 November 2015.
ThankYou