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Dhat Sinhgad Institute of Pharmacy, Narhe, Pune. 5/7/2011 1 Bioequivalence : Bioequivalence 5/7/2011 2 Drug substances in two or more identical dosage forms, reaches the systemic circulation at the same relative rate and to the same relative extent.Bioequivalence: Bioequivalence Pharmacokinetic Studies Key Measurements AUC Area under the concentration- time curve C max Maximum concentration A difference of greater than 20% in C max or the AUC represents a significant difference between the study and reference compounds T max Time to maximum concentration Study Compound Reference Compound Time(Hr) Plasma Concentration (µg\ml) C max T max AUC 5/7/2011 3Why Bioequivalence Study: Why Bioequivalence Study Regulatory requirement. Establishment of p’cokinetic parameters. Study of formulations & process variables. 5/7/2011 4BA-BE Study Protocol: BA-BE Study Protocol 1.Title 2.Study objective 3. Study design 4. Selection of subjects 5. Clinical procedures 6. Ethical Consideration 7. Facilities 8. Data analysis 9. Appendix 5/7/2011 5Study Design: Study Design 1. Parallel Design Formulations administered randomly to two groups of volunteers. Disadvantage Inter subject variability › formulation variability. 5/7/2011 6Slide 7: 2.Cross over design Minimizes inter subject variability. Uses each subject as his or her own control a)Latin Square Cross Over Design 1.Randomised,balanced, complete cross over design. 2.Each subject receives just once each formulation. 3.Each formulation is administered only once in each study period. 5/7/2011 72 way, 3 way ,4 way cross over design : 2 way, 3 way ,4 way cross over design 5/7/2011 8 Two Way Crossover Group No. Subjects in Groups Treatment for Period No. 1 1,2,3,4,5,6 1 2 A B 2 7,8,9,10,11,12 B A Three Way Crossover Group No. Subjects in Group Treatment for Period No. 1 1,2,3,4,5,6 1 2 3 A C B 2 7,8,9,10,11,12 B A C 3 13,14,15,16,17,18 C B AAdvantages of cross over design: Advantages of cross over design Minimizes the effect of inter subject variability. Minimizes carry over effect. Minimizes the time effect on bioavailability since each dosage form is administered in each study period. Requires less number of subjects to get meaningful results. 5/7/2011 9 Disadvantages of cross over design: Disadvantages of cross over design Requires longer time to complete the study. Longer is the t 1/2 greater is time required. Greater the no. of formulations to be evaluated more the time for trials. Subjects drop out due to increased study periods. Medical ethics. 5/7/2011 10b) Balanced Incomplete Block Design (BIBD): b) Balanced Incomplete Block Design (BIBD) Each subject receives n.m.t 2 formulations Each formulation is administered same no. of times Each pair of formulations occurs together in the same number of subjects Four formulations :A,B,C,D Each formulation administered: 6 times Each subject receives: 2 formulations Each pair of formulation: AB,AC,AD,BC,BD,CD occurs together in 2 subjects 5/7/2011 11Balanced Incomplete Block Design: Balanced Incomplete Block Design 5/7/2011 12WASHOUT PERIOD: WASHOUT PERIOD Time interval between two treatments. At least 10 half lives between 2 treatments. Ensure 99.9% elimination, Max carry over: 0.1%. It is a function of t 1/2 and dose of drug administered. No. of wash out periods will depend upon the type of CD and no. of formulations that are to be evaluated. Metabolites should be eliminated. Wash out period: 1 week. 5/7/2011 13Reference & Test Product: Reference & Test Product Before proceeding study both the test product & reference product are tested for in vitro dissolution profile. 5/7/2011 14Selection of Subjects : Selection of Subjects Patients as Volunteers Advantages 1. Mimics actual conditions of usage. 2. Patient may be benefitted from the study. 3. Reflects better therapeutic efficiency of drug. 4. Avoids ethical issues of administering drugs to healthy subjects. 5. Drug absorption patterns in disease states can be evaluated. 6. Preferred for Multidose availability studies. 5/7/2011 15Slide 16: Drawbacks 1. Difficult to obtain many patients in a given place. 2. Severity of disease varies from patient to patient. 3. Ethical considerations do not allow withdrawal of many blood samples from patients for a longer time. 4. Unethical to administer dosage form to a patient whose therapeutic efficacy is not known. 5. Patient may already be on certain drugs, which may affect bioavailability of the test drug. 5/7/2011 16Single Vs Multiple Dose Studies: Single Vs Multiple Dose Studies Single Bioequivalence study. Dosage forms meant for single dose administration. Very Common. Easy, offer less exposure to drugs, less tedious. Difficult to predict steady state characteristics of drug and inter subject variability. 5/7/2011 17Slide 18: Multiple 1.Specialized dosage forms. (Time release, enteric coated, I.M depot preparations) 2. Drugs undergoing first pass metabolism. 3. Specialized Dosage regimen. Disadvantages Difficult to control. Exposes the subject to more drug, highly tedious, time consuming. 5/7/2011 18Sampling: Sampling Sampling should be frequent enough to define the absorption phase, C max , elimination phase during a drug’s time course. Enough data points should be available to determine K a and AUC. Sampling to be carried out till the linear elimination phase. For 1 st order process time required for complete elimination is ∞. 5/7/2011 19Study Conditions: Study Conditions Subjects maintained on uniform diet. No drug one week prior to the study. Condition to define- fasting period before administration. fluid intake & volume to be allowed. fasting after administration. 5/7/2011 20STATISTICAL ANALYSIS OF DATA: STATISTICAL ANALYSIS OF DATA Purpose Test formulation gives a blood level profile identical to the reference standard. Biological and experimental variation does exist due to limitations in the sampling technique. Necessary to ascertain whether these differences are simply chance occurrence or are due to actual differences in the treatment administered to the patient. Sources of variation: 1. Subjects 2. Period 3. Formulation 4. Order 5/7/2011 21Slide 22: Statistical methods are used to evaluate the data in order to identify 1. Different sources of variation. 2. Measure the contribution of each identified variable. 3. Isolate specific observation of primary interest . Types of Statistical Tests 1. t -test of significance. 2. Chi-squared tests of significance. 3. Analysis of Variance (ANOVA). 5/7/2011 22ANOVA: ANOVA Based on certain assumptions. Subjects should be randomly subjected to the sequences of the study. Variances associated with the 2 treatments as well as between sequence groups should be equal or at least comparable. No interaction between subject, treatment, sequence and period. Data obtained from bioequivalence studies should be normal . 5/7/2011 23ANOVA for multiple comparisons: ANOVA for multiple comparisons Useful for 4 formulations. ANOVA can only tell whether the 4 formulations are same or different. Which formulations are same and which are different? Newman – Kuels test. Formulation A & C , B & D are bioequivalent. A & C show higher bioavailability & differ significantly from B & D. 5/7/2011 24t-test of significance: t-test of significance Determines significance of difference observed between experimental conditions and control. 1. Two Independent sample t-test Used to compare 2 samples to check whether they are drawn from the same population. 2. Paired t-test Used when two different treatments are given to a single group of experimental units. E.g. 1. test and std are given to the same subjects on different occasion. 2. Comparison of new analytical method with already existing method. 5/7/2011 25Chi squared test of significance: Chi squared test of significance Can assume many different forms. 1. Checks agreement between expected frequencies and observed frequencies -Chi square (X 2 ) is a probability distribution derived from the sum of squares of chi square statistic and if the calculated value exceeds the value in table, difference is significant. E. g Tossing of coin 2. To check whether a new drug is effective in preventing death of animals due to a specific disease. 5/7/2011 26Logarithmic data transformation: Logarithmic data transformation AUC profile: left skewed distribution. Difficult to construct confidence interval for skewed data. Evidence is required to be provided for log transformed data than untransformed data. Log transformation is carried out to convert left skewed distribution to symmetric one. 5/7/2011 27Slide 28: For bioequivalence testing two products can be considered bioequivalent if 90% confidence interval of the ratio of untransformed pharmacokinetic parameters for test and reference (T/R) lie within the range of 80% – 120%. Products are bioequivalent if relative difference in the parameters is in the range of +/- 20%. For log transformed data, C.I for T/R has been widened to 80% to 125%. 5/7/2011 28Slide 29: THANK YOU 5/7/2011 29 You do not have the permission to view this presentation. In order to view it, please contact the author of the presentation.