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«WORLD HEALTH ORGANIZATION ORGANISATION MONDIALE DE LA SANTE MULTISOURCE (GENERIC) PHARMACEUTICAL PRODUCTS: GUIDELINES ON REGISTRATION REQUIREMENTS TO ...»

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All concentration-dependent pharmacokinetic parameters (e.g. AUC and Cmax) should be logtransformed using either common logarithms to the base 10 or natural logarithms. The choice of common or natural logs should be consistent and should be stated in the study report.

Logarithmically transformed concentration-dependent pharmacokinetic parameters should be analysed using ANOVA. Usually the ANOVA model includes the formulation, period, sequence or carry-over and subject factors.

Parametric (normal-theory) methods are recommended for the analysis of log-transformed bioequivalence measures. The general approach is to construct a 90% confidence interval for the quantity µT−µR and to reach a conclusion of pharmacokinetic equivalence if this confidence interval is contained in the stated limits. Due to the nature of normal-theory confidence intervals this is equivalent to carrying out two one-sided tests of hypothesis at the 5% level of significance (8,9). The antilogs of the confidence limits obtained constitute the 90% confidence interval for the ratio of the geometric means between the multisource and comparator products.

The same procedure should be used for analysing parameters from steady-state trials or cumulative urinary recovery, if required.

Usually for tmax descriptive statistics should be given. If tmax is to be subjected to a statistical analysis this should be based on non-parametric methods and should be applied to untransformed data. If tmax is analysed a sufficient number of samples around predicted maximal concentrations should have been taken to ensure the correctness of tmax estimate. For parameters describing the elimination phase (T1/2,) normally only descriptive statistics should be given.

Methods for identifying and handling of possible outlier data should be specified in the protocol.

Medical or pharmacokinetic explanations for such observations should be sought and discussed. As outliers may be indicative of product failure, post hoc deletion of outlier values is generally discouraged. An approach of dealing with data containing outliers is to apply distribution-free (nonparametric), statistical methods (10).

Working document QAS/04.093/Rev.4 page 24 If the distribution of log transformed data is not normal, non-parametric statistical methods can be considered. The justification of the intent to use non-parametric statistical methods should be included a priori in the protocol.

6.9 Acceptance ranges AUC-ratio The 90% confidence interval for this measure of relative bioavailability should lie within a bioequivalence range of 0.80-1.25. If the therapeutic range is particularly narrow the acceptance range may need to be reduced based on clinical justification. A larger acceptance range may be acceptable in exceptional cases if justified clinically.

Cmax-ratio In general acceptance limit 0.80-1.25 should be applied to the Cmax-ratio. However, this measure of relative bioavailability is inherently more variable than, for example, the AUC-ratio, and in certain cases a wider acceptance range (e.g. 0.75-1.33) may be acceptable. The range used must be defined prospectively and should be justified, taking into account safety and efficacy considerations. In exceptional cases, a simple requirement for the point estimate to fall within a bioequivalence limits of 0.80-1.25 may be acceptable with appropriate justification in terms of safety and efficacy.

tmax-difference Statistical evaluation of tmax only makes sense if there is a clinically relevant claim for rapid onset of action or concerns about adverse effects. The non-parametric 90% confidence interval for this measure of relative bioavailability should lie within a clinically relevant range.

For other pharmacokinetic parameters the same considerations as outlined above apply.

6.10 Reporting of results The report of a bioequivalence study should give the complete documentation of its protocol, conduct and evaluation complying with Good Clinical Practice rules (4). The respective ICH guideline (11) can be used in the preparation of the study report. The responsible investigator(s) should sign for their respective sections of the report. Names and affiliations of the responsible investigator(s), site of the study and period of its execution should be stated.

The names and batch numbers of the pharmaceutical products used in the study as well as the composition(s) of the tests product(s) should be given. Results of in vitro dissolution tests should be provided. In addition the applicant should submit a signed statement confirming the identity of the test product with the pharmaceutical product which is submitted for registration.

The bioanalytical validation report (see Section 6.7) should be attached. The bioanalytical report should include the data of calibrations and quality control samples. A representative number of chromatograms or other raw data should be included covering the whole calibration range, quality control samples and specimens from the clinical trial.

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(multisource or comparator) and time elapsed from drug application to blood sampling should be provided in an easily identifiable form. The procedure for calculating the parameters used (e.g. AUC) from the raw data should be stated. Deletion of data should be justified. If results are calculated using pharmacokinetic models, the model and the computing procedure used should be justified. Individual blood concentration/time curves should be drawn on a linear/linear, and linear/log scale. All individual data and results should be given, including those subjects who dropped out. The drop-out and/or withdrawn subjects should be reported and accounted for.





Results of all measured and calculated pharmacokinetic parameters should be tabulated for each subject-formulation combination together with descriptive statistics. The statistical report should be sufficiently detailed so as to enable the statistical analyses to be repeated if necessary. If the statistical methods applied deviate from those specified in the trial protocol the reasons for the deviations should be stated.

6.11 Special considerations 6.11.1 Fixed combination products If the pharmacokinetic bioequivalence of combination products is assessed by in vivo studies the study design should follow the same general principles as described in previous sections. In this study the multisource combination product should be compared with the pharmaceutically equivalent

comparator combination product. In certain cases (e.g. when no comparator combination product is :

available on the market) separate products administered in free combination can be used as a comparator (12). Sampling times should be chosen in such a way that pharmacokinetic parameters of all active ingredients could be adequately assessed. The bioanalytical method should be validated with respect to all compounds measured. Statistical analyses should be performed with pharmacokinetic data of all active ingredients; the 90% confidence intervals of test/comparator ratio of all active ingredients should be within acceptance limits.

6.11.2 Clinically important variations in bioavailability

Innovators should make all efforts to provide formulations with good bioavailability characteristics.

A "high variable" pharmaceutical product is one in which the active pharmaceutical ingredient itself is not highly variable, but the formulation is one of poor pharmaceutical quality. If a better formulation is being developed over time by the innovator this should then serve as the comparator product. A new formulation with a bioavailability outside the acceptance range compared to an existing pharmaceutical product is not interchangeable by definition. Adjusting the strength to compensate with regard to sub- or supra-bioavailability in comparison with the comparator product falls outside the scope of this document, as the pre-requisite of pharmaceutical equivalence is not fullfilled.

6.11.3 "Highly variable drugs" A "highly variable drug" has been defined as active pharmaceutical ingredient with a within-subject variability of ≥ 30% in terms of the ANOVA-CV (13). Moreover "highly variable drugs" are generally safe drugs with shallow dose-response curves. Proving the bioequivalence of dug products containing "highly variable drugs" is problematic because the higher the ANOVA-CV, the wider the 90% confidence interval. Thus large numbers of subjects must be enrolled in studies involving Working document QAS/04.093/Rev.4 page 26 highly variable drugs to achieve adequate statistical power. The following approaches to this

problem are currently being applied in different drug regulatory jurisdictions:

(i) some regulatory authority permit the use of broadened bioequivalence limits provided there is adequate justification (14), for example, the regulatory agency could broaden the bioequivalence limits from 0.8-1.25 to 0.75-1.33 taking into consideration the therapeutic category of the drug;

(ii) some regulatory authority permit the use of scaling to broaden the bioequivalence limits. In a two-period design, the limits are scaled to the residual standard deviation, or in a replicate design, to the within-subject standard deviation of the comparator formulation (15-17);

(iii) some regulatory authority allow the following acceptance criteria: “Products are considered to be bioequivalent, if the 90% confidence interval of difference in the average values of logarithmic AUC and Cmax between test and reference products is within the acceptable range of log(0.8) - log(1.25) (18); however, even though the confidence interval is not in the above range, test products are accepted as bioequivalent, if the following three conditions are

satisfied:

(a) the total sample size of the initial bioequivalence study is not less than 20 (n=10/group) or pooled sample size of the initial and add-on subject studies is not less than 30;

(b) the ratio of geometric LS means of AUC and Cmax between the multisource and comparator product are between 0.9-1.11; and (c) dissolution rates of test and reference products are evaluated to be equivalent under all dissolution testing conditions under Sec.3 A.V.

(iv) some do not allow for any adjustments (19).

However, the third rule cannot be applied to slowly dissolving products from which more than 80% of a drug does not dissolve within the final testing time (2 hr in pH 1.2 medium and 6 hr in others) under any conditions of the dissolution tests described in Sec.3 A.V.” The relevant national/regional regulatory authority of the country should adopt any one of these approaches prospectively to regulate the market authorization of highly variable pharmaceutical products.

6.11.4 Application of truncated AUC in bioequivalence determination

In bioavailability studies it is generally recommended that plasma concentrations should be followed for at least three half-lives post-dose. Potent drugs found in plasma at low concentrations usually require sophisticated and expensive equipment to be able to measure the active pharmaceutical ingredient in the terminal portions of the plasma concentration versus time curve. In consideration of the bioequivalence of immediate release formulations for systemic delivery, the most important portion of the plasma concentration versus time curve is until the absorption phase is complete. On the other hand the disposition phase does not illustrate formulation differences between the multisource product and comparator product in bioequivalence decision-making process (20 and 21).



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