Bioequivalence Studies

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Chapter: Biopharmaceutics and Pharmacokinetics : Bioavailability and Bioequivalence

If a new product is intended to be a substitute for an approved medicinal product as a pharmaceutical equivalent or alternative, the equivalence with this product should be shown or justified.


Need/Objectives for Biequivalence Studies

If a new product is intended to be a substitute for an approved medicinal product as a pharmaceutical equivalent or alternative, the equivalence with this product should be shown or justified. In order to ensure clinical performance of such drug products, bioequivalence studies should be performed. Bioequivalence studies are conducted if there is:

·            A risk of bio-inequivalence and/or

·            A risk of pharmacotherapeutic failure or diminished clinical safety.

Some of the important terms relevant in this context will be defined.

Equivalence: It is a relative term that compares drug products with respect to a specific characteristic or function or to a defined set of standards. There are several types of equivalences.

Chemical Equivalence: It indicates that two or more drug products contain the same labelled chemical substance as an active ingredient in the same amount.

Pharmaceutical Equivalence: This term implies that two or more drug products are identical in strength, quality, purity, content uniformity and disintegration and dissolution characteristics; they may however differ in containing different excipients.

Bioequivalence: It is a relative term which denotes that the drug substance in two or more identical dosage forms, reaches the systemic circulation at the same relative rate and to the same relative extent i.e. their plasma concentration-time profiles will be identical without significant statistical differences.

When statistically significant differences are observed in the bioavailability of two or more drug products, bio-inequivalence is indicated.

Therapeutic Equivalence: This term indicates that two or more drug products that contain the same therapeutically active ingredient elicit identical pharmacological effects and can control the disease to the same extent.

Types of Bioequivalence Studies

Bioequivalence can be demonstrated either –

·            In vivo, or

·            In vitro.

In vivo Bioequivalence Studies

The following sequence of criteria is useful in assessing the need for in vivo studies:

1. Oral immediate release products with systemic action

·            Indicated for serious conditions requiring assured response

·            Narrow therapeutic margin

·            Pharmacokinetics complicated by absorption < 70% or absorption window, nonlinear kinetics, presystemic elimination > 70%

·            Unfavourable physiochemical properties, e.g. low solubility, metastable modifications, instability, etc.

·            Documented evidence for bioavailability problems

·            No relevant data available, unless justification by applicant that in vivo study is not necessary.

2. Non-oral immediate release products.

3. Modified release products with systemic action.

In vivo bioequivalence studies are conducted in the usual manner as discussed for bioavailability studies, i.e. the pharmacokinetic and the pharmacodynamic methods.

In vitro Bioequivalence Studies

If none of the above criteria is applicable, comparative in vitro dissolution studies will suffice. In vitro studies, i.e. dissolution studies can be used in lieu of in vivo bioequivalence under certain circumstances, called as biowaivers (exemptions)

1. The drug product differs only in strength of the active substance it contains, provided all the following conditions hold –

·            Pharmacokinetics are linear

·            The qualitative composition is the same

·            The ratio between active substance and the excipients is the same, or (in the case of small strengths) the ratio between the excipients is the same

·            Both products are produced by the same manufacturer at the same production site

·            A bioavailability or bioequivalence study has been performed with the original product

·            Under the same test conditions, the in vitro dissolution rate is the same.

2. The drug product has been slightly reformulated or the manufacturing method has been slightly modified by the original manufacturer in ways that can convincingly be argued to be irrelevant for the bioavailability.

3. The drug product meets all of the following requirements –

·            The product is in the form of solution or solubilised form (elixir, syrup, tincture, etc.)

·            The product contains active ingredient in the same concentration as the approved drug product.

·            The product contains no excipients known to significantly affect absorption of the active ingredient.

4. An acceptable IVIVC and the in vitro dissolution rate of the new product is equivalent with that of the already approved medicinal product.


·            The product is intended for topical administration (cream, ointment, gel, etc.) for local effect.

·            The product is for oral administration but not intended to be absorbed (antacid or radio-opaque medium).

·            The product is administered by inhalation as a gas or vapour.

The criteria for drug products listed above indicate that bioavailability and bioequivalence are self-evident.

Bioequivalence Experimental Study Design

The various types of test designs that are usually employed in clinical trials, bioavailability and bioequivalence studies are discussed below.

1. Completely randomised designs

In a completely randomised design, all treatments (factor levels) are randomly allocated among all experimental subjects.

Method of randomisation

Label all subjects with the same number of digits, for e.g., if there are 20 subjects, number them from 1 to 20. Randomly select non-repeating random numbers (like simple randomisation) with among these labels for the first treatment, and then repeat for all other treatments.


1) The design is extremely easy to construct.

2) It can accommodate any number of treatments and subjects.

3) The design is easy and simple to analyse even though the sample sizes might not be the same for each treatment.


1) Although the design can be used for any number of treatments, it is best suited for situations in which there are relatively few treatments.

2) All subjects must be as homogeneous as possible. Any extraneous sources of variability will tend to inflate the random error term, making it difficult to detect differences among the treatment (or factor level) mean responses.

2. Randomised block designs

First, subjects are sorted into homogeneous groups, called blocks and the treatments are then assigned at random within the blocks.

Method of Randomisation

Subjects having similar background characteristics are formed as blocks. Then treatments are randomised within each block, just like the simple randomisation. Randomisations for different blocks are done independent of each other.


1.        With effective and systematic way of grouping, it can provide substantially more precise results than a completely randomised design of comparable size.

2.        It can accommodate any number of treatments or replications.

3.        Different treatments need not have equal sample size.

4.        The statistical analysis is relatively simple. The design is easy to construct.

5.        If an entire treatment or block needs to be dropped from the analysis for some reason, such as spoiled results, the analysis is not thereby complicated.

6.        Variability in experimental units can be deliberately introduced to widen the range of validity of the experimental results without sacrificing the precision of results.


1.        Missing observations within a block require more complex analysis.

2.        The degrees of freedom of experimental error are not as large as with a completely randomised design.

3. Repeated measures, cross-over and carry-over designs

This is essentially a randomised block design in which the same subject serves as a block. The same subject is utilized for each of the treatments under study. Since we take repeated measures on each subject we get the design name ―repeated measures design‖. The study may involve several treatments or a single treatment evaluated at different points in time. The administration of two or more treatments one after the other in a specified or random order to the same group of patients is called a crossover design or change-over design. The drawback of crossover studies is the potential for distortion due to carry-over, that is, residual effects from preceding treatments. To prevent carry-over effects, one must always allow for a wash-out period during which most of the drug is eliminated from the body – generally about 10 elimination half-lives. Example: clinical trials to monitor safety and side effects.

Method of Randomisation

Complete randomisation is used to randomise the order of treatments for each subject.

Randomisations for different subjects are independent of each other.


·           They provide good precision for comparing treatments because all sources of variability between subjects are excluded from the experimental error.

·           It is economic on subjects. This is particularly important when only a few subjects can be utilized for the experiments.

·           When the interest is in the effects of a treatment over time, it is usually desirable to observe the same subject at different points in time rather than observing different subjects at the specified points in time.


·           There may be an order effect, which is connected with the position in the treatment order.

·           There may be a carry-over effect, which is connected with the preceding treatment or treatments.

4. Latin square designs

Completely randomised design, randomised block design and repeated measures design are experiments where the person/subject/volunteer remains on the treatment from the start of the experiment until the end and thus are called as continuous trial. In a Latin square, however, each subject receives each treatment during the course of the experiment. A Latin square design is a two-factor design (subjects and treatments are the two factors) with one observation in each cell. Such a design is useful compared the earlier ones when three or more treatments are to be compared and carry-over effects are balanced. In a Latin square design, rows represent subjects, and columns represent treatments. A r x r Latin square design is a square with r rows and r columns such that each of the r2 cells contain one and only one of the r letters representing the treatments, and each letter appears once and only once in ever row and every column. A Latin square is called standard if the first row and the first column consist of the r letters in alphabetical order.

Randomised, balanced, cross-over Latin square design are commonly used for bioequivalence studies.


·           It minimizes the inter-subject variability in plasma drug levels.

·           Minimizes the carry-over effects which could occur when a given dosage form influences the bioavailability of a subsequently administered product (intra-subject variability).

·           Minimizes the variations due to time effect.

·           Treatment effects can be studied from a small-scale experiment. This is particularly helpful in preliminary or pilot studies.

·           Makes it possible to focus more on the formulation variables which is the key to success for any bioequivalence study.


·           The use of Latin square design will lead to a very small number of degrees of freedom for experimental error when only a few treatments are studied. On the other hand, when many treatments are studied, the degrees of freedom for experimental error maybe larger than necessary.

·           The randomisation required is somewhat more complex than that for earlier designs considered.

·           The study takes a long time since an appropriate washout period between two administrations is essential which may be very long if the drug has a long t½.

·           When the number of formulations to be tested is more, the study becomes more difficult and subject dropout rates are also high. This can be overcome by use of a balanced incomplete block design in which a subject receives no more than 2 formulations.

An example of a typical Latin square design is given in table 11.6.

Table 11.6.

Latin Square Cross-over Design for 6 (or 12) Subjects to Compare Three Different Formulations, A, B and C

Bioequivalence Study Protocol

The elements of in vivo bioequivalence study protocol are listed in table 11.7.

TABLE 11.7.

Elements of Bioequivalence Study Protocol

The in vivo bioequivalence study requires determination of relative bioavailability after administration of a single dose of test and reference formulations by the same route, in equal doses, but at different times. The reference product is generally a previously approved product, usually the innovator‘s product or some suitable reference standard. The study is performed in fasting, young, healthy, adult male volunteers to assure homogeneity in the population and to spare the patients, elderly or pregnant women from rigors of such a clinical investigation. Homogeneity in the study population permits focus on formulation factors.

As for bioavailability studies, either plasma level or urinary excretion studies may be performed to assess bioequivalence between drug products. In vitro-in vivo correlation can also be established for the formulations.

It is always easier to establish bioequivalence between existing drug products than determination of pharmacokinetics of a new drug or bioavailability of a new dosage form since —

1. The human volunteers used for the study of both products are same and all pharmacokinetic parameters can be assumed to be same for both drug formulations and there is no need to investigate nonlinearity.

2. The study protocol for all subjects is uniform, the efficiency of drug absorption from both formulations can be considered as same and thus differences in absorption pattern can be ascribed to differences in drug release from the two dosage form.

Statistical Interpretation of Bioequivalence Data

After the data has been collected, statistical methods must be applied to determine the level of significance of any observed difference in the rate and/or extent of absorption in order to establish bioequivalence between two or more drug products. The commonly adopted approaches to determine statistical differences are –

1. Analysis of variance (ANOVA) is a statistical procedure used to test the data for differences within and between treatment and control groups. A statistical difference between the pharmacokinetic parameters obtained from two or more drug products is considered statistically significant if there is a probability of less than 1 in 20 or 0.05 (p   0.05). The probability p is used to indicate the level of statistical significance. If p 0.05, the differences between the two drug products are not considered statistically significant.

2. Confidence interval approach Also called as two one-sided test procedure, it is used to demonstrate if the bioavailability from the test product is too low or high in comparison to the reference product. The 90% confidence limits are estimated for the sample means based on Student’s t distribution of data. A 90% confidence interval about the ratio of means of the two drug products must be within ±20% for bioavailability parameters such AUC or Cmax i.e. the difference between the bioavailabilities of the test product should not be greater than ± 20% of the average of reference product (between 80 and 120%). When log transformed data are used, the 90% confidence interval is set at 80-125%. These confidence limits are also termed as bioequivalence interval.

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