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Draft Guidance Document : Conduct and Analysis of Comparative Bioavailability Studies

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Contact:Policy Bureau Enquiries

Notice

January 25, 2010

Our file number: 10-100644-454

Health Canada is pleased to announce the release of two draft guidance documents, entitled Conduct and Analysis of Comparative Bioavailability Studies and Comparative Bioavailability Standards: Formulations used for Systemic Effects, for stakeholder comment.

The purpose of these documents is to update and consolidate eleven existing Health Canada documents related to the conduct and analysis of comparative bioavailability studies and the standards to be met in those studies in order to comply with Sections C.08.002(2)(h), C.08.002.1(2)(c)(ii) and C.08.003(3) of the Food and Drug Regulations.  Please note, however, until such time as these guidances are finalized and published, current bioequivalence requirements remain unchanged and proposals in the draft guidances are not to be implemented.

The existing documents which will be superseded, once the two draft documents are finalized, are as follows:

  1. Guidance for Industry: Conduct and Analysis of Bioavailability and Bioequivalence Studies - Part A: Oral Dosage Formulations Used for Systemic Effects (1992).
  2. Report C (of the Expert Advisory Committee on Bioavailability and Bioequivalence): Report on Bioavailability of Oral Dosage Formulations, Not in Modified Release Form, of Drugs Used for Systemic Effects, Having Complicated or Variable Pharmacokinetics (1992).
  3. Guidance for Industry: Conduct and Analysis of Bioavailability and Bioequivalence Studies - Part B: Oral Modified Release Formulations (1996).
  4. Draft Policy: Bioequivalence Requirements: Drugs Exhibiting Non-Linear Pharmacokinetics (2003).
  5. Notice to industry: Removal of Requirement for 15% Random Replicate Samples (2003).
  6. Draft Guidance for Industry: Use of Metabolite Data in Comparative Bioavailability Studies (2004).
  7. Notice to industry: Bioequivalence requirements for combination drug products (2004).
  8. Guidance for Industry: Bioequivalence Requirements: Comparative Bioavailability Studies Conducted in the Fed State (2005).
  9. Notice to Industry: Bioequivalence Requirements for Drugs for Which an Early Time of Onset or Rapid Rate of Absorption Is Important (rapid onset drugs) (2005).
  10. Notice to Industry: Bioequivalence Requirements for Long Half-life Drugs (2005).
  11. Guidance for Industry: Bioequivalence Requirements: Critical Dose Drugs (2006).

Please note, however, that Section 2.6: Analytical Methodology in the draft document Conduct and Analysis of Comparative Bioavailability Studies, is currently still under revision and further consultation will be undertaken, as appropriate.  We invite stakeholders to provide advance recommendations on analytical methodology, particularly assay validation.  These recommendations will be taken into consideration in revising this section.

Comments should be provided to Health Canada, preferably in electronic format using the attached template, within 60 days of the publication of this Notice.

Comments or requests for an electronic copy of the guidances should be directed to:

Bureau of Policy, Science and International Programs
Therapeutic Products Directorate
Health Canada
1600 Scott Street
Holland Cross, Tower B
2nd Floor, Address Locator 3102C5
Ottawa, Ontario
K1A 0K9

Telephone: 613-948-4623
Facsimile: 613-941-1812
E-mail: Policy_Bureau_Enquiries@hc-sc.gc.ca

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Foreword

Guidance documents are meant to provide assistance to industry and health care professionals on how to comply with governing statutes and regulations. Guidance documents also provide assistance to staff on how Health Canada mandates and objectives should be implemented in a manner that is fair, consistent and effective.

Guidance documents are administrative instruments not having force of law and, as such, allow for flexibility in approach.  Alternate approaches to the principles and practices described in this document may be acceptable provided they are supported by adequate justification.  Alternate approaches should be discussed in advance with the relevant program area to avoid the possible finding that applicable statutory or regulatory requirements have not been met.

As a corollary to the above, it is equally important to note that Health Canada reserves the right to request information or material, or define conditions not specifically described in this document, in order to allow the Department to adequately assess the safety, efficacy or quality of a therapeutic product.  Health Canada is committed to ensuring that such requests are justifiable and that decisions are clearly documented.

This document should be read in conjunction with the accompanying notice and the relevant sections of other applicable guidance documents.

Table Of Contents

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Introduction

1.1 Policy Objectives

To ensure that sponsors of new drug submissions have the information necessary to comply with Sections C.08.002(2)(h), C.08.002.1(2)(c)(ii) and C.08.003(3) of the Food and Drug Regulations with respect to comparative bioavailability and comparative pharmacodynamic studies used in support of the safety and efficacy of a drug.

1.2 Policy Statements

Comparative bioavailability studies should be conducted in accordance with generally accepted clinical practices that are designed to ensure the protection of the rights, safety and well-being of subjects and the good clinical practices referred to in Division 5 of the Food and Drug Regulations and described in the International Conference on Harmonisation (ICH) Guidance (Topic E6) on Good Clinical Practice.

The recommendations included in this guidance respecting study design and conduct, analytical methodology and analysis of data should be followed in order to ensure compliance with the Food and Drug Regulations.

1.3 Scope and Application

This guidance is intended to be applied to all comparative bioavailability studies which provide pivotal evidence of the safety and efficacy of a product. Examples of cases where this guidance applies are:

  1. comparative bioavailability studies in support of the bioequivalence of subsequent-entry products to the Canadian Reference Product;
  2. bridging studies where the formulation to be marketed is different from the formulation used in the pivotal clinical trials;
  3. studies in support of significant post-marketing changes and line extensions;
  4. safety studies for non-systemic drugs.

While this guidance is oriented toward oral dosage formulations, the principles described may also be applied, as appropriate, to other non-parenteral formulations such as transdermal patches, suppositories, etc. that are intended to deliver medication to the systemic circulation.

This guidance document should be read in conjunction with the associated Health Canada draft guidance document entitled: Comparative Bioavailability Standards: Formulations Used for Systemic Effects.

1.4 Background

Bioavailability is an important attribute of formulations of drugs used for systemic effects. It is defined as the rate and extent of absorption of a drug into the systemic circulation.

Bioavailability is most frequently assessed by serial measurements of the drug in the systemic circulation. These serial measurements provide a plasma concentration-time profile from which a number of important pharmacokinetic parameters can be calculated, including the area under the curve (AUC), the maximum observed concentration (Cmax) and the time when Cmax is reached (tmax). The AUC provides an estimate of the amount of drug absorbed into the systemic circulation while tmax reflects the rate of absorption. Cmax is a more complex function, which, together with tmax, may reflect the rate of absorption. For many drugs, AUC and Cmax together can characterize the concentration-time profile for comparative purposes.

Comparison of the AUC values following oral versus intravenous administration of an equivalent dose of the same active ingredient provides an estimate of absolute bioavailability for most drugs. Comparison of the plasma concentration-time profiles of the drug between the test and reference products containing the same active ingredient provides an estimate of relative bioavailability.

If the test and reference products are comparable dosage forms and contain the identical amounts of identical medicinal ingredient, they are said to be bioequivalent when the profiles of the drug are similar. The degree of similarity between the profiles needed to establish bioequivalence is determined by the appropriate statistical assessment and by meeting standards established for the particular drug and formulations being compared (see Health Canada draft guidance document: Comparative bioavailability standards: Formulations used for systemic effects).

Bioequivalence implies that the test product can be expected to have the same therapeutic effects and safety profile as the reference product when administered to patients under the conditions specified in the labelling.

Bioavailability is usually established by measuring the formulated drug in plasma. If the formulated drug cannot be assayed, a major primary metabolite may be used. In some situations, determination of the urinary excretion of the formulated drug, but not a metabolite, may be employed to measure bioavailability and establish bioequivalence. In the absence of an adequate methodology for bioavailability testing, alternate approaches such as pharmacodynamic studies can be used. In some instances, equivalence may have to be determined by clinical trials.

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2 Guidance For Implementation

The acceptability of data from comparative bioavailability studies will be assessed in accordance with principles enunciated in Division 5 of the Food and Drug Regulations and the ICH Guidance (Topic E6) on Good Clinical Practice. These documents will help sponsors to understand requirements for submissions to Health Canada, pursuant to the Food and Drug Regulations, even if the studies or a portion of the study are conducted in other countries.

2.1 Planning a Bioavailability Study

This section identifies the sections of the study protocol which should be prepared before the study is executed.

2.1.1 Study Objectives

In this section, a rationale should be provided to justify which comparative bioavailability standard will be applied.  Scientific justification should be provided for any deviation from standard procedure, for example (e.g.), analyte upon which bioequivalence will be assessed, deviation from a high fat/high calorie meal in studies conducted under fed conditions.

Among the topics covered by the Regulations and the ICH guidance on Good Clinical Practice, and therefore not repeated in detail here are: Institutional review boards, investigators, clinical, laboratory and analytical facilities.

2.2 Selection of Subjects for a Study

This section describes selection criteria for inclusion of subjects in a bioavailability study and indicates how the characteristics of the subjects may affect the study. In general, subjects should be selected so as to reduce variability that is not attributable to the drug itself.

2.2.1 Choice of Subjects

Bioequivalence studies can usually be conducted with normal, healthy volunteers. This approach has the advantage of minimizing variability that is not due to the drug or drug product per se. It is generally accepted that conclusions regarding relative bioavailability, drawn from studies with healthy volunteers, can be expected to hold in the patient population. It is more difficult to conduct cross-over comparative bioavailability studies in patients, in part due to potential disease progression. In some cases, for example when the safety profile of the drug being studied is such that it cannot be administered to healthy volunteers, it may be necessary to conduct studies in patients who are already receiving the drug. The variability of the disease states in patients in whom the studies are performed will be an important consideration in deciding the size of cohort which will have to be investigated in order to satisfy the standards.

2.2.2 Inclusion / Exclusion Criteria

An important objective in the selection of subjects is to reduce the intrasubject variability in pharmacokinetics that may be attributable to certain characteristics of the subject.

  1. Age

    Subjects should be between the age of legal majority and the age of onset of age-associated changes in organic function. This description typically coincides with an age range of 18 to 55 years, inclusive.

  2. Height/weight ratio

    The ratio for healthy volunteer subjects should be within 15 percent of the normal range, e.g., as given in current Metropolitan Life Insurance tables. Alternatively, weights within the normal range according to the normal values for body mass index, are acceptable.

  3. Health

    The health of the volunteers should be determined by the supervising physician through a medical examination and review of results of routine tests of liver, kidney, and hematological functions. Aberrant laboratory values should be rechecked and a summary should be presented along with the physician's opinion as to potential impact on the study's conclusions.

    Psychological characteristics should also be assessed by the physician in order to exclude patients unlikely to comply with study restrictions or unlikely to complete the study.

    Testing for alcohol and drugs of abuse should be conducted prior to drug administration in each period.

  4. Safety

    An electrocardiogram should be included in the study documentation if the drug has a cardiac effect.

    Subjects who have been previously treated for gastrointestinal problems (such as ulcers), or convulsive, depressive, or hepatic disorders, and in whom there is a risk of a recurrence during the study period, should be excluded.

    The investigators should ensure that female volunteers are not pregnant, lactating, or likely to become pregnant during the study. Confirmation regarding pregnancy should be obtained by urine tests prior to drug administration in each period.

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2.3 Study Design

2.3.1 Parallel versus Cross-over

The basic design to be used is a two-period cross-over, in which each subject is given the test and reference formulations. The advantage of the cross-over design is that in the construction of the confidence intervals for comparing mean differences, the intrasubject error is used, which is always lower than the intersubject error used in a parallel design. The linear model for the two treatment, two period, and two sequence (2×2) crossover design is given in Equation 1:

Yijkl = μ + Si + Vj(i) + Fk + Pl + εijkl (1)

where Yijkl = observation for subject j in sequence i given formulation k in period l; μ = the overall mean; Si = effect of sequence i; Vj(i) = random effect of subjects within sequence, assumed independently and identically distributed N(0, σ2B), where σ2B is an estimate of the intersubject variability; Fk = effect of formulation k; Pl = effect of period l; and εijkl = the residual assumed to be independently identically distributed N(0, σ2W), where σ2W is an estimate of the intrasubject variability.

Assumptions on this model are that observations made on different subjects are independent, and that the variance of an observed Y is σ2B + σ2W and any two observations have a covariance σ2B.

In cases where more than two formulations are under study, or are studied under different conditions, a higher order (that is [i.e.], more periods and sequences) should be considered. Since the intrasubject error term of these designs has more degrees of freedom, smaller sample sizes are often required.

Another type of crossover design that is sometimes used is the replicated design where the formulations being tested are replicated within subjects. The main advantage of these designs is that fewer subjects are required but they must appear for more periods.

Parallel designs are sometimes necessary to study patients where it would be unethical to discontinue medication for the washout period. Such designs may also be useful when studying drugs with very long elimination half-lives. The error term used is the intersubject variance.

2.3.1.1 Number of Subjects

The number of subjects to be used in the study should be estimated by considering the objectives of the study, study design and the drug products being compared. The drug and drug product determine the particular standard which needs to be met. A complete literature search should be done in order to understand the drug and drug product. The standard, the expected mean difference between the test and reference formulations of both AUCT and Cmax, the anticipated intrasubject coefficient of variation (CV) of both AUCT and Cmax and the power determine the number of subjects. The minimum number of subjects is 12, but a larger number is usually required.

Tables A1-A and A1-B in Appendix A1 suggest sample sizes for the various scenarios of CV, expected mean differences, bioequivalence limits and power for two-way crossover studies.

For parallel studies see Tables A1-C and A1-D, Appendix A1.

Higher order designs have a larger degrees of freedom and will often require slightly smaller sample sizes.

2.3.2 Other Strategies for Collecting Data

2.3.2.1 Add-ons

As a result of random variation or a larger than expected relative difference, there is no guarantee that the sample size as calculated will pass the standards. If the study is run with the appropriate size and the standards are not met, the sponsor may add more subjects (a minimum of 12). The same protocol should  be used (i.e., same formulations, same lots, same blood sampling times, a minimum number of 12 subjects, etc.). The choice to use this strategy, as with all designs, should be declared and justified a priori.

The level of confidence should be adjusted using the Bonferroni procedure. The t-value should be that for p=.025 instead of .05.

2.3.2.2 Sequential designs

In these aforementioned basic designs, a group sequential design approach (see Gould A.L. Group sequential extensions of a standard bioequivalence testing procedure. J Pharmacokinet Biopharm 1995 Feb;23(1):57-86) could be implemented when the best estimate of the intrasubject variability is not certain.

  1. Obtain an estimate of the intrasubject CV.
  2. The total sample size should be estimated according to the procedure outlined above.
  3. The number of subjects at which time a "peek" at the data will be determined and declared in the protocol.
  4. The overall type 1 error of the experiment should be preserved. Analysis of data from the initial stage should be treated as an interim analysis and both first and second stage analyses should be conducted at adjusted significance levels resulting in confidence intervals of higher than 90%.
  5. The decision rules for stopping at each stage should be provided to ensure that group sequential design procedure is valid.
  6. The choice to use a sequential design should be specified a priori, in the protocol, along with the adjusted significance levels to be used for each of the analyses.

After all data is collected, the usual methods for calculating the point estimates and their confidence intervals should be used.

2.3.2.3 Adaptive designs

An adaptive design may be used when little is known about the formulations being compared, e.g., new chemical entities.

Sample size re-estimation is permitted when the variability in the data is larger than anticipated. No penalty need to be assessed if the assessment of variability is performed blinded to formulation. Increasing sample size after an unblinded assessment will be treated as add-on requiring Bonferroni adjustment. All other anticipated design modifications and adaptations should be specified and justified in the protocol, with attention paid to preserving type I error.

2.3.3 Accounting for Drop-outs and Withdrawals

More subjects than the sample size calculation requires should be recruited into the study. This strategy allows for possible no-shows, drop-outs and withdrawals and discontinuations. A fixed number (one or two for each sequence) of subjects should be added to the sample-size number.

Reasons for withdrawal (e.g., adverse drug reaction) should be reported and the subject's plasma level data provided. The results of all samples that were measured in subjects who were withdrawn from the study should be included in the report. Data from all subjects should be included in the statistical analysis, unless the subject is in a cross-over trial and does not complete at least one period with the test product and one period with the reference product.

2.3.4 Outlier consideration

Comparative bioavailability studies are small studies compared to other clinical trials. One or two extreme values could have a large effect on the inference to be made from these small studies. The usual parametric assumptions and estimation are not robust against extreme values.

There are three main causes of these extreme values. One cause is a possible subject by formulation interaction where the two formulations act consistently differently for a subpopulation of individuals. The reason is generally unknown but is more frequent with modified-release formulations. Retesting the subject(s) may provide data to suggest that this interaction is real, if the results of the retest on the two formulations is similar to the initial results. Another potential cause is actual formulation failure. This is a more difficult cause to determine since the "tablet" can only be tested once. Given current strict manufacturing requirements, formulation failure is not a likely cause of the extreme values. In vitro testing of the test biobatch should be done if outliers are declared in a data set (Section 2.7.4.1). The most likely cause of a large difference between two similar formulations is the particular subject's physiology or metabolism on the specific day of testing. Again retesting of the subject on both formulations may provide an explanation for the observation.

A strategy to identify and account for outliers should be part of the protocol. These extreme values should be rare and no more than two should be identified. If a protocol for handling outliers is stated it must be followed before the results of the analysis are summarised into confidence intervals (i.e., regardless of whether results meet the standard the outlier protocol should be followed).

First, in order to be considered an extreme value, the observation must be outside the range of all the other observations regardless of formulation. Second it must be identified by an outlier test. It is recommended that the outlier test be a simple studentised residual tested against a conservative t-value at the .02 level of significance and degrees of freedom for the design. In other words the test should only identify observations which are very different from all others collected.

A declaration of how extreme values are to be dealt with, should be made a priori. One strategy is to perform a  non-parametric construction of the confidence interval. A non-parametric analysis which uses the log differences is preferred. Another strategy is to retest the identified subject(s). If subjects are to be retested, they should be brought back and given both formulations. In addition, 3 to 5 subjects from the original study, who were not identified as outliers, should be retested to serve as controls. The new results are put back into the analysis and if not declared an outlier by the same procedure, the original values may be removed. The retest values are not to be part of the final analysis. The subject's values, both initial and retest, should be reported. Should the same values be identified as outliers, consultation with the Branch is recommended.

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2.4 Study Conduct

2.4.1 Standardization

Every effort should be made to standardize the study conditions in every phase of the study-for example, exercise, diet, smoking, and alcohol use. It is preferable to use non-smokers; where smokers are included, they should be so identified.

Volunteers should not take any other drug, including alcoholic beverages and over-the-counter (OTC) drugs, for an appropriate interval before, as well as during, the study. Consideration should also be given to the potential metabolic effects of dietary items, such as flavonoid-containing juices, that may affect the outcome of the study. Protocol violations with respect to the use of any drug should be reported (dose and time of administration). The decision whether to include or exclude the results from a subject who has varied from the established protocol should be made before statistical analysis commences.

2.4.2 Blinding

If possible, the study should be conducted in such a way that the subject is not aware of which product (test or reference) is being administered. Furthermore, the person checking for adverse reactions and the person conducting the analysis of samples should not know which product was administered. Other individuals involved in the administration of the drugs, the surveillance of the patients, or the analysis of plasma data should not know which product was administered.

2.4.3 Administration of Food and Fluid

2.4.3.1 Fasted study

For immediate-release dosage forms, comparative bioavailability should be demonstrated in single-dose studies under fasting conditions. For the majority of drugs in immediate-release dosage forms, this will provide sufficient information for the assessment of bioequivalence to the Canadian Reference Product.

The administration of food and fluid should be controlled carefully. Normally, subjects should fast for 10 hours before drug administration. A fast means that no food or solids are to be consumed, although alcohol-free, xanthine-free and flavonoid-free clear fluids are permissible the night prior to the study. Water may be permitted up to one hour before drug administration. The dose should be taken with water of a standard volume (minimum of 150 millilitre) and at a standard temperature. One hour after drug administration xanthine- and flavonoid-free fluids are permitted. Four hours after drug administration, a standard meal may be taken. All meals should be standardized and repeated on each study day.

When comparing the performance of two orally disintegrating dosage forms that are intended to be taken without water, the comparative bioavailability study should be designed to challenge the formulation under the most discriminatory conditions. For such dosage formulations, water should not be administered from one hour prior to dosing, concurrent with dosing and up to one hour post dosing.

2.4.3.2 Fed Study

Bioequivalence should be demonstrated under both fasted and fed conditions for critical-dose drugs, drugs exhibiting non-linear pharmacokinetics and drugs in modified-release dosage forms (including delayed-release formulations). Requirements for modified-release formulations may differ from those for conventional drug formulations because a greater likelihood exists that increased intersubject variability in bioavailability will occur, including the possibility of dose-dumping and there may be an increased risk of adverse effects such as gastrointestinal irritation, depending on the site of drug release, or absorption, or both.

If, however, there is a documented serious safety risk to subjects from single-dose administration of the drug or drug product in either the absence or presence of food, then an appropriately designed study conducted in the indicated condition of use (fed or fasted state) may be acceptable for purposes of bioequivalence assessment. This approach should be scientifically justified a priori by the sponsor.

The meal used in a comparative bioavailability study under fed conditions should allow maximal perturbation of systemic bioavailability of the drug from the drug product. This is generally a high fat, high calorie meal. Thus, the default meal, for comparative bioavailability studies under fed conditions, should be a high fat, high calorie meal.

Given the above, use of a meal other than a high fat, high calorie meal should only occur under exceptional circumstances. Use of a meal other than a high fat, high calorie meal should be scientifically justified, a priori, by the submission sponsor. A possible justification for use of a meal other than a high fat, high calorie meal would be a documented serious safety risk to subjects from single-dose administration of the drug or drug product in the presence of such a meal. In any case, deviations from the default meal should be scientifically justified, a priori, by the submission sponsor. The meal should be given within 30 minutes prior to administration of the drug product.

A high-fat (approximately 50 percent of total caloric content of the meal) and high-calorie (approximately 800 to 1000 calories) meal should derive approximately 150, 250, and 500-600 calories from protein, carbohydrate, and fat, respectively. One example of a test meal that is expected to promote the greatest perturbation in gastrointestinal physiology so that systemic drug bioavailability is maximally affected would be the following breakfast: 2 eggs fried in butter, 2 strips of bacon, 2 slices of toast with butter,120 grams of hash browns and 240 millilitres of whole milk.

2.4.3.3 Steady-state Studies

If steady-state studies are required, the food and fluid conditions and restrictions noted above should apply on the preceding evening and on the day the plasma profiles are to be obtained.

2.4.4 Posture and Physical Activity

For most drugs, subjects should not be allowed to recline until at least two hours after drug ingestion. Physical activity and posture should be standardized as much as possible to limit effects on gastrointestinal blood flow and motility. The same pattern of posture and physical activity should be maintained for each study day.

2.4.5 Interval Between Doses

The interval between study days should be long enough to permit elimination of essentially all of the previous dose from the body. The interval should be the same for all subjects and, to account for variability in elimination rate between subjects, normally should be not less than 10 times the mean terminal half-life of the drug. Normally, the interval between study days should not exceed three to four weeks. Furthermore, the drugs should be administered at approximately the same time on each study day.

2.4.6 Sampling Times

The duration of sampling in a study should be sufficient to account for at least 80 percent of the known AUC to infinity (AUCI). This period is usually at least three times the terminal half-life of the drug.

To permit calculation of the relevant pharmacokinetic parameters, a minimum of 12 samples should be collected per subject per dose. Intersubject variability, as well as such factors as potential for erratic behaviour of some formulations under some conditions (for example, a fatty environment may affect release from an enteric-coated product), should be taken into consideration in the placement and number of samples. The exact times at which the samples are taken should be recorded and spaced such that the following information can be estimated accurately:

  1. peak concentration of the drug in the blood (Cmax);
  2. the area under the concentration time curve (AUCT) is at least 80 percent of the known AUCI; and
  3. the terminal disposition rate constant of the drug.

There may be considerable inaccuracies in the estimates of the terminal disposition rate constant if the constant is estimated from linear regression using only a few points. To reduce these inaccuracies it is preferable that four or more points be determined during the terminal log-linear phase of the curve. If urine is used as the biological sampling fluid (see below), then sufficient samples should be obtained to permit an estimate of the rate and extent of renal excretion.

2.4.7 Sample Collection

Under normal circumstances, blood should be the biological fluid sampled to measure the concentrations of the drug. In most cases the drug may be measured in serum or plasma; however, in some cases, whole blood may be more appropriate for analysis. If the concentrations in the blood are too minute to be detected and a substantial amount (>40 percent) of the drug is eliminated unchanged in the urine, then the urine may serve as the biological fluid to be sampled. In those rare situations where use of drug concentrations in urine is justifiable for the assessment of relative bioavailability, only parent drug concentrations may be used. That is, use of metabolite concentrations in urine is not considered acceptable in the assessment of bioequivalence.

When urine is collected at the study centre, the volume of each sample should be measured immediately after collection and included in the report. Urine should be collected over a period of no less than three times the terminal elimination half-life. For a 24-hour study, sampling times of 0 to 2, 2 to 4, 4 to 8, 8 to 12, and 12 to 24 hours are usually appropriate. Quantitative creatinine determinations on each urine sample are also required.

Sometimes the concentration of drug in a fluid other than blood or urine may correlate better with effect. Nevertheless, the drug must first be absorbed prior to distribution to the other fluids such as the cerebrospinal fluid, bronchial secretions, etc. Thus, for bioavailability estimations, blood is still to be sampled and assayed.

2.4.8 Handling of Samples

Samples should be processed and stored under conditions that have been shown not to cause significant degradation of the analytes. Appropriate storage conditions should be confirmed with samples from subjects who have been given the drug under study, in case spiked samples give misleading results, e.g., if there is evidence that metabolites are likely to interconvert to the parent drug.

2.4.9 Identification of Adverse Events

In some cases, adverse events are due to factors other than the active ingredient in a formulation. The rate of absorption and excipients within formulations may affect the frequency, onset, and severity of adverse events. The incidence, severity, and duration of all adverse events observed during the study should be reported. The probability that an adverse event is drug-induced is to be judged by the investigator.

As much as possible, the same observer and format for eliciting and recording information on adverse events should be used for all subjects. Questions concerning adverse events should be asked on each study day by the "blinded" observer. For drugs with known adverse events -for example, metallic taste, postural hypotension, cardiac dysrhythmia-the specific questions should be raised and observations, such as blood pressure measurement and electrocardiogram, should be performed and recorded at the time the events are known to occur with respect to the time of administration. In asking the questions, the interviewer should avoid leading the subject to believe that the events are expected or unexpected. Furthermore, the subject should be questioned in private.

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2.5 Test and Reference Drug Products

This section describes the required characteristics of the test and reference drug products that should be documented, including quality, dosage, and strength.

The test and reference drug products should be of high quality and mention should be made in the study documentation of the dosage and strength of the drug and what reference product is used in the study.

2.5.1 Chemistry

The products should meet a Schedule B or other applicable standard acceptable to Health Canada. The chemistry and manufacturing guidances for preclinical and new drug submissions should be consulted for an interpretation of the general technical requirements listed in sections C.08.005(1) and C.08.002(2) respectively.

2.5.2 Dosage and Strength

In bioequivalence studies, the same dose of each product should be used. The lots for comparative bioavailability testing should be representative of proposed market production batches. The lots for comparative bioavailability testing should be taken from a batch that is a minimum of ten percent of the commercial batch size and is produced using the same type of equipment and procedures, and for modified-release formulations, the same site, proposed for market production.

For products in which the proportions of excipients and the dissolution characteristics are similar, comparative bioavailability studies may not be required for all strengths. Whether all strengths should be tested will depend on the extent to which the formulation differs among strengths.

When a modified-release product in the form of a scored tablet possesses the claim that a portion of the tablet may be administered to provide a proportional dose, evidence must be presented to justify the claim.

2.5.3 Selection of Reference Product

For a new drug substance (i.e., the first market entry), an oral solution should be used as the reference product when possible. The oral solution can be prepared from an intravenous solution, if available.

In bioequivalence studies, the Canadian reference product is:

  1. a drug in respect of which a notice of compliance is issued pursuant to section C.08.004 of the Food and Drug Regulations and which is marketed in Canada by the innovator of the drug;
  2. a drug, acceptable to the Minister, that can be used for the purpose of demonstrating bioequivalence on the basis of pharmaceutical and, where applicable, bioavailability characteristics, where a drug in respect of which a notice of compliance has been issued pursuant to section C.08.004 cannot be used for that purpose because it is no longer marketed in Canada;
    or
  3. a drug, acceptable to the Minister, that can be used for the purpose of demonstrating bioequivalence on the basis of pharmaceutical and, where applicable, bioavailability characteristics, in comparison to a drug referred to in paragraph (a).
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2.6 Analytical Methodology

Bioavailability determinations rely on well-characterized and validated analytical methods that are able to generate reliable estimates of analyte concentrations.

2.6.1 Drug and Drug Metabolites

Determination of bioequivalence should be based on data for the parent drug.

Waiver of the measurement of the parent drug will not be considered, unless concentrations of the parent drug cannot be reliably measured, e.g., if the parent drug is not detectable due to rapid biotransformation. In such instances, the use of metabolite data may be acceptable. The measured metabolite should be a primary (first step) and major one, and appropriate scientific justification for a waiver of the measurement of the parent drug and the use of metabolite data should be provided. The choice of using the metabolite instead of the parent drug is to be clearly stated, a priori, in the objective of the study in the study protocol.

For the purpose of this guidance, a pro-drug is to be treated as a 'parent drug'. That is, if the substance released from the dosage form is absorbed intact and is reliably measurable in the systemic circulation, it should be used in the assessment of bioequivalence.

It is not generally considered necessary to measure both parent drug and metabolite levels for the purpose of bioequivalence assessment. However, quantitation of metabolite levels may sometimes be helpful, e.g., to explain extreme values caused by metabolic changes within a subject.

In those rare situations where use of drug concentrations in urine is justifiable for the assessment of relative bioavailability, only parent drug concentrations may be used. That is, use of metabolite concentrations in urine is not considered acceptable in the assessment of bioequivalence.

2.6.2 Assay Methodology

The analytical methods used to measure the drug, or metabolite, in plasma, blood, serum, or urine should  be reproducible, specific, and sufficiently sensitive, precise, and accurate. When these operating parameters have been shown to be adequate in the hands of the test laboratory, the investigators can then undertake the bioavailability study.

The principles and procedures for analytical validation described in the summary document "Analytical Methods Validation: Bioavailability, Bioequivalence, and Pharmacokinetic Studies," V. P. Shah et al (1992), Journal of Pharmaceutical Sciences 81(3) and "Workshop/Conference report - Quantitative bioanalytical methods validation and implementation: Best practices for chromatographic and ligand binding assays," C.T. Viswanathan et al (2007) The AAPS Journal 9 (1) Article 4, should be followed. In addition to pre-study validation, appropriate performance characteristics (accuracy, precision, quality control) should be documented for each analytical run during a study.

2.6.3 Stability

In order for samples to maintain their stability (degradation of analytes), they should be handled according to validated handling and storage procedures (Section 2.4.8, "Handling of Samples"). Validation should be included.

2.6.4 Limit of Quantitation (LOQ)

The analytical method chosen should be capable of assaying the analyte over the expected concentration range. A reliable lowest limit of quantitation should be established based on an intra- and inter-day coefficient of variation (CV) usually not greater than 20 percent. The limit of detection (LOD-the lowest concentration that can be differentiated from background levels) is usually lower than the LOQ. Values between LOQ and LOD should be identified as "Below Quantitation Limits".

2.6.5 Specificity

It should be demonstrated that endogenous compounds in the biologic matrix, nutrients, metabolites, and degradation products do not interfere with the assay method. In cases in which a stereospecific method is used, proof of the specificity should be documented. Specificity should be established using at least six independent sources of the same matrix being studied.

2.6.6 Recovery

The reproducibility of the absolute recovery of drug during the sample preparation procedure should be demonstrated and should be established for low, medium and high concentrations, based on the expected range.

2.6.7 Standard Curves

A standard curve demonstrates the range of concentrations over which an analyte can be reliably determined in matrix, using a minimum of five concentration points. Standard curves should be included with each run. The intra- and inter-run variability in the standard curves should be reported together with the coefficients of variation (CVs) obtained during sample measurement. These attributes will be used to determine the acceptability of the standard curve. The number of standards to be used will be a function of the dynamic range and nature of the concentration-detector response relationship. The standard curve should be determined using an appropriate algorithm.

2.6.8 Precision and Accuracy

The precision and accuracy of the assay should be determined for low, medium, and high drug concentrations in the biological matrix, based on the expected range. Accuracy for inter-day and intra-run should be within 15 percent of the nominal value. For precision, the CV should be no greater than 15 percent, except at the limit of quantitation, when a value no greater than 20 percent is acceptable.

2.6.9 Quality Control for Spiked Samples

For stable analytes, quality control (QC) samples should be prepared in the fluid of interest (e.g., plasma), including concentrations at least at the low, middle, and high segments of the calibration range. The quality control samples should be stored with the study samples. These are accepted for stability if they exhibit similar characteristics to those taken from volunteers.

For less stable analytes, daily or weekly quality control samples may have to be prepared.

A minimum of six QC samples, composed of three concentrations in duplicate, should be blinded and analysed with each batch of study samples for each analytical run.

2.6.10 Aberrant Values (Repeat Assays)

In most studies, some plasma or urine samples will require re-assay. Criteria for identifying these samples should be established ahead of time.

Certain aberrant values can be identified before breaking the analytical code. These values may be attributed to such factors as:

  1. processing errors;
  2. equipment failure;
  3. obviously poor chromatography; or
  4. quality control samples outside pre-defined tolerances.

Other apparently aberrant values may become evident after the analytical code is broken. In some such cases, the original assay value would show poor pharmacokinetic fit (but this should be applied with caution). In other cases, there might be a need to confirm a double peak. For aberrant values that have become evident after the analytical code is broken, the submission should note the reason for the repeat assay.

When the results of a repeat assay differ from the original by more than 15 percent, a third analysis should be performed. When three replicate analyses indicate that one is spurious, then the average of the other two should be used. The criteria used in selecting among replicates for inclusion in calculations should be stated.

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2.7 Analysis of Data

When all measurements of samples have been completed, the information collected should be analysed. This section discusses the data that should be recorded, the parameters of that data, the statistical analyses that should be performed on the data, and the format that should be used to present the results in reports.

2.7.1 Presentation of Data

The concentrations of the drug in plasma for each subject, the sampling time, and the formulation should be tabulated. Unadjusted, measured concentrations should be provided.

Deviations from the protocol (e.g., missed samples or late collection of samples) should be clearly identified in the tables.

Two graphs should be drawn for each subject and two for the mean values of all subjects, one linear and the other semilogarithmic. On these graphs, the drug concentrations from the reference and the test formulations should be plotted against the sampling times. Natural logarithms (ln) are to be employed. Usually, the semilogarithmic graphs should display the regression lines that are employed to estimate the terminal disposition rate constant (λ) for the two formulations.

2.7.2 Pharmacokinetic Parameters

Estimates of the following pharmacokinetic parameters should be tabulated for each subject-formulation combination:

  1. AUCT
    Area under the concentration-time curve measured to the last quantifiable concentration, using the trapezoidal rule.
  2. AUCI
    AUCT plus additional area extrapolated to infinity, calculated using λ.
  3. AUCT/AUCI
    The ratio of AUCT to AUCI.
  4. Cmax
    Maximum observed concentration.
  5. tmax
    Observed time after dosing, at which Cmax occurred.
  6. λ
    Terminal disposition rate constant.
  7. T1/2
    Terminal elimination half-life.

    Where the time to onset of action is important the following parameter should also be reported:

  8. AUCRefTmax
    Area under the curve to the time of the maximum concentration of the reference product, calculated for each study subject.

    Where multiple dose studies are conducted, the following parameters should also be reported:

  9. Cmin
    Minimum observed concentration.
  10. Cpd
    Pre-dose concentrations determined immediately before a dose at steady state.
  11. AUCΤau
    Area under the concentration versus time curve, over the dosing interval of the test formulation, calculated using the linear trapezoidal rule.
  12. Fluctuation
    (Cmax - Cmin) /(AUCΤau/Τau) × 100.

    Where comparative bioavailability is based upon urine data, the following parameters should be reported:

  13. Ae0-T
    Cumulative amount of drug excreted to last sampling time.
  14. Rmax
    Maximum rate of urinary excretion.

Additional pharmacokinetic parameters may also be presented, but the methods used to estimate them should be fully described. The means and coefficients of variation should be given for each parameter and for each formulation.

2.7.3 Data Collection

If an add-on, sequential or adaptive design is used, a description of how changes were made to collection of data should be provided.

2.7.4 Statistical Analysis

2.7.4.1 Outlier analysis

If the protocol states that outlier identification is to be performed, a summary of these results should be presented before any calculation of the confidence intervals is performed. The protocol test at the specified level should be performed and values identified. No more than 5 percent of subjects should be identified as outliers. If there are more, then the drug is more likely to be a highly variable drug and appropriate action should taken (i.e., use a study design and analysis appropriate for a highly variable drug). If the non-parameteric analysis is to be performed, the results should be presented in the analysis section below. If retesting is performed, results of the retest and re-analysis of the retest values and declaration and removal of original values should be shown. Uniformity of dosage units and dissolution should be re-tested (as per the applicable United States Pharmacopeia (USP) or European Pharmacopeia (EP) monograph) and results should be provided for the biobatches.

2.7.4.2 Model Fitting

By definition the crossover design is a mixed effects model with fixed and random effects. The basic 2 period crossover can be analysed according to a simple fixed effects model and least squares means estimation. Identical results will be obtained from a mixed effects analysis such as Proc mixed in SAS. If the mixed model approach is used, parameter constraints must be defined in the protocol. Higher order models must be analysed with the mixed model approach in order to estimate random effects properly.

2.7.4.3 Testing of fixed effects

A summary of the testing of sequence, period and formulation effects and other fixed effects should be presented. Explanations for significant effects should be given.

2.7.4.4 Estimation of random effects

A summary of the estimates of intersubject and intrasubject variances should be presented. For higher order designs estimates of subject by formulation and within formulation variance estimates should be given.

The analyses should include all data for all subjects (see Section 2.3.3, "Accounting for Drop-outs and Withdrawals") on measured data. Analysis based on less data should be justified.

Analysis should be carried out on the logarithmically transformed AUCT and Cmax data. The analysis and results for each parameter should be reported on a separate page as detailed in Appendix A2, "Sample Analysis for a Comparative Bioavailability Study". The reported results should include:

  1. means and CVs (across subjects) for each product;
  2. testing and estimates for fixed and random effects;
  3. AUCT and Cmax ratios for test versus reference products;
  4. the appropriate confidence interval about the parameter being analysed.
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Appendices

Appendix 1 Number of Subjects

The formula for calculating sample sizes is based on Hauschke et al., Sample size determination for bioequivalence assessment using a multiplicative model. Journal of Pharmacokinetics and Biopharmaceutics, 1992; 20(5): 557-561.

To use the table:

  1. Obtain an estimate of the intrasubject CV from the literature.
  2. Choose table A1-A or A1-B depending on the bioequivalence interval required.
  3. Choose the power required (80% or 90%).
  4. Choose an expected true ratio of test over reference means (usually 100%, but consider potency differences between the test and reference products).
  5. Go down the column until you arrive at the rounded CV. The number is the sample size.

This sample size algorithm should be provided in the study protocol and anticipated CV declared.

Note: Sample size calculations, based on a standard where only the mean estimate is required to fall within the bioequivalence interval, are not possible.

Table A1-A. Sample Sizes for 2×2 Crossover Design for Interval Hypotheses for 80-125% Rule to Attain a Power of 80 and 90%, Respectively in the Case of the Multiplicative Model (Linear interpolation can be used between stated CVs)
Power θ = μT/μR
CV (%) 0.85 0.90 0.95 1.00 1.05 1.10 1.15 1.20
80% 10 36 12 12* 12* 12* 12* 20 76
12 50 16 12* 12* 12* 14 28 110
14 68 20 12 12* 12 18 38 148
16 88 24 14 12 14 22 48 192
18 112 32 16 14 16 26 60 242
20 138 38 20 16 18 32 74 300
22 166 46 22 20 22 38 88 362
24 196 54 26 22 26 46 104 430
26 230 62 30 26 30 52 122 504
28 266 72 34 30 34 62 142 584
30 306 82 40 34 40 70 162 670
32 346 94 46 38 44 80 184 762
35 414 112 54 44 52 94 220 912
40 540 146 70 58 68 122 286 1190
45 684 182 88 72 84 154 362 1504
50 842 226 108 88 104 190 448 1858
55 1020 272 130 106 126 230 540 2246
60 1214 324 154 126 148 274 642 2674
90% 10 50 16 12* 12* 12* 14 28 106
12 70 20 12* 12* 12* 18 38 150
14 94 26 14 12 14 24 50 204
16 122 34 18 14 18 30 66 266
18 154 42 22 18 20 38 82 336
20 188 52 26 20 26 44 102 414
22 228 62 30 24 30 54 122 500
24 270 74 36 28 36 62 144 594
26 318 86 42 32 40 74 170 698
28 368 100 48 36 46 84 196 808
30 422 114 54 42 54 96 224 928
32 480 128 62 48 60 110 254 1054
35 574 154 74 56 72 132 304 1262
40 748 200 40 72 92 170 396 1648
45 946 252 120 90 116 214 502 2084
50 1168 312 148 112 144 264 618 2572
55 1412 376 178 134 172 320 748 3112
60 1680 446 212 160 206 380 890 3702

* Calculated sample size < 12

Table A1-B. Sample Sizes for 2×2 Crossover Design for Interval Hypotheses for 90-112% Rule to Attain a Power of 80 and 90%, Respectively in the Case of the Multiplicative Model (Linear interpolation can be used between stated CVs)
Power θ = μT/μR
CV (%) 0.95 1.00 1.05 1.10
80% 10 44 16 32 384
12 64 22 46 550
14 86 28 60 748
16 110 36 78 978
18 140 46 98 1236
20 172 56 122 1526
22 208 68 146 1846
24 246 80 174 2196
26 288 92 204 2578
28 334 108 236 2988
30 384 122 270 3430
32 436 140 306 3902
35 520 166 366 4668
40 680 216 478 6096
45 858 272 604 7714
50 1060 336 744 9524
55 1282 406 900 11524
60 1526 482 1072 13714
90% 10 62 20 44 530
12 88 28 62 762
14 118 36 84 1036
16 152 46 108 1354
18 192 58 136 1712
20 236 70 168 2112
22 286 84 202 2556
24 340 100 240 3042
26 398 116 280 3568
28 462 134 326 4138
30 530 154 372 4750
32 602 176 424 5404
35 720 210 506 6466
40 940 272 660 8444
45 1190 344 836 10686
50 1468 424 1030 13192
55 1776 512 1246 15960
60 2112 610 1484 18994
Table A1-C. Sample Sizes for Parallel Design for Interval Hypotheses for 80-125% Rule to Attain a Power of 80 and 90%, Respectively in the Case of the Multiplicative Model (Linear interpolation can be used between stated CVs)
Power θ = μT/μR
CV (%) 0.85 0.90 0.95 1.00 1.05 1.10 1.15 1.20
80% 10 70 20 12 12* 12 18 38 150
12 100 28 14 12 14 24 54 216
14 134 38 18 16 18 32 72 294
16 174 48 24 20 24 42 94 382
18 220 60 30 26 28 52 118 484
20 272 74 36 30 36 62 144 596
22 328 88 44 36 42 76 174 720
24 390 106 50 42 50 90 208 858
26 458 122 60 50 58 104 242 1006
28 530 142 68 56 66 122 282 1166
30 608 162 78 64 76 138 322 1338
32 692 184 88 74 86 158 366 1522
35 826 220 106 86 102 188 438 1820
40 1080 288 136 112 132 244 572 2376
45 1364 364 172 142 168 308 722 3008
50 1684 448 212 174 206 380 892 3712
55 2038 542 256 210 248 460 1078 4492
60 2424 644 304 250 296 548 1282 5344
90% 10 96 28 14 12 14 24 52 208
12 136 38 20 16 18 32 74 298
14 186 50 26 20 24 44 100 406
16 242 66 32 24 32 56 128 528
18 304 82 40 32 40 70 162 668
20 376 102 48 38 48 86 200 824
22 454 122 58 44 58 104 242 998
24 540 144 70 52 68 124 286 1186
26 632 170 80 62 78 144 336 1392
28 734 196 94 72 90 166 388 1614
30 842 224 106 82 104 192 446 1852
32 956 256 122 92 118 218 508 2108
35 1144 306 144 110 140 260 606 2520
40 1494 398 188 142 182 338 790 3292
45 1890 502 238 178 230 428 1000 4166
50 2332 620 292 220 284 526 1234 5142
55 2822 750 354 266 344 636 1492 6220
60 3358 892 420 316 408 758 1776 7402

* Calculated sample size < 12

Table A1-D. Sample Sizes for Parallel Design for Interval Hypotheses for 90-112% Rule to Attain a Power of 80 and 90%, Respectively in the Case of the Multiplicative Model (Linear interpolation can be used between stated CVs)
Power θ = μT/μR
CV (%) 0.95 1.00 1.05 1.10
80% 10 44 30 62 764
12 64 40 88 1100
14 86 54 118 1496
16 110 70 154 1952
18 140 88 194 2470
20 172 110 240 3050
22 208 132 290 3690
24 246 156 344 4390
26 288 182 404 5152
28 334 212 468 5974
30 384 242 536 6858
32 436 276 610 7802
35 520 330 730 9334
40 680 430 952 12190
45 860 542 1204 15428
50 1060 670 1486 19046
55 1282 810 1798 23044
60 1526 962 2140 27424
90% 10 62 36 84 1058
12 88 52 120 1522
14 118 68 164 2070
16 152 90 214 2704
18 192 112 268 3422
20 236 138 332 4222
22 286 166 400 5110
24 340 196 476 6080
26 398 230 558 7136
28 462 268 648 8274
30 530 306 742 9498
32 602 348 844 10806
35 720 416 1010 12928
40 940 542 1318 16884
45 1190 686 1668 21368
50 1468 846 2058 26380
55 1776 1022 2490 31920
60 2112 1216 2964 37986
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Appendix 2 Sample Analysis for a Comparative Bioavailability Study

The following tables and figures illustrate data collected and used in a sample bioavailability study. An analysis of this data is also shown.

Although a comparative bioavailability study may include many formulations, the basic analysis is the same - each test formulation is compared to a standard formulation.

The analysis of any comparative bioavailability study should have the following sections:

  1. A randomization scheme for the design, where all subjects randomized into the study are included and identified by code, sequence, and dates of the dosing periods for both test and reference formulations (see Section A2.1.).
  2. A summary of drug concentrations (graphic and quantitative) at each sampling time for each subject for both test and reference formulations (see Section A2.2.).
  3. A summary of the estimates of the parameters as defined in Section A2.3 for both test and reference formulations, including the means, standard deviations, and CVs (see Section A2.4.).
  4. A formal statistical analysis of the relevant parameters with comparisons of the test formulations to the reference formulations (see Sections A2.5 through A2.9.).

All the sample statistical analyses that follow have the minimum two formulations (test and reference) given on two dosing days or periods.

A2.1 Randomization Scheme of the Design

Shown in Table A2-A is the randomization scheme for the cross-over design used in the study. In any study, all subjects who were randomized into the study should be included. Even those subjects that did not complete the study should be included and identified accordingly. Subject numbers that appear on informed consent forms and reporting forms should be given. Also, if any other subject identification code was used, it should be given here. The sequence to which the subject was randomized should be given. Finally, all dosing periods and dates should be given.

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A2.2 Summary of Drug Concentrations

Tables A2-B and A2-C show a list of the concentrations at each sampling time for each subject for the test and reference formulations, respectively. If any concentration is missing, it should be identified, and the reason it is missing given (e.g., lost sample; sample not collected).

Although no formal statistical analysis is required at each sampling time, it is recommended that summary statistics be given at each sampling time for each formulation. It is also helpful if the lower limit of quantitation of the analytical method is given in this table.

Table A2-A: Randomization Scheme of the Cross-over Design for the Comparison of Test (T) Versus Reference (R) Formulations
Subject Period
Number ID Sequence May 14, 2008 May 21, 2008
001 A TR T R
002 B RT R T
003 C RT R T
004* D TR T -
005 E TR T R
006 F RT R T
007 G TR T R
008 H RT R T
009 T TR T R
010** I RT - -
011 K RT R T
012 L TR T R
013 M TR T R
014 N RT R T
015 O RT R T
016 P TR T R
017 Q RT R T
018 R TR T R

* Subject did not appear for second period.

** Subject did not appear for either period.

Table A2-B: Drug Concentrations (nanograms (ng)/millilitre (mL)) for the Test Formulation
ID Seq Period Sampling Times (hours)
0.00 0.33 0.66 1.0 1.5 2.0 3.0 4.0 6.0 8.0 12.0 16.0
A TR 14 May 0.00 BQL* 52.01 95.03 122.20 77.88 65.15 46.24 19.20 14.99 BQL* BQL*
B RT 21 May 0.00 BQL* 56.66 80.85 102.00 86.41 63.81 49.20 24.00 11.37 8.24 BQL*
C RT 21 May 0.00 28.63 201.50 189.80 188.70 136.20 97.64 64.53 32.08 20.63 14.59 BQL*
E TR 14 May 0.00 BQL* 9.04 34.32 47.70 52.79 59.47 32.61 17.61 8.76 BQL* BQL*
F RT 21 May 0.00 BQL* 55.33 66.40 58.97 48.29 43.19 34.23 17.30 6.15 BQL* BQL*
G TR 14 May 0.00 BQL* 33.15 45.64 54.19 34.13 32.78 21.73 10.75 8.35 BQL* BQL*
H RT 21 May 0.00 35.38 79.14 100.90 70.71 48.43 30.73 26.19 8.65 6.83 BQL* BQL*
I TR 14 May 0.00 BQL* 64.57 76.52 89.51 86.21 69.04 50.96 21.55 13.71 7.55 BQL*
K RT 21 May 0.00 BQL* 79.34 99.41 154.80 58.60 57.12 32.57 19.82 BQL* BQL* BQL*
L TR 14 May 0.00 14.78 55.54 56.88 46.87 37.29 28.75 25.20 BQL* BQL* BQL* BQL*
M TR 14 May 0.00 BQL* BQL* BQL* BQL* BQL* 8.37 23.15 19.74 16.49 5.74 5.18
N RT 21 May 0.00 BQL* 37.76 28.58 21.56 19.02 13.25 12.44 6.38 BQL* BQL* BQL*
O RT 21 May 0.00 BQL* 27.85 43.30 43.30 32.57 29.59 25.42 16.89 7.68 BQL* BQL*
P TR 14 May 0.00 BQL* 68.25 52.57 51.97 28.64 23.70 12.74 BQL* BQL* BQL* BQL*
Q RT 21 May 0.00 BQL* 5.90 13.00 27.54 13.32 12.34 9.81 9.73 BQL* BQL* BQL*
R TR 14 May 0.00 BQL* 18.92 35.77 53.93 60.43 47.44 41.72 16.66 8.87 5.49 BQL*
MEAN - - 0.00 4.92 52.81 63.69 70.87 51.26 42.65 31.80 15.04 7.73 2.60 0.32
STD - - 0.00 11.26 47.05 45.04 49.76 33.66 24.64 15.42 8.60 6.57 4.42 1.29
CV - - - 228.66 89.09 70.72 70.22 65.66 57.79 48.51 57.18 84.94 169.84 400

* Lower limit of quantitation is 5 ng/mL. Any concentration below this limit is reported as Below Quantification Limit (BQL) except at time 0. Zero is used in the calculation of area under the curve (AUC) for times preceding the first observed concentration and in the calculation of summary statistics.

Table A2-C: Drug Concentrations (ng/mL) for the Reference Formulation
ID Seq Period Sampling Times (hours)
0.00 0.33 0.66 1.0 1.5 2.0 3.0 4.0 6.0 8.0 12.0 16.0
A TR 14 May 0.00 BQL* 116.40 124.60 126.20 107.60 45.65 33.22 16.11 12.60 BQL* BQL*
B RT 21 May 0.00 BQL* 88.45 121.40 206.90 179.00 84.53 40.02 38.01 15.12 5.39 BQL*
C RT 14 May 0.00 BQL* BQL* 95.57 122.80 103.20 101.70 57.65 23.85 14.59 6.29 BQL*
E TR 21 May 0.00 BQL* 37.23 37.26 35.90 28.87 28.48 25.10 24.91 6.72 BQL* BQL*
F RT 14 May 0.00 BQL* 29.25 62.88 64.26 84.67 45.21 25.05 17.18 8.47 BQL* BQL*
G TR 21 May 0.00 BQL* 6.89 50.04 55.27 51.68 38.58 26.19 7.79 BQL* BQL* BQL*
H RT 14 May 0.00 BQL* 113.50 218.70 125.80 69.77 45.03 32.78 18.55 5.42 BQL* BQL*
I TR 21 May 0.00 BQL* 181.90 135.80 96.51 90.50 62.58 30.43 18.50 BQL* BQL* BQL*
K RT 14 May 0.00 BQL* 42.71 58.75 59.68 54.37 44.35 22.94 11.58 6.95 BQL* BQL*
L TR 21 May 0.00 BQL* 14.29 21.32 24.32 25.56 25.51 10.49 5.49 BQL* BQL* BQL*
M TR 21 May 0.00 BQL* 8.21 48.87 57.05 56.32 42.08 24.79 16.54 15.81 7.60 BQL*
N RT 14 May 0.00 BQL* 47.20 34.90 34.90 24.19 20.11 8.08 7.27 BQL* BQL* BQL*
O RT 14 May 0.00 BQL* BQL* 20.35 70.88 70.60 70.38 40.51 26.93 8.20 BQL* BQL*
P TR 21 May 0.00 BQL* 39.23 86.29 97.46 52.26 40.53 26.74 12.54 BQL* BQL* BQL*
Q RT 14 May 0.00 BQL* BQL* 30.86 88.38 37.67 29.28 14.99 6.38 BQL* BQL* BQL*
R TR 21 May 0.00 BQL* BQL* 24.84 59.27 98.82 69.98 46.50 23.46 9.91 6.96 BQL*
MEAN - - 0.00 - 45.33 73.28 82.85 70.94 49.62 29.09 17.19 6.49 1.64 -
STD - - 0.00 - 53.30 54.49 46.24 39.78 22.51 12.88 8.83 5.98 2.96 -
CV - - - - 117.59 74.37 55.82 56.08 45.37 44.28 51.38 92.23 180.73 -

* Lower limit of quantitation is 5 ng/mL. Any concentration below this limit is reported as Below Quantification Limit (BQL) except at time 0. Zero is used in the calculation of area under the curve (AUC) for times preceding the first observed concentration and in the calculation of summary statistics.

A2.3 List of Parameters and Definitions

Table A2-D shows a list of the parameters used in the analysis and their definitions. If any other parameters are used, they should also be clearly defined.

Table A2-D: Parameter Definitions
Parameter Definition
Cmax Maximum observed concentration (ng/mL).
tmax Sampling time at which Cmax occurred (h).
AUCT Area under the raw concentration versus time curve calculated using the trapezoidal rule from time 0 to LQCT (ng.h/mL).
AUCI Area to infinity = AUCT + CT/λ where CT is the estimated concentration at LQCT (ng.h/mL).
AUCT/AUCI × 100 Percent of the area measured by AUCT relative to the extrapolated total AUC.
λ Terminal disposition rate constant calculated from the points on the log-linear end of the concentration versus time curve (h-1).
TLIN Time point where log-linear elimination begins (h).
LQCT Lowest Quantifiable Concentration Time. Time at which the last concentration occurred that is above the lower limit of quantitation (h).
t½ Drug half-life = ln2/λ = 0.693/λ (h).
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A2.4 Summaries of Parameter Estimates

Tables A2-E and A2-F list, for each subject, the estimates of the parameters defined in Table A2-D for the test and reference formulations respectively. Summary statistics (arithmetic means or medians, standard deviations, and CVs) should be given for each formulation.

Table A2-E: Parameter Estimates for Each Subject Given the Test Formulation
ID Seq Period Test Formulations
Cmax
(ng/mL)		 tmax
(h)		 AUCT
(ng.h/mL)		 AUCI
(ng.h/mL)		 AUCT
(%)		 λ
(h-1)		 TLIN
(h)		 LQCT
(h)		 t½
(h)
A TR 14 May 122 1.50 365 409 89 0.3002 2.0 8.0 2.3
B RT 21 May 102 1.50 405 432 94 0.2384 3.0 12.0 2.9
C RT 21 May 202 0.66 703 774 91 0.1776 4.0 12.0 3.9
E TR 14 May 59 3.00 233 256 91 0.3680 3.0 8.0 1.9
F RT 21 May 66 1.00 247 265 93 0.3902 3.0 8.0 1.8
G TR 14 May 54 1.50 178 205 87 0.2768 3.0 8.0 2.5
H RT 21 May 101 1.00 246 263 94 0.3437 2.0 8.0 2.0
I TR 14 May 90 1.50 408 433 94 0.2486 3.0 12.0 2.8
K RT 21 May 155 1.50 315 372 85 0.3379 3.0 6.0 2.1
L TR 14 May 57 1.00 140 331 42 0.1318 3.0 4.0 5.3
M TR 14 May 23 4.00 165 195 85 0.1485 6.0 16.0 4.7
N RT 21 May 38 0.66 88 113 78 0.2620 2.0 6.0 2.6
O RT 21 May 43 1.00 183 215 85 0.2671 3.0 8.0 2.6
P TR 14 May 68 0.66 122 148 83 0.5031 1.5 4.0 1.4
Q RT 21 May 28 1.50 68 113 60 0.1833 1.5 6.0 3.8
R TR 14 May 60 2.00 275 292 94 0.2546 3.0 12.0 2.7
MEAN* - - 79 1.50 259 301 84 0.2770 3.0 8.0 2.8
STD - - 48 0.89 158 164 14 0.0967 1.1 3.3 1.1
CV - - 61 59.35 61 54 17 34.92 37.3 38.5 37.9

* for tmax, TLIN, and LQCT, these are medians.

Table A2-F: Parameter Estimates for Each Subject Given the Reference Formulation
ID Seq Period Reference Formulation
Cmax
(ng/mL)		 tmax
(h)		 AUCT
(ng.h/mL)		 AUCI
(ng.h/mL)		 AUCT
(%)		 λ
(h-1)		 TLIN
(h)		 LQCT
(h)		 t½
(h)
A TR 21 May 126 1.50 375 418 90 0.2660 3.0 8.0 2.6
B RT 14 May 207 1.50 595 613 97 0.2900 3.0 12.0 2.4
C RT 14 May 123 1.50 471 492 96 0.2666 4.0 12.0 2.6
E TR 21 May 37 1.00 190 224 85 0.2653 3.0 8.0 2.6
F RT 14 May 85 2.00 257 285 90 0.3114 3.0 8.0 2.2
G TR 21 May 55 1.50 175 190 92 0.5437 3.0 6.0 1.3
H RT 14 May 219 1.00 382 398 96 0.4047 2.0 8.0 1.7
I TR 21 May 182 0.66 361 406 89 0.3837 3.0 6.0 1.8
K RT 14 May 60 1.50 218 236 93 0.3580 3.0 8.0 1.9
L TR 21 May 26 2.00 92 105 88 0.4208 2.0 6.0 1.6
M TR 21 May 57 1.50 269 327 82 0.1373 6.0 12.0 5.1
N RT 14 May 47 0.66 106 125 85 0.3246 2.0 6.0 2.1
O RT 14 May 71 1.50 290 313 93 0.4028 3.0 8.0 1.7
P TR 21 May 97 1.50 230 266 87 0.3644 2.0 6.0 1.9
Q RT 14 May 88 1.50 144 156 92 0.4964 3.0 6.0 1.4
R TR 21 May 99 2.00 344 369 93 0.2370 4.0 12.0 2.9
MEAN - - 99 1.50 281 308 90 0.3420 3.0 8.0 2.2
STD - - 59 0.41 136 138 4 0.1017 1.0 2.4 0.9
CV - - 60 29.05 48 45 5 29.7262 32.6 29.2 39.4
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A2.5 Area Under the Curve to the Last Quantifiable Concentration (AUCT) analysis

Tables A2-G, A2-H, and A2-I provide the complete analysis required for AUCT. Table A2-G lists the AUCT estimates on the raw scale and the log scale. Also given is the test AUCT as a percentage of the reference AUCT. Summary statistics are calculated for each variable.

Table A2-G: AUCT (ng.h/mL) Analysis - Data
ID Raw Scale Log Scale
Test
AUCT 		Reference
AUCT 		Relative
AUCT (%)		 Test
ln(AUCT)		 Reference
ln(AUCT)
A 365 375 97 5.90 5.93
B 405 595 68 6.00 6.39
C 703 471 149 6.55 6.16
E 233 190 123 5.45 5.25
F 247 257 96 5.51 5.55
G 178 175 102 5.18 5.17
H 246 382 65 5.51 5.94
I 408 361 113 6.01 5.89
K 315 218 144 5.75 5.39
L 140 92 153 4.94 4.52
M 165 269 61 5.11 5.59
N 88 106 83 4.48 4.66
O 183 290 63 5.21 5.67
P 122 230 53 4.81 5.44
Q 68 144 47 4.22 4.97
R 275 344 80 5.62 5.84
MEAN 259 281 94 5.39 5.52
STD 158 136 35 0.61 0.52
CV 61 48 37 - -

Table A2-H gives the analysis of variance (ANOVA) for the cross-over design model for ln(AUCT). This analysis gives the appropriate intrasubject variance estimate, MS (Residual), for the calculation of the 90% confidence interval. Any significant effects in the model, other than Subject(Seq), should be investigated. The intrasubject and intersubject CVs should also be calculated.

Table A2-H: AUCT (ng.h/mL) Analysis - Type3 Tests of Fixed Effects for ln(AUCT)
Effects Numerator df Denominator df F Value Prob > F*
Seq 1 14 0.09 0.7699
Period 1 14 0.33 0.5751
Form 1 14 1.88 0.1916

* p-value

Table A2-I: AUCT (ng.h/mL) Analysis - Variance Estimates for ln(AUCT)
Parameter Variance CV
Subject(Seq) 0.2648 55.0665
Residual 0.0729 27.5136

Intrasubject CV = 100 × (MSResidual)0.5 = 100 × (0.0729)0.5 = 27 percent
Intersubject CV = 100 × (MSSubject (Seq) )0.5 = 100 × (0.2648)0.5 = 51.45 percent

The AUC ratio estimate and its 90% confidence interval are derived in the calculations shown in Table A2-J. Because this study had a balanced design (i.e., an equal number of subjects per sequence) the difference is simply the difference in the arithmetic means of the ln(AUC)s. If the study was not balanced, then the least-squares mean estimate for each formulation should be used to form this difference, together with the appropriate standard error.

Table A2-J: AUCΤ (ng.h/mL) Analysis - Calculations

Difference = Test x‾ - Reference x‾ = 5.39 - 5.52 = -0.13
SEDifference = (2MSResidual/n)0.5 = (2 × 0.0729/16)0.5 = 0.0955
AUC Ratio = 100 × eDifference = 100 × e(5.39-5.52) = 88%
90% Confidence Limits
Lower, Upper = 100 × e (Difference ± t0.05,14× SEDifference)
Lower = 100 × e(-0.13 - 1.761 × 0.0955) = 74%
Upper = 100 × e(-0.13 + 1.761 × 0.0955) = 104%

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A2.6 Maximum Observed Concentration (Cmax) Analysis

The necessary information and summary for the analyses of Cmax is shown in Table A2-J.

Table A2-K: Cmax (ng/mL) Analysis - Data
ID Raw Scale Log Scale
Test
Cmax 		Reference
Cmax 		Relative
Cmax (%)		 Test
ln(Cmax)		 Reference
ln(Cmax)
A 122 126 97 4.81 4.84
B 102 207 49 4.62 5.33
C 202 123 164 5.31 4.81
E 59 37 160 4.09 3.62
F 66 85 78 4.20 4.44
G 54 55 98 3.99 4.01
H 101 219 46 4.61 5.39
I 90 182 49 4.49 5.20
K 155 60 259 5.04 4.09
L 57 26 223 4.04 3.24
M 23 57 41 3.14 4.04
N 38 47 80 3.63 3.85
O 43 71 61 3.77 4.26
P 68 97 70 4.22 4.58
Q 28 88 31 3.32 4.48
R 60 99 61 4.10 4.59
MEAN 79 99 98 4.21 4.42
STD 48 59 68 0.59 0.61
CV 61 60 69 - -
Table A2-L: Cmax (ng/mL) Analysis - Type3 Tests of Fixed Effects for ln(Cmax )
Effects Numerator df Denominator df F Value Prob > F*
Seq 1 14 1.02 0.3306
Period 1 14 0.13 0.7264
Form 1 14 1.77 0.2052

* p-value

Table A2-M: Cmax (ng.h/mL) Analysis - Variance Estimates for ln(Cmax )
Parameter Variance CV
Subject(Seq) 0.161 41.7977
Residual 0.2048 47.6698

Intrasubject CV = 100 × (MSResidual)0.5 = 100 × (0.2048)0.5 = 45.25 percent
Intersubject CV = 100 × (MSSubject (Seq) )0.5 = 100 × (0.1610)0.5 = 40.12 percent

Table A2-N: Cmax Analysis - Calculations

Difference = Test x‾ - Reference x‾ = 4.21 - 4.42 = -0.21
SEDifference = (2MSResidual/N)0.05 = 0.1600
Cmax Ratio = 100 × eDifference = 100 × e(4.21 -4.42) = 81%
90% Confidence Limits
Lower, Upper = 100 × e(Difference ± t0.05,14× SEDifference) Lower = 100 × e(-0.21 - 1.761 × 0.1600) = 61% Upper = 100 × e(-0.21 + 1.761 × 0.1600) = 107%

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A2.7 Concentration versus Time Profiles (Subject A)

Figure 1 shows a plot of the concentration versus time profile for subject A. Each plot should include profiles for all formulations given to that subject. Similar profiles should be given for each subject.

Figure 1: Concentration-Time Profile for Subject A

Figure 1: Concentration-Time Profile for Subject A

Figure 2 gives a plot of the ln (concentration) versus time profile for subject A. This plot should contain the regression lines from which the terminal disposition rate constants (λ) were estimated. This line should start and end at the time points considered to be in the log-linear elimination phase. Any point that was not used to estimate the regression line should be identified.

Figure .2: Ln (concentration) - Time Profile for Subject A

Figure .2: Ln (concentration) - Time Profile for Subject A

Figure 3 shows a profile of the arithmetic means over all subjects for each formulation and sampling time.

Figure 3: Average Concentration-Time Profile for All Subjects

Figure 3: Average Concentration-Time Profile for All Subjects

Figure 4 shows a profile of the ln (arithmetic means) over all subjects for each formulation and sampling time.

Figure 4: Ln(average concentration)-Time Profile for All Subjects

Figure 4: Ln(average concentration)-Time Profile for All Subjects

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Appendix 3 Glossary of Terms

Accuracy - The extent to which an experimentally determined value agrees with the true or absolute value.

Adverse event - Any untoward medical occurrence in a patient or clinical investigation subject administered a pharmaceutical product and which does not necessarily have to have a casual relationship with this treatment.

AUC (area under the curve) - The area under the concentration versus time curve. The AUC symbol may be qualified by a specific time (e.g., 8 hours, or AUC8), time of last quantifiable concentration (AUCT), or infinity (AUCI).

AUCI (AUC to infinity) - The area obtained by extrapolating to infinity the AUCTau. This can be calculated by adding CT/λ to AUCTau where CT is the estimated last quantifiable concentration and λ is the terminal disposition rate constant.

AUC ratio - The ratio of geometric means of the test and reference AUCs. It is calculated as the antilogarithm of the difference between the means of the logarithms (ln) of the test and reference AUCs. The Cmax ratio should be similarly calculated .

AUCT (AUC to the last quantifiable concentration) - This describes the AUC to the time of the last quantifiable concentration. AUCT is calculated from observed data at specific time points by the linear trapezoidal rule.

AUCτau (AUC over a dosing interval) - Area under the concentration versus time curve, over the dosing interval in a multiple-dose study, calculated using the linear trapezoidal rule

Balanced cross-over design - A cross-over design in which subjects are randomly assigned into each sequence in equal numbers.

Bioavailability - The rate and extent of absorption of a drug into the systemic circulation.

Bioequivalence - A high degree of similarity in the bioavailabilities of two pharmaceutical products (of the same galenic form) from the same molar dose, that are unlikely to produce clinically relevant differences in therapeutic effects, or adverse effects, or both.

Bioequivalent means that test and reference products containing an identical drug or drugs, after comparison in an appropriate bioavailability study, were found to meet the standards for rate and extent of absorption specified in this guideline.

Cmax (maximum observed concentration) - The observed maximum or peak concentration.

Cmin (minimum observed concentration) - The observed minimum concentration.

CPD (pre-dose concentration) - Pre-dose concentration from same time of each day.

CT (last quantifiable concentration) - The last concentration that can be quantified and is equal to or greater than the lowest limit of quantitation.

Dropout - A subject in a clinical trial who for any reason fails to continue in the trial until the last visit required of him/her by the study protocol.

Excipient - Any ingredient, excluding the drug substances, incorporated in a formulation for the purpose of enhancing stability, usefulness or elegance, or facilitating preparation; for example, base, carrier, coating, colour, flavour, preservative, stabilizer, and vehicle.

Fluctuation - Fluctuation between maximum and minimum concentrations within a dosing interval in a multiple-dose study, calculated as (Cmax - Cmin) /(AUCΤau/Τau) × 100.

Formulation - An ingredient or mixture of specific ingredients; that is, drug substances and excipients in specific amounts, defining a given product.

Label - Includes any legend, word, or mark attached to, included in, belonging to, or accompanying any drug or package. (Section 2 of the Food and Drugs Act.)

Last quantifiable concentration (CT) - See CT.

Lowest limit of detection(LOD) - The lowest concentration that can be differentiated from background levels.

Lowest limit of quantitation (LOQ) - The lowest measured concentration on the standard curve having an acceptable degree of precision. The LOQ cannot be below the lowest nominal concentration on the same standard curve.

Maximum observed concentration (Cmax) - See Cmax.

Measured content of the drug product - The drug contents of representative samples (i.e., the lots used in the bioavailability/bioequivalence study) of the test and reference drug products established as percent label claim by an appropriate assay, such as USP.

Modified-release dosage form - A dosage form for which the drug-release characteristics of time-course or drug-release location are chosen to accomplish therapeutic or convenience objectives not offered by conventional dosage forms.

Modified-release dosage forms are drug formulations that differ from conventional formulations in the rate at which the drug is released. For the purpose of these guidances, modified-release forms include formulations designed to meet one or more of the following objectives:

To delay disintegration, de-aggregation, or dissolution so that the drug's rate of degradation is altered.

To delay or decrease the rate of absorption so that the likelihood of gastrointestinal or other adverse effects is diminished (e.g., enteric-coated forms).

To provide effective drug concentrations for a longer period of time after a single dose.

To deliver the drug initially at a rate similar to that obtained with the conventional form, and to provide effective drug concentrations for a longer period of time.
To minimize fluctuations in drug concentrations during the dosing interval.

To provide, after single administration, multiple peaks and troughs in the serum concentration-time curves similar to those achieved after repeated dosing with the conventional formulation.

90% Confidence interval - An interval about the estimated value that provides 90 percent assurance that it contains the true value. The method of constructing the interval is described in Appendix 2, "Sample Analysis for a Comparative Bioavailability Study").

Non-linear kinetics - A general term referring to dose or time dependency in pharmacokinetic parameters arising from factors associated with absorption, first-pass metabolism, binding, and excretion.

Precision - The closeness of agreement of values obtained in the analysis of replicate samples of the same specimen, usually indicated by the coefficient of variation (relative standard deviation).

Pro-drug - An inactive (or much less active) precursor that is bio-transformed to the active drug.

Rate of absorption- The rate at which a drug reaches the systemic circulation after oral administration.

Standard meal - A meal of known carbohydrate, protein, fat, and fluid composition.

Terminal disposition rate constant (λ) - The rate constant estimated from the slope of the terminal portion of the ln (drug concentration) versus time curve. The terminal half-life (t½) is calculated from this constant (t½=ln2/λ). (Also known as Terminal Elimination Rate Constant.)

Terminal elimination rate constant - See Terminal Disposition Rate
Constant (λ).

Time of maximum observed concentration (tmax) - The time after administration of the drug at which Cmax is observed.

Date Modified: 2010-01-15

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Important Notices