Regulatory requirements for BE
and Existing Guidelines
Alfredo García – Arieta, PhD
WHO Workshop on Assessment of Bioequivalence Data, 31 August – 3 September, 2010, Addis Ababa
Subjects: Drop-outs and withdrawals
 Healthy volunteers: inclusion / exclusion criteria
 Sufficient number to compensate for drop-outs or
withdrawals
 Replacement of subjects complicates the statistical model
and analysis
 Reason for withdrawal (e.g. AE or personal reason) must
be reported
 Protocol must state replacement policy or add-on designs
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Subjects: Drop-outs and withdrawals
 Recruit a few subject more to compensate for drop-outs
or withdrawals
 Protocol should state whether samples from this extra
subjects will be assayed if not required for stat. analysis
 EU EMA, on the contrary:
– The data from all treated subjects should be treated equally
– It is not acceptable to have a protocol which specifies that
‘spare’ subjects will be included in the analysis only if needed
as replacements for other subjects who have been excluded
– It should be planned that all treated subjects should be included
in the analysis, even if there are no drop-outs.
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
EU Subject Accountability
 Ideally, all treated subjects should be included in the
statistical analysis.
 However, subjects in a crossover trial who do not provide
evaluable data for both of the test and reference products
(or who fail to provide evaluable data for the single period
in a parallel group trial) should not be included.
 The analysis for each comparison should be conducted
excluding the data from the treatments that are not
relevant for the comparison in question (e.g. a three
period study including two references, US and EU).
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Exclusion of subjects in EU
 Unbiased assessment of results from randomised studies requires
that all subjects are observed and treated according to the same
rules
 These rules should be independent from treatment or outcome
 In consequence, the decision to exclude a subject from the
statistical analysis must be made before bioanalysis
 In principle any reason for exclusion is valid provided it is specified
in the protocol and the decision to exclude is made before
bioanalysis
 However the exclusion of data should be avoided, as the power of
the study will be reduced and a minimum of 12 evaluable subjects
is required
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Exclusion of subjects in EU
 Examples
– Vomiting
– Diarrhoea
– the use of concomitant medication, in exceptional cases,.
 It should be noted in the CRF as the study is being conducted
 Clearly described and listed in the study report
 Exclusion of data cannot be accepted on the basis of statistical
analysis or for pharmacokinetic reasons alone, because it is
impossible to distinguish the formulation effects from other effects
influencing the pharmacokinetics.
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Exception where subject can be excluded
 A subject with lack of any measurable concentrations or
only very low plasma concentrations for reference
 Very low plasma concentrations: if its AUC is less than
5% of reference medicinal product geometric mean AUC
(which should be calculated without inclusion of data from
the outlying subject)
 The exclusion of data due to this reason will only be
accepted in exceptional cases and may question the
validity of the trial.
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Exceptions where subject must be excluded
 Subjects with non-zero baseline concentrations > 5% of
Cmax
 Excluded from bioequivalence calculation to avoid carryover effects
 In case of immediate release products it can be caused
by:
– subject non-compliance (mouth check)
– insufficient wash-out period (sufficient wash-out)
 The samples from subjects excluded from the statistical
analysis should still be assayed and the results listed
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Not to exclude
 Subjects whose AUC(0-t) covers less than 80% of AUC(0∞)
 But if the percentage is less than 80% in more than 20%
of the observations then the validity of the study may
need to be discussed
 This does not apply if the sampling period is 72 h or more
and AUC(0-72h) is used instead of AUC(0-t)
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Add-on designs
 If bioequivalence cannot be demonstrated because:
– Larger variability than expected
– Larger difference than expected but still within 20%
 An add-on design can be performed using not less than
half the number of subjects in the initial study
 Provided this was anticipated in the protocol
 Combining data only if:
– Same protocol
– Same batches
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Add-on designs
 Add-on designs must be given appropriate statistical
treatment
 Canadian add-on design requires:
–
–
–
–
–
No interaction formulation effect x study phase
No statistical difference in variability of both phases
But the consumer’s risk is increased
Statistically inadequate
It must be a sequential design with control of the alpha
expenditure (EMA)
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Two-stage design
 An initial group of subjects can be treated and their data analysed.
 If bioequivalence has not been demonstrated an additional group
can be recruited and the results from both groups combined in a
final analysis.
 If this approach is adopted appropriate steps must be taken to
preserve the overall type I error of the experiment and the stopping
criteria should be clearly defined prior to the study.
 The analysis of the first stage data should be treated as an interim
analysis and both analyses conducted at adjusted significance
levels (with the confidence intervals accordingly using an adjusted
coverage probability which will be higher than 90%)
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Two-stage design
 For example, using 94.12% confidence intervals for both
the analysis of stage 1 and the combined data from stage
1 and stage 2 would be acceptable, but there are many
acceptable alternatives and the choice of how much
alpha to spend at the interim analysis is at the company’s
discretion.
 The plan to use a two-stage approach must be prespecified in the protocol along with the adjusted
significance levels to be used for each of the analyses.
 When analysing the combined data from the two stages,
a term for stage should be included in the ANOVA model.
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Genetic Phenotyping
 Phenotyping for metabolizing activity for high-clearance
drugs that are metabolized by enzymes that are subject
to genetic polymorphism, e.g. propranolol
 Phenotyping of subjects can be considered for studies of
drugs that show phenotype-linked metabolism and for
which a parallel group design is to be used, because it
allows fast and slow metabolizers to be evenly distributed
in the two groups of subjects
 Phenotyping could also be important for safety reasons,
determination of sampling times and wash-out periods in
cross-over design studies
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Study standardization
 Standardization of study conditions is important to minimize the
magnitude of variability other than in the pharmaceutical products
 Standardization should cover:
–
–
–
–
–
Exercise
Diet
fluid intake
Posture
Restriction of the intake of alcohol, caffeine, certain fruit juices and
concomitant medicines for a specified time period before and during the
study
 Volunteers should not take any other medicine, alcoholic beverages
or over the-counter (OTC) medicines and supplements for an
appropriate interval either before or during the study
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Study standardization
 In the event of emergency, the use of any non-study medicine must
be reported (dose and time of administration).
 Physical activity and posture should be standardized as far as
possible to limit their effects on gastrointestinal blood flow and
motility
 The same pattern of posture and activity should be maintained for
each day of the study
 The time of day at which the study drug is to be administered
should be specified
 All meals should be standardized and the composition stated in the
study protocol and report.
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Selection of dose
 In bioequivalence studies the molar equivalent dose of
multisource and comparator product must be used
– If possible
– If not, potency correction (see Canadian Guideline)
– Applicable if PK is dose-proportional
 Generally the marketed strength
with the greatest sensitivity to
bioequivalence assessment should
be administered as a single unit
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Selection of dose
 This will usually be the highest marketed strength
– Drug with low solubility and dose-proportional PK
– Drug with more than proportional increase in PK (AUC)
R T
R T
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Selection of dose
 A lower strength in the linear
part if PK shows a less than
proportional increase with
dose due to saturation of
absorption process
 Both a lower strength in the
linear part and the highest
strength if PK shows a less
than proportional increase
with dose due to solubility
limitations
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Selection of dose
 A higher dose (i.e. more than one dosage unit) may be employed
when analytical difficulties exist
 In this case the total single dose should not exceed the maximal
daily dose of the dosage regimen
 Alternatively, the application of area under the curve (AUC)
truncated to 3 × median tmax of the comparator formulation would
avoid problems of lack of assay sensitivity in many cases
 In certain cases a study performed with a lower strength can be
considered acceptable if this lower strength is chosen for reasons
of safety.
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Sample fluids and their collection
 Usually blood should be the biological fluid sampled
 In most cases the analyte is measured in serum or plasma
 Urine only if the analyte cannot be measured in plasma, etc.
– Not necessary that “the API is excreted predominantly unchanged in the
urine”
– The volume of each sample must be measured at the study centre, where
possible immediately after collection, and included in the report
– In most cases the exclusive use of urine excretion data should be avoided
as this does not allow estimation of the tmax and Cmax
 Samples should be processed and stored under conditions that
have been shown not to cause degradation of the analytes
 The sample collection methodology must be specified in the study
protocol.
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Parameters to be assessed
 The shape of the plasma concentration versus time curves is
assessed by:
– Cmax is peak exposure
– AUC is extent of exposure
– Tmax is the time of peak exposure
 Focus now on exposure instead of absorption
– AUC is extent of absorption if PK is linear /not saturated
– Tmax and Cmax gives some information on rate of absorption
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Primary parameters to be assessed
 For single-dose studies, the following parameters should
be measured or calculated:
– AUC0–t, where t is the last sampling time point with a
measurable concentration in the individual formulation tested.
• The method of calculating AUC-values should be specified.
• In general AUC should be calculated using the linear/log trapezoidal
integration method.
• In practice linear/linear trapezoidal rule is more frequent
• The use of compartmental-based parameters is not recommended.
– Cmax is the maximum or peak concentration observed
representing peak exposure of API (or metabolite) in plasma,
serum or whole blood.
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Secondary parameters to be assessed
 Secondary parameters:
– AUC0-inf representing total exposure,
• where AUC0- = AUC0–t + Clast/;
• Clast is the last measurable drug concentration
•  is the terminal or elimination rate constant
– tmax is the time after administration of the drug at which Cmax
is observed.
 Additional information:
– T1/2 is the plasma (serum, whole blood) half-life
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Application of truncated AUC in BE
 In US-FDA and EU: AUC0-72 h for drugs with long half-life
 There are two important advantages to the use of truncated areas:
– more blood samples can be clustered around tmax to give greater precision
in the estimation of both tmax and Cmax;
– high assay sensitivity to define the disposition phase is not required.
 The applicability of the truncated AUC approach merits particular
consideration in the following cases:
– where low concentrations occur in the terminal portion of the plasma
concentration versus time curve, which may not be quantifiable by means of
an adequately validated, sensitive analytical method; and
– for products of APIs with long half-lives.
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Application of truncated AUC in BE
 When considering BE of immediate-release formulations for
systemic delivery, the most important portion of the plasma
concentration versus time curve is until the absorption phase is
complete
 On the other hand, the disposition phase does not illustrate
formulation differences between the multisource product and
comparator product in the bioequivalence decision-making process
 Gaureault examined the use of partial (truncated) AUC using Monte
Carlo simulations and found a high degree of concordance
between the bioequivalence decision based on the partial area
truncated to four times tmax and the area extrapolated to infinity
 The evidence suggests that for immediate-release formulations it is
unnecessary to take blood samples beyond four times tmax.
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Parameters to be assessed in SS and Urine
 For steady-state studies (prolonged release):
–
–
–
–
AUC is AUC over one dosing interval () at steady-state;
Cmax;
Cmin is concentration at the end of a dosing interval;
Peak trough fluctuation is percentage difference between Cmax
and Cmin
– Immediate release: only AUC and Cmax.
 When urine samples are used
– Cumulative urinary recovery (Ae) instead of AUC
– Maximum urinary excretion rate instead of Cmax.
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Parameters to be assessed in SS
 For steady-state studies (prolonged release):
– AUC
– Cmax
– Cmin
– PTF
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Analyte: parent or metabolite
 Generally, evaluation of pharmacokinetic bioequivalence
will be based upon the measured concentrations of the
parent drug released from the dosage form rather than
the metabolite
 The concentration–time profile of the parent drug is more
sensitive to changes in formulation performance than a
metabolite, which is more reflective of metabolite
formation, distribution and elimination.
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Analyte: parent or metabolite
 In some situations it may be necessary to measure
metabolite concentrations rather than those of the parent
drug:
– The measurement of concentrations of therapeutically active
metabolite is acceptable if the substance studied is a pro-drug.
– Measurement of a metabolite may be preferred when
concentrations of the parent drug are too low to allow reliable
analytical measurement in blood, plasma or serum for an
adequate length of time, or when the parent compound is
unstable in the biological matrix.
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Analyte: parent or metabolite
 It is important to state a priori in the study protocol which chemical
entities (pro-drug, drug (API) or metabolite) will be analysed in the
samples.
 It is important to note that measurement of one analyte, API or
metabolite, carries the risk of making a type-I error (the consumer
risk) to remain at the 5% level
 However, if more than one of several analytes is selected
retrospectively as the bioequivalence determinant, then both the
consumer and producer risks change.
 When measuring the active metabolites wash-out period and
sampling times may need to be adjusted to enable adequate
characterization of the pharmacokinetic profile of the metabolite.
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Enantiomers
 A non-stereoselective assay is currently acceptable for
most pharmacokinetic bioequivalence studies
 When the enantiomers have very different
pharmacological or metabolic profiles, assays that
distinguish between the enantiomers of a chiral API may
be appropriate
 Stereoselective assay is also preferred when systemic
availability of different enantiomers is demonstrated to be
non-linear
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Enantiomers in US FDA
 For BE studies, the racemate using an achiral assay.
 Measurement of individual enantiomers in BE studies is
recommended only when all of the following conditions
are met:
– the enantiomers exhibit different PD characteristics,
– the enantiomers exhibit different PK characteristics,
– primary efficacy and safety activity resides with the minor
enantiomer, and
– Nonlinear absorption is present (as expressed by a change in
the enantiomer concentration ratio with change in the input rate
of the drug) for at least one of the enantiomers
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Enantiomers in EU
 The use of achiral bioanalytical methods is generally
acceptable.
 However, the individual enantiomers should be measured
when all the following conditions are met:
– the enantiomers exhibit different pharmacokinetics
– the enantiomers exhibit pronounced difference in
pharmacodynamics
– the exposure (AUC) ratio of enantiomers is modified by a
difference in the rate of absorption.
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Enantiomers in EU
 The individual enantiomers should also be measured if
the above conditions are fulfilled or are unknown
 If one enantiomer is pharmacologically active and the
other is inactive or has a low contribution to activity, it is
sufficient to demonstrate bioequivalence for the active
enantiomer
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Statistical Analysis: Concern
 The primary concern in BE assessment is to limit the risk
of a false declaration of equivalence
 Statistical analysis of the BE trial should demonstrate that
a clinically significant difference in bioavailability between
the multisource product and the comparator product is
unlikely
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Statistical Analysis: Method
 The statistical procedures should be specified in the
protocol before the data collection starts
 The statistical method for testing PK BE is based upon
the determination of the 90% confidence interval around
the ratio of the log-transformed population means
(multisource/comparator) for the pharmacokinetic
parameters under consideration and by carrying out two
one-sided tests at the 5% level of significance
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Statistical Analysis: Conclusion
 To establish PK BE, the calculated confidence interval
should fall within a preset bioequivalence limit
– 80-125% for the 90% CI is the conventional acceptance range
– 80-125% for the 90% CI for AUC and Cmax always in FDA
• Except scaling for HVD based on intra-subject variability
– 80-125% for 90 CI% of AUC and for PE of Cmax in Canada
– 90-111% for 90% CI of AUC and 80-125% for CI of Cmax in
Canada
– 80-125% for 90% CI of AUC and Cmax normally in EU
• Except scaling for Cmax in HVD based on intra-subject variability
• Narrowing to 90-111 in AUC and/or Cmax in NTI drugs
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Statistical Analysis: Why 0.80-1.25?
 The procedures should lead to a decision scheme which
is symmetrical with respect to the two formulations (i.e.
leading to the same decision whether the multisource
formulation is compared to the comparator product or the
comparator product to the multisource formulation)
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Statistical Analysis: log-transformation
 All concentration-dependent pharmacokinetic parameters
(e.g. AUC and Cmax) should be log-transformed using
either common logarithms to the base 10 or natural
logarithms
 The choice of common or natural logs should be
consistent and should be stated in the study report.
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Statistical Analysis: ANOVA
 Logarithmically transformed, concentration-dependent
pharmacokinetic parameters should be analysed using
analysis of variance (ANOVA)
 Usually the ANOVA model includes the formulation,
period, sequence or carry-over and subject factors
 Parametric methods, i.e. those based on normal
distribution theory, are recommended for the analysis of
log-transformed bioequivalence measures
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Statistical Analysis: in log scale
 The general approach is to construct a 90% confidence
interval for the quantity μT−μR and to reach a conclusion
of pharmacokinetic equivalence if this confidence interval
is within the stated limits
 The nature of parametric confidence intervals means that
this is equivalent to carrying out two one-sided tests of
the hypothesis at the 5% level of significance
 The antilogs of the confidence limits obtained constitute
the 90% confidence interval for the ratio of the geometric
means between the multisource and comparator products
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Statistical Analysis
 The same procedure should be used for analysing
parameters from steady state trials or cumulative urinary
recovery, if required:
– For steady-state studies:
• AUC is AUC over one dosing interval () at steady-state;
• Cmax;
• Cmin is concentration at the end of a dosing interval;
• Peak trough fluctuation is percentage difference between Cmax and
Cmin.
– When urine samples are used
• Cumulative urinary recovery (Ae) instead of AUC
• Maximum urinary excretion rate instead of Cmax.
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Statistical Analysis: Tmax
 For tmax descriptive statistics should be given
 If tmax is to be subjected to a statistical analysis this
should be based on non-parametric methods and should
be applied to untransformed data
– For drugs where onset of action is important
– EU before 90% CI, but now not required 90% but PE
 A sufficient number of samples around predicted maximal
concentrations should have been taken to improve the
accuracy of the tmax estimate
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Statistical Analysis: other parameters
 For parameters describing the elimination phase (T1/2)
only descriptive statistics should be given
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Statistical Analysis: outliers
 Methods for identifying and handling of possible outlier data should
be specified in the protocol.
 Medical or pharmacokinetic explanations for such observations
should be sought and discussed
 As outliers may be indicative of product failure, post hoc deletion of
outlier values is generally discouraged.
 An approach to dealing with data containing outliers is to apply
distribution-free (non-parametric), statistical methods
– No longer valid or acceptable
– No parametric methods ignore outlier values and it is equivalent to remove
them
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Statistical Analysis: non-parametric
 If the distribution of log-transformed data is not normal,
non-parametric statistical methods can be considered
–
–
–
–
No longer valid
Outliers make the distribution non-normal
Only tmax is analyzed with non-parametric methods
ANOVA is robust despite deviations from Normality
 The justification of the intent to use nonparametric
statistical methods should be included a priori in the
protocol.
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Acceptance ranges: AUC-ratio
 The 90% confidence interval for this measure of relative
bioavailability should lie within a bioequivalence range of
0.80–1.25
 If the therapeutic range is particularly narrow, the
acceptance range may need to be reduced based on
clinical justification
– Canada: 90.00-111.11%
– EU: 90.00-111.11.%
 A larger acceptance range may be acceptable in
exceptional cases if justified clinically
– HVD in US FDA (not in Guidance for Industry)
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Acceptance ranges: Cmax-ratio
 In general the acceptance limit 0.80–1.25 should be applied
 However, this measure of relative bioavailability is inherently more
variable, and in certain cases a wider acceptance range (e.g. 0.75–
1.33) may be acceptable
– EU for HVD only widening in Cmax based on intra-subject variability
 The range used must be defined prospectively and should be
justified, taking into account safety and efficacy considerations.
 In exceptional cases, a simple requirement for the point estimate to
fall within bioequivalence limits of 0.80–1.25 may be acceptable
with appropriate justification in terms of safety and efficacy
– Canada
– Not statistically correct.
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Acceptance ranges: tmax-difference
 Statistical evaluation of tmax makes sense only if there is a
clinically relevant claim for rapid onset of action or
concerns about adverse effects
 The nonparametric 90% confidence interval for this
measure of relative bioavailability should lie within a
clinically relevant range.
– EU presently only based on Point Estimate
 For other pharmacokinetic parameters the same
considerations as outlined above apply
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Fixed-dose combination products
 The study design should follow the same general
principles as described in previous sections
 The multisource FDC product should be compared with
the pharmaceutically equivalent comparator FDC product
 In certain cases (e.g. when no comparator FDC product is
available on the market) separate products administered
in free combination can be used as a comparator
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Fixed-dose combination products
 Sampling times should be chosen to enable the
pharmacokinetic parameters of all APIs to be adequately
assessed.
 The bioanalytical method should be validated on respect
to all compounds measured
 Statistical analyses should be performed with
pharmacokinetic data collected on all active ingredients;
the 90% confidence intervals of test/comparator ratio of
all active ingredients should be within acceptance limits.
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Highly variable drugs: The problem
 A “highly variable drug” has been defined as an API with a withinsubject variability of > 30% in terms of the ANOVA-CV
 Moreover “highly variable drugs” are generally safe drugs with
shallow dose–response curves
 Proving the bioequivalence of medicinal products containing “highly
variable drugs” is problematic because the higher the ANOVA-CV,
the wider the 90% confidence interval
 Thus large numbers of subjects must be enrolled in studies
involving highly variable drugs to achieve adequate statistical
power
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Highly variable drugs: The solutions
 Some regulatory authorities permit the use of broadened
bioequivalence limits provided there is adequate
justification
 For example, the regulatory agency could broaden the
bioequivalence limits from 0.8–1.25 to 0.75–1.33 taking
into consideration the therapeutic category of the drug
– In EU previously.
– Not presently
– Now acceptance range is widen based on intra-subject
variability if clinically justified for Cmax only
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Highly variable drugs: The solutions
 Some regulatory authorities permit the use of scaling to
broaden the bioequivalence limits
– South-Africa
 In a two-period design, the limits are scaled to the
residual standard deviation, or in a replicate design, to the
within-subject standard deviation of the comparator
formulation
– In US-FDA and EU a replicate design in necessary to estimate
the real intra-subject variability of the comparator
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Highly variable drugs: Japan’s solution
 Some regulatory authorities allow the following acceptance criteria:
– “Products are considered to be bioequivalent, if the 90% confidence interval
of average ratios of AUC and Cmax between test and reference products is
within the acceptable range of 0.8–1.25
– If the confidence interval is not in the above range, test products are
accepted as bioequivalent, if the following three conditions are satisfied:
• the total sample size of the initial bioequivalence study is not less than 20 (n =
10/group) or pooled sample size of the initial and add-on subject studies is not less than
30
• the ratio of geometric least squares means of AUC and Cmax between the multisource
and comparator product are between 0.9 and 1.11; and
• dissolution rates of test and reference products are evaluated to be equivalent under all
dissolution testing conditions
– This rule cannot be applied to slowly dissolving products from which less
than 80% of a drug dissolves within the final testing time (2 hr in pH 1.2
medium and 6 hr in others) under any conditions of the dissolution tests
described
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Highly variable drugs: Canada’s solution
 Some regulatory authorities do not allow for any
adjustments
– In Canada Cmax variability is not a problem because it is
usually assessed with Point Estimate
– In US-FDA no widening if the drug is not HVD
– Now in EU no widening for AUC
– Now in EU no widening for Cmax if the drug is not HVD or if it is
not clinically justified
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Highly variable drugs: Proposal
 AUC is usually critical: no widening despite variability
– Like Canada and EU
 Cmax can be widening if the comparator Cmax is HV
–
–
–
–
A clinical justification is necessary (EU)
A replicate design is necessary (EU and US-FDA)
Predefined in the protocol
Proportionality constant of EU is statistically more adequate
than the one of US-FDA with respect to consumer’s risk
• Endrenyi L, Tothfalusi L. Regulatory conditions for the determination of
bioequivalence of highly variable drugs. J Pharm Pharm Sci 2009;
12(1):138-149
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Limits at CV = 30 or 25%
Acceptance Limits in original scale with ScABE
versus within-subject variability
1.6
1.5
1.4
Acceptance Limits
1.3
1.2
1.1
1
0.9
0.8
0.7
0.6
0.00
0.05
0.10
0.15
0.20
0.25
Coefficient of variation (%)
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
0.30
0.35
0.40
0.45
0.50
Highly variable drugs: EU
 Highly variable drug products (HVDP) are those whose
intra-subject variability for a parameter is larger than 30%
 If an applicant suspects that a drug product can be
considered as highly variable in its rate and/or extent of
absorption, a replicate cross-over design study can be
carried out
– Any replicate design is acceptable
– The FDA recommends a specific one (RTR/TRR)
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Highly variable drugs: EU
 Those HVDP for which a wider difference in Cmax is considered
clinically irrelevant based on a sound clinical justification can be
assessed with a widened acceptance range
 If this is the case the acceptance criteria for Cmax can be widened
to a maximum of 69.84 – 143.19%
 For the acceptance interval to be widened the bioequivalence study
must be of a replicate design where it has been demonstrated that
the within-subject variability for Cmax of the reference compound in
the study is >30%
 The applicant should justify that the calculated intra-subject
variability is a reliable estimate and that it is not the result of outliers
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Highly variable drugs: EU
 If this is the case the acceptance criteria for Cmax can be
widened to a maximum of 69.84 – 143.19%
 The extent of the widening is defined based upon the
within-subject variability seen in the bioequivalence study
using scaled-average-bioequivalence according to [U, L]
= exp [±k·sWR],
–
–
–
–
Where U is the upper limit of the acceptance range,
L is the lower limit of the acceptance range,
k is the regulatory constant set to 0.760 and
sWR is the within-subject standard deviation of the logtransformed values of Cmax of the reference product
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Highly variable drugs: EU
 The table below gives examples of how different levels of
variability lead to different acceptance limits using this
methodology
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Highly variable drugs: EU
 The geometric mean ratio (GMR) should lie within the
conventional acceptance range 80.00-125.00%.
 The possibility to widen the acceptance criteria based on
high intra-subject variability does not apply to AUC where
the acceptance range should remain at 80.00 – 125.00%
regardless of variability
 It is acceptable to apply either a 3-period or a 4-period
crossover scheme in the replicate design study
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Narrow Therapeutic Index Drugs
 It is difficult to define NTI drugs
– US-FDA list in SUPAC guideline
– JAPAN list is also available in BE guideline
– Canada Guideline on Critical Dose Drugs
• “Critical dose drugs” are defined as those drugs where comparatively small differences
in dose or concentration lead to dose-and concentration-dependent, serious therapeutic
failures and/or serious adverse drug reactions which may be persistent, irreversible,
slowly reversible, or life threatening, which could result in inpatient hospitalization or
prolongation of existing hospitalization, persistent or significant disability or incapacity,
or death. Adverse reactions that require significant medical intervention to prevent one
of these outcomes are also considered to be serious
• Cyclosporine , Digoxin, Flecainide, Lithium, Phenytoin, Sirolimus, Tacrolimus,
Theophylline, Warfarin
– EU: case by case
• Ciclosporine: AUC and Cmax should be narrowed in both fed and fasting state studies
• Tacrolimus: AUC should be narrowed
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Narrow Therapeutic Index Drugs
 FDA
– 80.00 – 125%
 Canada
– 90% CI AUC T/R should be within 90.0 to 112.0%
– 90% CI Cmax T/R should be between 80.0 and 125.0%
– Both the fasted and fed states
 EU
– In specific cases, the acceptance interval for AUC should be tightened to
90.00-111.11%
– Where Cmax is of particular importance for safety, efficacy or drug level
monitoring the 90.00-111.11% acceptance interval should also be applied for
this parameter
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa
Thank you very much for your attention!
WHO Workshop on Assessment of Bioequivalence Data
31 August – 3 September, 2010, Addis Ababa