Bioequivalence and Average Bioequivalence (ABE) Main concerns with ABE Design and limitations of ABE studies Individual and Population Bioequivalence (IBE and PBE) Metrics Design and sample size of replicate studies for IBE and PBE Conduct and analysis Example Issues

1. Average, Individual and Population
Bioequivalence – Understanding the
True Variability of a Generic Product
1st Annual Generic Medicine Middle East Conference
April 14-15th, Crown Plaza, Yas Island, Abu Dhabi
Dr. Bhaswat S. Chakraborty
Sr. Vice President, R&D, Cadila Pharmaceuticals

2. Outline
• Bioequivalence and Average Bioequivalence (ABE)
• Main concerns with ABE
• Design and limitations of ABE studies
• Individual and Population Bioequivalence (IBE and PBE)
• Metrics
• Design and sample size of replicate studies for IBE and PBE
• Conduct and analysis
• Example
• Issues
• Conclusion

3. Bioequivalent Drug Products
• Pharmaceutical Equivalent
– Same dose and dosage form, ideally same assay and
content uniformity
– Could be pharmaceutical alternative dose or form
• Bioequivalent
– Statistical and pharmacokinetic equivalent
– Equivalent rate and extent of absorption
• 90% CI of relative mean Cmax and AUC: 80-125%
• Interpretation: Therapeutic equivalence

4. Currently Practiced Bioequivalence
• For almost all generic drus today, the regulatory standard is
“average bioequivalence (IBE)”
• Concluded from 2-product, 2-period, crossover studies with
fixed effects
• That means
– An average patient (volunteer) will have
– An average Cmax and AUC
– From an average reference and test product
– That are not significantly different
• Problem: cannot individualize or generalize for population

5. Three Main Concerns with ABE
• Safety
– Generic N– as safe as the Gen 2
Brand?
Gen 1
• Prescribability
– Can a physician have an equal Brand ?
choice of prescribing Brand or
Generic N to drug-naïve
patients?
Gen 3 Gen N
• Switchability
– Can a patient stabilized on
Generic1 be switched to
Generic N?

6. Design of 2-product, 2-period,
crossover studies
Period I W Period II
A
Sequence 1 Test S Reference
H
Subjects Randomizaion O
U
Sequence 2 Reference T
Test

7. Limitations of ABE
• Produces medical dilemma
• Ignores distribution of Cmax and AUC
• Within subject variation is not accurate
• Ignores correlated variances and subject-by-formulation
interaction
• One criteria irrespective of inherent patterns of product, drug
or patient variations
• Although rare, but may not be therapeutic equivalent

8. Other Choices in BE
and their Conditions
• Individual Bioequivalence (IBE)
– Addresses switchability
• Population Bioequivalence (PBE)
– Addresses prescribability
• Design and statistics of IBE & PBE
– Take into account both population mean
and variance
– Address switchability and thereby subject-fomulation interaction
– Provide same level of confidence (consumer’s risk of 5%) and power
– Accept formulations with reduced within subject variability

9. Individual Bioequivalence (IBE) Metric
( µT − µ R ) 2 + σ D + (σ WT − σ WR )
2 2 2
≤ θI
max(σ WR , σ W 0 )
2 2
Where
(ln1.25) 2 +ε
θI =
σ2 0
W
Where
µT = mean of the test product
µR = mean of the reference product
σD2 = variability due to the subject-by-formulation interaction
σWT2 = within-subject variability for the test product
σWR2 = within-subject variability for the reference product
σW02 = specified constant within-subject variability

10. Population Bioequivalence (PBE) Metric
≤θP
Where
µT = mean of the test product
µR = mean of the reference product
σTT2 = total variability (within- and between-subject) of the test product
σTR2 = total variability (within- and between-subject) of the reference
product
σ02 = specified constant total variance

11. FDA Recommended Designs of
IBE/PBE studies
• 2-product, 2-period, crossover studies with fixed
effects are not recommended
• 3- or 4-period, replicate designs with restricted sequences
are recommended
TRTR or TRT
RTRT RTR
• Estimation of sWR2, sWT2, and sD2 are required along with
response means
• One can use either reference or constant scaling (without
much concern about increased Type I error due to multiple
testing)

12. Design of 4-period, Replicate Studies
W W W
PI PII PIII PIV
A A A
S S S
Sequence 1 T R T R
H H H
O O O
Subjects Randomizaion
U U U
Sequence 2 R T T T R T T
1 2 3

13. Sample Size for IBE
Minimum 12 Source: US FDA Guidelines for Industry

14. Sample Size for PBE
Minimum 18 Source: US FDA Guidelines for Industry

15. Conduct of Replicate Studies
• Generally dosing, environmental control, blood sampling
scheme and duration, diet, rest and sample preparation for
bioanalysis are all the same as those for 2-period, crossover
studies
• Avoid first-order carryover (from preceding formulation) &
direct-by-carryover (from current and preceding formulation)
effects
– Unlikely when the study is single dose, drug is not endogenous,
washout is adequate, and the results meet all the criteria
• If conducted in groups, for logistical reasons, ANOVA model
should take the period effect of multiple groups into account
• Use all data; if outliers are detected, make sure that they don’t
indicate product failure or strong subject-formulation
interaction

16. Standards for IBE and PBE
 E ( yR − yT ) 2 − E ( yR − y R ) 2
'
 if E ( yR − yR )2 / 2 ≥ σ 02
'
 E ( yR − yR ) 2 / 2
'
θ =
 E ( yR − yT ) − E ( yR − y R )
2 ' 2
if E ( yR − yR )2 / 2 < σ 02
'

 σ02
Where σ0 is constant variability.
For IBE, YT, YR and YR’ are PK responses from the test and
two reference formulations to the same individual
For PBE, YT, YR and YR’ are PK responses from the test
and two reference formulations to the different individuals

17. Declaring IBE and PBE
H0: θ ≥ θI or θP; HA: < θI or θP
IBE or PBE is claimed when 95% confidence upper bound of
of θ is less than θI or θP and the observed ratio of geometric
means is within bioequivalence limits of 80 – 125%.

18. Analysis by SAS Proc Mixed

19. Example: Two Cyclosporine Formulations
Test: open circles; Ref.: closed circles; n = 20
Canafax et al.(1999) Pharmacology 59:78–88

20. ABE – Two Cyclosporine Formulations
Test: open circles; Ref.: closed circles; n = 20
Canafax et al.(1999) Pharmacology 59:78–88

21. IBE – Two Cyclosporine Formulations
Test: open circles; Ref.: closed circles; n = 20
<θI
εI=0.04-0.05;Constant Scaled σ W0
2
= 0.2; θI = 2.245; IBE declared
Canafax et al.(1999) Pharmacology 59:78–88

22. Another Example: Two Alverine Formulations
Highly variable drug, intra-subject CV ~35%; n = 48
Chakraborty et al.(2010) Unpublished Data

23. ABE, IBE & PBE: Two Alverine Formulations
Highly variable drug, intra-subject CV ~35%; n = 48
Chakraborty et al.(2010) Unpublished Data

24. Issues
• Primary
– Justification and need for an IBE criterion
– Financial and human resource burden of conducting replicate study
design
– appropriateness of the statistical methodology
• Advanced
– Mean-variance trade-off (if the term σWT2 – σWR2 ) is sufficiently negative,
the test product could be deemed BE with a large difference in the
averages of a BE metric; resolved difference cannot exceed 80-125%)
– Extra-reference 2x3 designs (TRR,RTR)
• Advantages, disadvantages
– ABE from replicate studies
• CR products, highly variable drugs

25. Conclusions
• ABE serves well for wide therapeutic index and
uncomplicated PK drugs
• ABE has limitations
– Ignores switchability and prescribability; ignores distributions of C max and AUC;
estimate of within subject variation is not accurate; ignores correlated
variances and subject-by-formulation interaction….
• IBE provides for switchability and PBE for prescribability
• Replicate studies are required for IBE and PBE
• Analysis of variability is done by a mixed effects model
• NTR, HVDP, CR formulations can be assured for IBE and
PBE
• There are methodological issues for IBE and PBE which must
be discussed and resolved

26. References
• US FDA (1999). In Vivo Bioequivalence Studies
Based on Population and Individual Bioequivalence
Approaches. Food and Drug Administration,
Rockville, Maryland, August, 1999.
• US FDA (2001). Guidance for Industry: Statistical
Approaches to Establishing Bioequivalence. Food
and Drug Administration, Rockville, Maryland,
January, 2001.

27. Acknowledgements:
Priyanka Kocheta
Somnath Sakore
Thank you very much