FDA什么是高度生物变异性药物

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Product C (Cmax)
2
Test Reference
1
ln Cmax
0
-1
-2
37 Subjects in Numerical Order
25
Product C (AUClast)
3
Test Reference
ln Cmax
2
1
0
37 Subjects in Numerical Order
15
Product A: 90%CIs
Measure
T v R1
T v R2
R1v R2 72 - 102 85 - 112
ln Cmax 103 - 146 89 - 126 ln AUClast 97 - 128 94 - 125
ANOVA-1 (GLM)
16
Product B (ABE4)
M. Tanguay et al., AAPS Abstract, November 2002 (Data from 800 fasting studies)
When Will a Drug Formulation Pass or Fail the BE Criteria? Experience from 1200 Studies
GMR%
107 109
CV%
33.7 27.1
90%CI
94-123 97-122
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Dealing with HVDs

HVDs are generally safe drugs High WSV of Cmax is often the problem A 90%CI is not required for Cmax in the case of ‘uncomplicated drugs’... a potential solution for HVD/Ps?
Studies Failing (%) 6% 10% 26% 62%
Intra-individual CV%z < 10% 10-20% 20-30% >30%
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BE Requirements for HVD/Ps

At present, there are no set specific acceptance criteria for HVD/Ps We shall apply 90%CIs to both Cmax and AUC in this presentation for acceptance in order to stimulate discussion
Measure
ln Cmax ln AUClast
ANOVA-1: (GLM)
GMR%
99 92
CV%
29.6 32.5
90%CI
87-111 81-106
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Product C (ABE4) Ref-1 versus Ref-2
Measure
ln Cmax ln AUClast
ANOVA-1: (GLM)


22 healthy volunteers 2-Formulation, 4-Period, 4-Sequence Cross-Over design Washout period, 2 weeks 17 plasma samples collected over 96 hours
17
Product B (Cmax)
9
Residual Variance (ABE1)

ANOVA 1: Contains several variance components WSV in ADME, plus a component of analytical variability Within formulation variability (WFV) Subject by formulation interaction (S*F) Unexplained random variability
9 9 27 17
9 27
17
9
27 17
17
27
20
Product B (ABE4) Test versus Ref
Measure
ln Cmax ln AUClast
ANOVA-3: (MIXED)
GMR%
112 113
CV%
36.7 28.0
90%CI
95-131 101-126
21
Product B (ABE4) Test-1 versus Test-2
Highly Variable Drugs & Drug Products-A Rationale for Solution of a Persistent Problem Kamal K. Midha C.M., Ph.D, D.Sc College of Pharmacy and Nutrition, University of Saskatchewan & Pharmalytics, Inc. Saskatoon Canada
12
Cmax
Ref-1 Ref-2 Ref-1
AUClast
Ref-2
6 6 7 13 6 20 16 13 7
7
13 16 20 27
16 20 6 13 7
16 20 27
27
27
13
Cmax
Ref-1 Ref-2 Ref-1
AUClast
Ref-2
6 6 7 13 6 20 16 13 7
30
Suggested Approaches*

BE Study


Multiple dose study BE on the basis of metabolite Area correction method to reduce intra-subject variability Application of stable isotope technique
7
13 16 20 27
16 20 6 13 7
16 20 27
27
27
14
Product A (ABE3) 3 x 37 Subjects
Measure ln Cmax ln AUClast
ANOVA-2 (GLM)
GMR% 115 110
CV% 42.3 34.8
90%CI 99-133 97-124
3
The Width of the 90%CI



The width depends on: the Within-Subject Variability (WSV) the number of subjects in the study The wider the 90%CI, the more likely it is to fall outside the limits of 80-125% Highly Variable Drugs are a problem
2
What are Highly Variable Drugs?


Drugs with high within-subject variabilities in Cmax and/or AUC are called ‘highly variable drugs’ (HVDs) ANOVA-CV ≥ 30% HVDPs are products in which the drug is not highly variable, but the product is of poor pharmaceutical quality high within-formulation variability
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Product A: ANOVA-CV%
Study 1a
ln Cmax ln AUClast
aBioequivalence bPharmacokinetic
Study 2b
39.9 36.6
Study 3c
37.2 33.0
42.3 34.8
study, n=37 (3-period study) study n=11 (solution, 3-period study) cPharmacokinetic study, n=9, CPZ with & without quinidine (2-period study)
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Product C (ABE4) Test versus Ref
Measure
ln Cmax ln AUClast
ANOVA-3: (MIXED)
GMR%
104 103
CV%
41.7 35.8
90%CI
92-117 93-114
27
Product C (ABE4) Test-1 versus Test-2
Measure
ln Cmax ln AUClast
ANOVA-1: (GLM)
GMR%
97 97
CV%
26.0 18.7
90%CI
84-111 87-107
22
Product B (ABE4) Ref-1 versus Ref-2
Measure
ln Cmax ln AUClast
ANOVA-1: (GLM)
Test-1 Test- 2 Ref-1 Ref-2
17 9 27
9
9 17 27
9 27 17
17
27
18
Product B (Cmax)
Test-1 Test- 2 Ref-1 Ref-2
17 9 27
9
9 17 27
9 27 17
17
27
19
Product B (AUC)
Test-1 Test- 2 Ref-1 Ref-2
1
Outline



Highly variable drugs (HVD) and highly variable drug products (HVDP) Examples: Studies from our archives Widening the bioequivalence (BE) limits Arbitrary preset wider BE limits Scaling Conclusions
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Replicate Designs (ABE3 or ABE4)

ANOVA-2: Formulation Period Subject Subject by Formulation Interaction

Residual Variance (approx = WSV) Can separate test and reference variances
* From Published Literature
31
Suggested Approaches*

Statistical Considerations

Scaled ABE criteria GMR-dependent scale ABE limits Individual Bioequivalence (IBE)
GMR%
87 87
CV%
49.9 39.2
90%CI
66-113 71-108
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ProducБайду номын сангаас C (ABE4)


37 healthy volunteers 2-Formulation, 4-Period, 4-Sequence Cross-Over design Washout period, 1 week 15 plasma samples collected over 13.5 hr
4
90%CIs & BE Limits
125%
Green Low WSV (~15%) Narrow 90%CI Passes Red High WSV (~35%) Wide 90%CI Lower bound <80% Fails
100%
80%
GMR & the # subjects same in both cases 5

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Some Examples

Product A Product B


Product C
8
Study Design and Data Analysis



ABE1: Non-replicated study design Using two or more period data ANOVA 1 ABE3: Partially replicated study design Using three period Data Reference product is replicated ANOVA 2 ABE4: Fully replicated study design Using four period data Both test and reference products are replicated ANOVA 3