1

Chapter 9Chapter 9

Bridging Studies & Multi-Regional Bridging Studies & Multi-Regional

TrialsTrials

                 

 

2

Outline

Introduction

Taiwan’s Situations

An Bayesian Approach

Discussion

3

Introduction

ICH (International Conference on Harmonisation) E5

Ethnic Factors in the Acceptability of

Foreign Clinical Data

The purpose of this guidance is to facilitate the

registration of medicines among ICH regions

by recommending a framework for evaluating

the impact of ethnic factors upon a medicine’s

effect, i.e., its efficacy and safety at a particular

dosage and dose regimen.

4

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 150.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Asian (n = 342)HR = 0.66 (0.48, 0.91), P = .011

RR = 12.0%

Non-Asian (n = 1350)HR = 0.93 (0.81, 1.08), P = .364

RR = 6.5%

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

1.0

0.9

0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1

0.00 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

—— IRESSA®

------ Placebo

Time, mo

Pat

ien

ts s

urv

ivin

g (

%)

Ethnic Difference

5

Objectives of ICH E5

To describe the characteristics of foreign clinical data that will facilitate their extrapolation to different populations

and support their acceptance as a basis for registration of a medicine in a new region

To describe regulatory strategies that minimize duplication of clinical data and facilitate acceptance of foreign clinical data in the new region

To describe the use of bridging studies, when necessary, to allow extrapolation of foreign clinical data to a new region

To describe development strategies capable of characterizing ethnic factor influences on safety, efficacy, dosage, and dose regimen

6

Bridging Data PackageA bridging data package consists of

1) Selected information from the complete clinical data package (CCDP) that is relevant to the population of the new region, including pharmacokinetic data, and any preliminary pharmacodynamic and dose-response data,

and

2) If needed, a bridging study to extrapolate the foreign efficacy and/or safety data to the new region.

7

Complete Clinical Data Package

A clinical data package intended for

registration containing clinical data that fulfill the

regulatory requirements of the new region and

containing pharmacokinetic data relevant to the

population in the new region

8

Bridging StudyA bridging study is defined as a supplemental study

performed in the new region to provide

pharmacodynamic or clinical data on efficacy,

safety, dosage, and dose regimen in the new

region that will allow extrapolation of the

foreign clinical data to the new region.

9

Ethnic Factors Intrinsic Ethnic Factors are more genetic and

physiologic in nature

e.g., genetic polymorphism, age, gender, height, weight, lean body mass, body composition, and disease conditions, etc.

Extrinsic Ethnic Factors are more social and cultural in nature

e.g., environment, culture, medical practice, health insurance, practices in clinical trials or conduct

10

Bridging Studies

• ICH E5

• Only after the medicine is approved in

the original region

• Performed in the new region

11

Taiwan’s Situations

12

Taiwan Before Bridging Study An approved local clinical trial study report is

required for the new drug application in Taiwan—July 7 Announcement in 1993

Disadvantage: A sample size of 40 as required would be

difficult to demonstrate significant importance clinically or statistically

The study design of the local trial usually only repeated a study that has been done in the foreign

countries but in a smaller sample size;The study has not been designed based on the medical situation in Taiwan

13

Taiwan’s Strategy to Implement Bridging Study Smoothly convert compulsory Local Clinical Trial (LCT) to

meaningful bridging study Gradually, stepwise announce waived local clinical trial Create an environment: (1) meet international regulation, ICH (2) require optimized dosage for Taiwanese patient Communicate with local and international pharmaceutical

industry Announce new regulation according to the international

norm and the consensus from communications Create an international platform “APEC – Taipei” Implement Double Twelve Announcement – Bridging

Study

14

Stepwise Implementation 1998 Announce: two years later, switch from LCT to

bridging study Many communications and negotiations with local and

international pharmaceutical industry 2000, Dec.12, (Double Twelve Announcement) – public

announce bridging study regulation 1998 Five announcements of LCT wavier Two years transition periods: both LCT and bridging

studies acceptable from 2000 ~ 2002 Many international conferences held in Taipei and other

Asian countries, regarding BS, through the APEC platform Ask CDE to complete the practical issues related to

implementation of BS 2004, Jan. 1, Bridging evaluation

15

Available Statistical Methods 1. Hierarchical Model

(Liu, Hsueh, and Chen, 2002, Biometrical Journal, 44: 969-981) 2. Takeuchi, M. Controlled Clinical Trials 23: 55-57, 2002 3. Shao, J. and Chow, S. C. Statistics in Medicine, 21: 1727-1742, 2002 4. Population Similarity

(Chow, Shao, Hu, 2002, JBS, 12: 385-400) 5. Consistency Approach (Shih, 2001, Controlled Clinical Trials, 22: 357-366) 6. Bayesian Positive Treatment Approach

(Liu, Hsiao, and Hsueh, 2002, JBS 12: 297-294) 7. Bayesian Noninferiority Approach

(Liu, Hsueh and Hsiao, 2004, JBS accepted) 8. Group Sequential Approach

(Hsiao, Xu and Liu, 2003, JBS, 13: 793-801) 9. Two-Stage Approach (Hsiao, Xu and Liu, 2004, submitted)

16

INFO

Y3 N

Data Package

Vol., page1 Checking List for the evaluation of Bridging Study by the Sponsor

I. The current status of clinical study of the drug in the world □ □

II. NDA expert report or Investigator’s Brochure2 □ □

III. Pharmacokinetics, safety and efficacy data related to Asian population □ □

IV.Comparative analysis of Pharmacokinetics, safety and efficacy data between Asian population and others. □ □

V. Self evaluation (please provide reference materials or literature) □ □Y N U

1. Does the drug show a Non-linear pharmacokinetics at the therapeutic dose?

□ □□ □ □

2. Is the drug with a steep pharmacodynamic curve for both efficacy and safety (a small change in dose results in a large change in effect) in the range of the recommended dosage and dose regimen?

□ □□ □ □

□ □□ □ □3. Is the drug with narrow therapeutic dose range?

Note ： 1. To speed up reviewing process, please clearly indicate the volume and page number as requested. In

addition to the page number, the related paragraph may be highlighted when necessary. 2. Please provide the comparative analysis of different ethnic groups, if it’s available. Please also explain

if there is no comparative analysis of different ethnic groups in NDA expert report. 3. Y=yes; N=no; U=unknown

Checking List for Sponsors (1 of 3)

17

Note ： 1. To speed up reviewing process, please clearly indicate the volume and page number as requested. In

addition to the page number, the related paragraph may be highlighted when necessary.2. Y=yes; N=no; U=unknown

INFO

Y2 N

Data Package

Vol., page1 Checking List for the evaluation of Bridging Study by the Sponsor

V. Self evaluation (please provide reference materials or literature) □ □Y N U

4. Is the drug highly metabolized, especially through a single pathway, thereby increasing the potential for drug-drug interaction ?

□ □□ □ □

5. Is the drug metabolized by enzyme known to show genetic polymorphism?

□ □□ □ □

□ □□ □ □6. Is the drug administered as a prodrug, with the potential for ethnically variable enzymatic conversion ?

□ □□ □ □7. Is the drug with high inter-subject variation in bioavailability ?

□ □□ □ □8. Is the drug with low bioavailability, thus more susceptible to dietary absorption effects?

□ □□ □ □9. Is the drug with high likelihood of use in setting of multiple co-medications ?

□ □□ □ □10. Is the drug with high likelihood for inappropriate use, e.g. analgesics and tranquilizers ?

Checking List For Sponsors (2 of 3)

18

INFO

Y3 N

Data Package

Vol., page1 Checking List for the evaluation of Bridging Study by the Sponsor

V. Self evaluation (please provide reference materials or literature) □ □Y N U

11. Is there any difference in epidemics of applied indication between the major study population and our population (including medical history, mechanism of disease development and the rate of occurrence, the efficacy and safety of other drugs in the same class)?

□ □□ □ □

12. Other important ethnic sensitive factors, such as “Is there any difference in the medical practice?” □ □□ □ □

Note ： 1. To speed up reviewing process, please clearly indicate the volume and page number as requested. In

addition to the page number, the related paragraph may be highlighted when necessary. 2. Y=yes; N=no; U=unknown3. Please according the checking list provide an integrate summary or a brief description of all the

information submitted.

VI. Post-marketing surveillance information □ □

Overall conclusion of self evaluation (Is it clinically insignificant? What is the risk and benefit of the drug applied (such as, “Does the indication applied belong to severe disease”, “Is there a alternative therapy?”, “Are the differences of the data in ethnic factors acceptable ?)

□ □

Summary3 □ □

Checking List for Sponsors (3 of 3)

19

•Bridging Data Package•Summary for the Consideration of Bridging Study

Accept submission

Checking ListTechnical Review

(Designate reviewer)

Review meeting

Sponsor meetingSupplement

Clinical Review Committee

Review report and Recommendation:1. No Bridging study required2. Bridging study is required – Type of Bridging study

Result of Evaluation:1. No Bridging study

required2. Bridging study is required

– Type of Bridging studyNotification

Sponsor BoPA CDE

CDE acceptance

verification

Expert Consultants (Statistical, Clinical, Pharmacokinetics reviewers)

Schedule Sponsor meeting

20

21

71.1

21.1 21.1 21.1

47.455.3

5.3

31.6

2.6

0

20

40

60

80

100R

easo

ns f

or n

ot w

aive

d/to

tal c

ases

(%

)

22

Does bridging strategy of ICH E5 warrant further implementation?

Is Taiwan on the right way?

23

Case I

Drug A is a fixed combination of two anti-platelet agents with indication for secondary prevention of thromboembolic stroke (200mg dipyridamole/25mg aspirin 1bid)

After the standard process of BSE, we decided to request a bridging study due to an ethnic difference in medical practice (much lower dose for one of the components in Taiwan) and higher headache-associated dropout rate in previous Philippine study

24

Case I

Headache drop out rate: Phillipino > Caucasian Local Bridging Study Result : first 4 weeks

Group Placebo Reduced Dose 2wk Full Dose Full Dose 2wk 4wk

Headache 8.7% 6.7% 16.3%drop out rate

Risk Management: Change labeling’s instruction for use

25

Case II

Drug B is a new potent lipid-lowering agent The PK study in Japanese shows that Cmax

of Japanese is 1.9~2.5 times of that for Caucasian while AUC is 2~2.5 times

Although the mean interracial difference is not substantial, Taiwan approved the drug with reduced maximal dosage due to the dose-dependent, drug-related rare SAE of rhabdomyolysis

26

Case II

The decision is further echoed by US FDA After reviewing the results of a Phase IV

PK study in Asian-Americans, FDA urged the physician to reduce the starting dose and prescribe high dose with caution for Asians in Labeling in March, 2005

27

Bayesian Approach

28

Bayesian ApproachFor bridging studies Small sample size No power Information on dose response, efficacy and safety of the

original region can not be concurrently obtained from the local bridging studies but are available in the trials conducted in the original region

Need to borrow “strength” from CCDP of the original region

Information on dose response, efficacy and safety of the original region can and should be incorporated in a statistically sound manner to evaluate bridging evidence by local bridging studies

29

Before Experiment

After Experiment

Bayesian Approach

Past experience about similar situations

involving similar

Prior informationP (

Posterior information

P(prior&data

Observed results( Data )

MakeStatisticalinference

Treatmenteffect

30

Assumption, Notation and Hypotheses We focus on the trials for comparing a test product

and a placebo control Xi and Yj are some efficacy responses for patients i

and j receiving the test product and the placebo control respectively in the new region

Xi’s and Yj’s are normally distributed with known variance σ2

μNT and μNP are the population means of the test and placebo, respectively, and let ΔN = μNT - μNP

H0: ΔN 0 vs. HA: ΔN > 0

31

Parameters

Test Product Effect

Placebo Effect

Original Region OT OP

New Region NT NP

32

Before Bridging Study

Original region data to estimate OT

Original region data to estimate OP

ConcludeOT > OP

33

Bayesian Positive Treatment Approach

Original region information to

form prior

Posterior information

P{NT-NP prior & bridging

Bridging data

New regiontreatment effect

NT — NP

Conclude NT>NP if

P{NT-NP>0 prior & bridging

is large

34

Previous Statistical Approach

Use the estimate of treatment effect from the original region formulated as a normal prior

Compute the posterior treatment effect with the data from the new region

35

Results from Original RegionChange from baseline in sitting DBP at week 12Region Statistics Test PlaceboI n 138 132

Mean -18 -3 SD 11 12

II n 185 179 Mean -17 -2

SD 10 11III n 141 143

Mean -15 -5 SD 13 14

Previous Statistical Approach

36

Results from New Region:

Change from baseline in Sitting DBP at week 12

Region Statistics Test PlaceboNew n 64 65

Mean -4.5 -3.8 SD 11 11

Posterior probability of similarity: Psp 1

Previous Statistical Approach

37

Previous Statistical Approach

Original region: Efficacy of the test drug is superior to the placebo

New Region: Reduction of sitting BP of the test drug is same as that of the placebo

Conclusion: The results of the original region can be extrapolated to the new region despite of inconsistent results between original and new regions

Evaluation of bridging studies is overwhelmingly by the results of original region due to imbalance of information provided by the two regions

38

Use of Prior Distribution

The proposed mixture model of the prior

distribution for ΔN is a weighted average of the noninformative and normal priors as given below

π(ΔN) =γπ1(ΔN) + (1-γ)π2(ΔN) π1(.) ≡c is a non-informative prior π2(.) is a normal prior with mean θ0 and variance σ

02 which summarizes the foreign clinical data abou

t the treatment difference provided in the CCDP 0 γ 1≦ ≦

39

Marginal Density

Based on the clinical responses from the

bridging study in new region, ΔN can be

estimated by

The marginal density is

where

.ˆNNN yx

,)~(2

)ˆ(exp

)~(2

1)1()ˆ(

220

20N

220

N

m

.//~P

2T

22 nn

40

Posterior Distribution

Given the bridging data and prior distribution,

the posterior distribution of ΔN is

.~2

)ˆ(

2

)(exp~2

1)1(

~2

)ˆ(exp~2

1

)ˆ(

1)ˆ|(

2

2NN

20

20N

0

2

2NN

NN

m

41

Bridging EvaluationSimilarity on efficacy in terms of a positivetreatment effect for the new region can beconcluded if the posterior probability ofSimilarity

for some pre-specified 0 < < 0.5.

,1

)ˆ|(

)prior and data bridging|0(PP

0

NNN

NPNTSP

d

42

Example

The CCDP provides the results of three randomized, placebo controlled trials for a new antidepressant (test drug) conducted in the original region

The primary endpoint is the change from baseline of sitting diastolic blood pressure (mmHg) at week 12

A bridging study was conducted in the new region to compare the difference in efficacy between the new and original region

43

Three Scenarios The first scenario presents the situation where no

statistically significant difference in the primary endpoint exists between the test drug and placebo (2-sided p-value = 0.6430

The second situation is that the mean reduction of sitting diastolic blood pressure at week 12 of the test drug is statistically significantly greater than the placebo group (2-sided p-value < 0.0001)

The third scenario is the situation where due to the insufficient sample size of the bridging study, no statistical significance is found between the test drug and placebo although the magnitude of the difference between the test drug and placebo observed in the original region is preserved in the new region (2-sided p-value = 0.0716)

44Treatment Group Region Statistics

Drug Placebo

Original 1 N

Mean

Standard Deviation

138

-18

11

132

-3

12

Original 2 N

Mean

Standard Deviation

185

-17

10

179

-2

11

Original 3 N

Mean

Standard Deviation

141

-15

13

143

-5

14

New 1

(Example 1)

N

Mean

Standard Deviation

64

-4.7

11

65

-3.8

11

New 2

(Example 2)

N

Mean

Standard Deviation

64

-15

11

65

-2

11

New 3

(Example 3)

N

Mean

Standard Deviation

24

-11

13

23

-4

13

45

Psp Example 1 Example 2 Example 3

0.0 1.0000 1.0000 1.0000 0.1 0.6789 0.9999 0.9727 0.2 0.6789 0.9999 0.9700 0.3 0.6789 0.9999 0.9690 0.4 0.6789 0.9999 0.9685 0.5 0.6789 0.9999 0.9682 0.6 0.6789 0.9999 0.9680 0.7 0.6789 0.9999 0.9678 0.8 0.6789 0.9999 0.9677 0.9 0.6789 0.9999 0.9676 1.0 0.6789 0.9999 0.9675

46

Scenario I

If the regulatory agency allows all information of the original region to be used for evaluation of similarity between the new and original region, γ is set to be 0 and hence PSP 1.00

If γ 0.1, then P≧ SP always drops to around

0.6789

47

Scenario II

The values of PSP in Example 2 appear to be

close to 1.00 regardless of the choice of γ

48

Scenario III

• The values of PSP are all greater than 0.9675 for all

values of γ between 0 and 1 • With the strength of the substantial evidence of

efficacy is borrowed from the CCDP of the original region, our procedure can prove the similarity of efficacy between the new and original region when a non-significant efficacy result but with a similar magnitude is observed in the bridging study

49

Final Remarks

The proposed prior is a weighted average of a non-informative prior and a normal prior

The proposed procedure can avoid the situation of concluding similarity between the new and original region when the efficacy result of the test drug observed the bridging study of the new region is same as or even worse than that of the placebo group

Our proposed procedure can reach a conclusion that is more consistent with the results obtained from the bridging study

50

Final Remarks

Selection of weight γ by the regulatory agency in the new region should consider all differences in both intrinsic and extrinsic ethnical factors between the new and original regions and at the same time should also reflect their belief on the evidence of efficacy provided in the CCDP of the original region

51

Final Remarks

We use a normal prior for summarization of the results in CCDP of the original region

We also use other prior distributions

I) double exponential distribution

II) lognormal distribution

Other different distributions used for π2

reach the same conclusion

52

The 4th Multitrack Workshop in Japan

Pursuing Global Joint Development, Drug Discovery

and Fostering Promotion

53

Drug Lag

Number of products waiting for marketing among world’s top 88 selling-products in 2004• Japan: 28• Russia: 27• Singapore: 22• Taiwan: 12• France: 9• Korea: 5• Germany: 2• UK: 1• USA:0

54

55

56

ICH-E5 Q11

• It may be desirable in certain situations to achieve the goal of bridging by conducting a multi-regional trial under a common protocol that includes sufficient numbers of patients from each of multiple regions to reach a conclusion about the effect of the drug in all regions…

57

Key Words in Q11 Answer

• Multiregional Trials serving as a bridging study• Hierarchy of persuasiveness

– The most persuasive results• Statistical significant in overall result AND• Statistical significant in region of interest

– Still persuasive results • Statistical significant in overall result AND• Region of interest could not reach statistical significance

BUT• Consistent trends across regions

58

Questions

• How do we draw inferences concerning the treatment effect in a multi-regional trial?

• How do we assess “consistent trends” across regions?

• What is a rational way to determine the minimum sample size for a region?

59

Fundamental Premises

1. No region should proclaim itself to be the region of interest and demand the treatment to show a statistically significant result at the usual significance level within that region.

2. The study’s primary objective is to demonstrate an overall treatment effect.

3. Satisfying regional requirement is a key secondary objective.

60

Assumption and Notation

We focus on the trials for comparing a test product and a placebo control

Xi and Yj are some efficacy responses for patients i and j receiving the test product and the placebo control respectively in the new region

Xi’s and Yj’s are normally distributed with known variance σ2

μT and μP are the population means of the test product and placebo, respectively, and let Δ = μT - μP

61

Assumption and Notation• Effect size (Δ/σ) is uniform across regions• Hypothesis: H0:Δ 0 vs. H≦ A:Δ ＞ 0 • N is the total sample size for each group planned for detect

ing an expected treatment difference Δ=δ at the desired significance level αand with power 1 － β.

N=2{(z1-α+z1-β)/δ}2,

where z1-α is the (1 － α)th percentile of the standard normal distribution.

62

Assumption and Notation

• pi is the proportion of patients in the ith region

• Zi is the test statistic in the ith region

• For simplicity, we will work with 3 regions

• Z is the test statistic for the overall results

63

Strategies

• Positive consistent trends across all regions

• Positive consistent trends at some significant level for all regions

• Positive consistent trend for a specific region

64

11 2

1

2

pp p

Notations

1 2 11 2p p p

Region 3[Largest]

Region 2[Second smallest]

Region 1 （ Japan? ）

[Smallest]

Sample Size/Group: N

p3

p2

p1

The number N is determined to provide an 80% or 90% power for the primary analysis at the one-sided 2.5% level.

Due to the constraints ofp1 ≤ p2 ≤ p3 and p1+p2+p3=1

D3

D2

D1

Estimated treatment effect(New treatment - Placebo)

65

Positive Consistent Trends Across All RegionsProbability of consistent trends across 3 regions

ψ(x) is the cumulative distribution of the standard

normal distribution at x

)0 ,0 ,0(

113

1

321

ZZp

ZZZP

P

jj

cs

66

Observations

• Pcs is the largest when p1 = p2 = p3, i.e., the 3 regions are equally represented.

• For a given p1,

Pcs is the smallest when p2 = p1;

Pcs is the largest when p2 = p3 = (1-p1)/2.

67

Pcs When p2 = p1

(p1, p2, p3) 80% power 90% power

(0.05, 0.05, 0.9) 53.7 58.6

(0.1, 0.1, 0.8) 65.6 71.7

(0.15, 0.15, 0.7) 73.4 79.9

(0.2, 0.2, 0.6) 78.9 85.3

(0.25, 0.25, 0.5) 82.5 88.8

(0.3, 0.3, 0.4) 84.5 90.7

68

Pcs When p2 = p3

(p1, p2, p3) 80% power 90% power

(0.05, 0.475, 0.475) 69.6 74.6

(0.1, 0.45, 0.45) 76.4 82.2

(0.15, 0.425, 0.425) 80.4 86.5

(0.2, 0.4, 0.4) 82.8 88.9

(0.25, 0.375, 0.375) 84.2 90.3

(0.3, 0.35, 0.35) 84.8 91.0

69

A Reasonable Question

• Assuming that treatment effect is positive and uniform across regions, what is the minimum number of subjects the smallest region should contribute so that the probability of observing consistent trends across the 3 regions is 80% (90%)?

70

Plots of Pcs against p1 with p2=p1

p 1

Pro

babi

lity

of

obse

rvin

g al

l Di>

0

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0.05 0.10 0.15 0.20 0.25 0.30

0.8

0.9

0.151 0.213 0.277

Power:90%

Power:80%

Pcs neverreaches 90%

71

But …

• In practice, inference concerning regional results in a confirmatory trial is relevant only if the overall treatment effect is statistically significant.

• The above calls for looking at Pcs conditional on first concluding a significant overall treatment effect at the one-sided 2.5% level.

72

Conditional Pcs vs Unconditional Pcs

80% power 90% power

(0.05, 0.05, 0.9) 57.5 (53.7) 64.6 (58.6)

(0.1, 0.1, 0.8) 71.1 (65.6) 73.8 (71.7)

(0.15, 0.15, 0.7) 82.5 (73.4) 82.5 (79.9)

(0.2, 0.2, 0.6) 86.1 (78.9) 90.0 (85.3)

(0.25, 0.25, 0.5) 90.9 (82.5) 92.2 (88.8)

(0.3, 0.3, 0.4) 93.2 (84.5) 94.4 (90.7)

Treatment effect = 0.250, =1