1. Bridging Studies - A Genomic ApproachBy
Jen-pei Liu, Ph.D., Professor 劉仁沛教授
Division of Biometry, Department of Agronomy
National Taiwan University
Division of Biostatistics and Bioinformatics ,
National Health Research Institutes at
The 34 Training Course on Clinical Trials
Foundation of Medical Professionals Alliance in Taiwan
October 14, 2005
The views expressed in this paper are professional opinions of the presenter and may not necessarily represent the position of the National Taiwan University and National Health Research Institutes, Taiwan.
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2. Acknowledgements and Thanks
 Herng-Der Chen, MD, PhD, Center for Drug Evaluation
 Mey Wang, PhD, Center for Drug Evaluation
 Chin-Fu Hsiao, PhD, National Health Research Institutes
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3. Outline I. Statistical Interpretation of ICH E5
II. Implementation of Bridging Studies
III. Examples of Bridging Studies
IV. Current Statistical Approaches
V. A Statistical Genomic Approach
VI. Summary
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4. Statistical Interpretation of ICH E5
ICH Harmonised Tripartite Guideline (Feb. 5, 1998)
Ethnic Factors in the Acceptability of Foreign Clinical Data
A US FDA Guidance (Federal Register, June 10, 1998)
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5. Statistical Interpretation of ICH 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.
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6. Statistical Interpretation of ICH E5
Objectives of ICH E5 (Section 1.1)
To describe the characteristics of foreign clinical data that will facilitate their extrapolation to different population 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 study, 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 and dose region
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7. Statistical Interpretation of ICH E5
ICH E5 Ethnic Factors in the Acceptability of Foreign Data
BRIDGING DATA PACKAGE (Section 3.2)
A bridging data package consists of
1) selected information from the Complete Data Clinical Package
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.
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8. Statistical Interpretation of ICH E5
Complete Clinical Data Package (CCDP)
A clinical data package intended for registration containing clinical data that fulfills regulatory requirements of the new region and pharmacokinetic data relevant to the population in the new region
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9. Statistical Interpretation of ICH E5
Bridging Study
A bridging study is defined as a 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 population in the new region
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10. Extrapolation and Similarity
ICH E5 Ethnic Factors in the Acceptability of Foreign Data
If the bridging study shows that dose response, safety and efficacy in the new region are similar, then the study is readily interpreted as capable of "bridging" the foreign data
If a bridging study, properly executed, indicates that a different dose in the new region results in a safety and efficacy profile that is not substantially different from that derived in the original region, it will often be possible to extrapolate the foreign data to the new region, with appropriate dose adjustment, if this can be adequately justified (e.g., by pharmacokinetic and/or pharmacodynamic data).
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11. 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
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12. Taiwan’s Strategy to Implement Bridging Study
An approved report of a local clinical trial study is required for the new drug application in Taiwan—July : Double 7 Announcement
Disadvantages:
A minimal sample size of 40 as required could be difficult to provide conclusive and substantial evidence of
efficacy and safety
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
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13. Taiwan’s Strategy to Implement Bridging Study
Smoothly convert compulsory Local Clinical Trials (LCT) to meaningful bridging studies
Gradually, stepwise announce waived local clinical trials
Create an environment: (1) meet international regulations, ICH
(2) require optimized dosage for
Taiwanese patients
Communicate with local and international pharmaceutical industry
Announce new regulations according to the international norm and the consensus from communications
Create an international platform “APEC – Taipei”
Implement Double Twelve Announcement – Bridging Study
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14. Stepwise Implementation
Two years after the 1998 announcement, switch from LCT to bridging study
Many communications and negotiations with local and international pharmaceutical industry
Dec. 12, 2000: (Double Twelve Announcement) – public announcement of the bridging study regulations
1998: Five announcements of LCT wavier
A two-year transition period: both LCT and bridging studies concurrently acceptable from 2000 ~ 2002
Many international conferences held in Taipei and other Asian countries, regarding BS, through the APEC platform
Consult with CDE to complete the practical issues related to implementation of BS
Jan. 1, 2004: Bridging evaluation
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15. Products Requiring No Verification of Ethnic Insensitivity
Drugs for treatment of AIDS
Drugs for organ transplantation
Topical agents
Nutrition supplements
Cathartics prior to surgery
Radio-labelled diagnostic pharmaceuticals
The drug is the only choice of treatment for a given severe disease
Drugs for life-threatening disease have demonstrated a breakthrough efficacy
Lacking adequate trial subjects for any drug used for rare disease
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16. Products Requiring Verification of Ethnic Insensitivity
Anticancer drugs
Drugs with breakthrough efficacy
Drugs of single use
Drugs with different salt of the same composition and the same administered route have been approved internal
Drugs for chronic psychological or immunological diseases and conducting clinical trails internal difficultly
Each compounds of new combination drug have been proved internal, and the efficacy is the same as the single compound
Drugs with the mechanism, administered route, efficacy and adverse effect, similar to the approved drugs
New combination composed of single compound of approved combination or compounds of approved combination has the same efficacy as approved combination
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17. Evaluation Process BoPA CDE Sponsor Bridging Data Package
Summary for the Consideration of Bridging Study
Accept submission
Checking List
CDE acceptance
verification
Technical Review
(Designate reviewer)
Expert Consultants (Statistical, Clinical, Pharmacokinetics reviewers)
Review meeting
Evaluation Process
Schedule Sponsor meeting
Supplement
Sponsor meeting
Clinical Review Committee
Result of Evaluation:
1. No Bridging study required
2. Bridging study is required – Type of Bridging study
Review report and Recommendation:
1. No Bridging study required
2. Bridging study is required – Type of Bridging study
Notification
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19. 2018/12/8

20. Examples
Example I
Drug A is a fixed combination of two anti-platelet agents with indication for secondary prevention of thromboembolic stroke
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
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21. Examples
Case I
Fixed combination 200mg dipyridamole/25mg aspirin 1bid for prevention of recurrent stroke
Headache drop out rate: Phillipino > Caucasian
Local Bridging Study Result : first 4 weeks
Reduced Dose 2wk Full Dose
Placebo Full Dose 2wk wk
Headache % % %
Risk Management: Change labeling’s instruction for use
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22. Examples 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 of that for Caucasian
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
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23. Examples Case II The decision was further echoed by US FDA
After reviewing the results of a Phase IV PK study in Asian-Americans, FDA urged the physicians to reduce the starting dose and prescribe high dose with caution for Asians in Labeling in March, 2005
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24. Current Statistical Approaches
“Similarity”
Positive Rx effect
Equivalence
Non-inferiority
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25. Current Statistical Approaches
Extrapolation and Similarity
Positive treatment effect (better than control)
The efficacy or safety of the test drug is better than control in the new region
Ho: NT - NC  0 vs. Ha: NT - NC > 0
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26. Current Statistical Approaches Positive Rx EffectD O D
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27. Current Statistical Approaches
Similarity (No substantial difference)
Two-sided equivalence
The relative efficacy or safety (test - control) of the new region is within some clinically acceptance limit of that of the original region
Let  = (NT - NC) - (OT - OC)
Ho:   - or    vs. Ha: - <  < 
where  is some clinically acceptable limit (equivalence limit).
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28. Current Statistical Approaches EquivalenceD O D
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29. Current Statistical Approaches
Similarity (No substantial difference)
One-sided non-inferiority
The relative efficacy or safety (test - control) of the new region is not inferior to the original region by some clinically acceptance limit.
Ho:   - vs. Ha:  > -.
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30. Current Statistical Approaches Non-inferiorityD O D
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31. Current Statistical Approaches
Between-study Analysis: Equivalence or non-inferiority
Hierarchical Model (Liu, Hsueh, and Chen 2002, Biometrical J.)
Step 1: From the complete clinical data package, under the hierarchical model, use the clinical data from the original region to obtain the estimate of relative efficacy and its estimated standard error.
Step 2: From the data of the bridging study, obtain the estimate of relative efficacy and its estimated standard error in the new region.
Step 3: Based on the estimated relative efficacy and its standard error from both the new and original regions and equivalence limit , perform the usual two one-sided tests procedure or one-sided
non-inferiority test procedure (or confidence interval).
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32. Current Statistical Approaches
Empirical Bayesian Approach
Bridging studies
 Small sample size
 Need to borrow “strength” from CCDP of 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 the bridging studies in the new region.
 Positive treatment effect: (Liu, Hsiao, and Hsueh, 2002, JBS)
 Noninferiority approach: (Liu, Hsueh, and Hsiao 2004, JBS)
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33. Current Statistical Approaches
Between-study Analysis:
Bayesian Approach (Liu, Hsiao, and Hsueh, 2002)
 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
Compute the posterior probability of similarity, Psp as the
posterior probability of a positive treatment effect
 Conclude the results of the foreign region can be extrapolated
to the new region if Psp is sufficiently large.
 Sample size might be determined based on the
difference between the posterior and prior treatment
effect
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34. Current Statistical Approaches
For a positive treatment effect
The model (Liu, Hsiao, and Hsueh, 2002)
Yi = P(1-Xi) + {Nzi + O(1-Zi)}Xi + i, I ~ N(0, 2), where
P: control effect
N: treatment effect of the new region
O: treatment effect of the original region
X = 1(0) treatment (control) group
Z = 1(0) new (original region)
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35. Current Statistical Approaches
For a positive treatment effect
Empirical Bayesian Approach (Liu, Hsiao, and Hsueh, 2002)
 Given P, N, the estimates of P, N, say p and aN follows a
bivariate normal distribution with mean vector (P, N)’ and the
diagonal covariance matrix diag(VP, VN).
 In addition, the prior distribution of (P, N, O)’ follows a trivariate
normal distribution with mean vector (p, N, O) and
diagonal covariance matrix diag(2p, 2N, 2O).
Conclude a positive treatment effect if posterior probability of
similarity
P(N - P > 0data and prior) > 1 - , for some  > 0.5. (Simon, 1999)
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36. Current Statistical Approaches
For a positive treatment effect
Empirical Bayesian Approach (Liu, Hsiao, Hsueh, 2002)
Under assumption that N = O,
for P(N - P > 0data and prior) > 1 - ,
the following equation must be satisfied
(O - p)/2O+2p = -1(1-q),
where -1(1-q) represents the evidence for positive treatment effect in the original region.
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37. Current Statistical Approaches
Results from Original Region
Change from baseline in sitting DBP at week 12
Region Statistics Test Placebo
I n
Mean SD
II n
Mean SD
III n
Mean SD
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38. Current Statistical Approaches
Results from New Region:
Change from baseline in Sitting DBP at week 12
Region Statistics Test Placebo
New n
Mean SD
Posterior probability of similarity: Psp  1
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39. Current Statistical Approaches
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. .
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40. Current Statistical Approaches
A Mixture Prior Bayesian Approach (Hsiao, Hsu and Liu, 2005)
Define N = NT - NC
A mixture prior model:
(N) =1(N) +(1 - )2(N)
1(N) is a noninformative prior and is set to be 1.
2(N) is a normal prior that summarizes the results of original region
is a weighing factor; 0   1
= 0: the same prior used in Liu, Hsueh and Hsiao (2002)
= 1: no results of original region is used
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41. Current Statistical Approaches
Posterior Probability of Similarity
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42. Current Statistical Approaches
Marginal Distribution
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43. Current Statistical Approaches
Posterior Distribution
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44. Current Statistical Approaches
Find the smallest nN that
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45. Current Statistical Approaches
Group Sequential Method (Hsiao, Xu, Liu, 2003)
A Two-stage Design (Hsiao, Xu, Liu, 2005)
Reason:
Under the hierarchical model or Bayesian approach, evaluation of similarity or non-inferiority based on the difference of relative efficacy might still require large sample size for the bridging study in the new region.
These are between-study analysis without internal
validity and may provide biased inference
Criterion for similarity
Maintenance of the similar trend in the new region
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46. Current Statistical Approaches
Step 1: When designing the adequate and well-controlled studies for submission to the original region, include the patients in the new region as part of recruitment for the whole study (The bridging study is a sub-study).
Step 2: The study should have a structure of group sequential design. Use the region as group sequence to enroll the patients from the original region first and then to enroll patients from the new region subsequently.
Step 3: Pre-specify the boundaries in the protocol, say alpha spending function. Because the primary objective of the trial is for submission to the original region, most of type I error rate should be spent for the interim analysis based on the results from the original region.
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47. Current Statistical Approaches
Step 4: When the recruitment of patients in the original region is
completed, perform the interim analysis up to results of the original region.
Step 5: Enroll the patients in the new region. After the recruitment of the patients is completed, perform the final analysis with additional data from the new region and adjustment of the interim analysis. If similar results (i.e., similar significance level to meet requirement of crossing boundary) are obtained for the final analysis, then the results of the new region can be declared similarity to the original region.
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48. A Statistical Genomic Approach
Targeted Clinical Trials
HER2 (the human epidermal growth factor receptor 2) gene in metastatic breast cancer - Herceptin - requirement of screening the patients with over-expressed HER2 level (Slamon, 2001).
Estrogen receptor polymorphism - Estrogen Replacement Atherosclerosis trial (ERA, Herrington, et al, 2002): a total of 9 SNPs were identified and interaction between treatment of HRT and some of SNPs in elevation of lipid levels is suggested
Sample size determination: Fijal, et al. (2000) and Maitournam and Simon (2005).
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49. A Statistical Genomic Approach
Targeted Clinical Trials and EGFR
Iressa (gefitnib) and Tarceva (Erlotinib) are targted at the EGFR pathway.
Efficacy is correlated to
race
number of gene copies
protein expression
EGFR mutation
Gappuzzo et al. (JNCI, 2005), Tsao, et al (NEJM, 2005)
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50. A Statistical Genomic Approach
—— IRESSA®
Placebo
1.0
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.0
Asian (n = 342) HR = (0.48, 0.91), P = .011
RR = 12.0%
Non-Asian (n = 1350) HR = (0.81, 1.08), P = .364
RR = 6.5%
Patients surviving (%)
Time, mo
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51. A Statistical Genomic Approach
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From: Tsao, et al (2005, NEJM)

52. A Statistical Genomic Approach
From: Tsao, et al (2005, NEJM)
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53. A Statistical Genomic Approach
From: Tsao, et al (2005, NEJM)
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54. A Statistical Genomic Approach
From: Tsao, et al (2005, NEJM)
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55. A Statistical Genomic Approach
Current statistical methods for bridging studies do not really take ethnic factors into considerations
After Human Genome Project, the availability of genomic data can provide the necessary quantitative information for intrinsic ethnic factor
Genomic information should be incorporated into evaluation of bridging studies
Bridging studies may be considered as one type of targeted clinical trials with genomic data as the bio-targets for intrinsic ethnic factors
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56. A Statistical Genomic Approach
Stratified Approach
Original Region
Genetic
Polymorphism Proportion Test Control
PO1 1T 1C
PO2 2T 2C
K POK KT KC
POiiT POiiC
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57. A Statistical Genomic Approach
Stratified Approach
New Region
Genetic
Polymorphism Proportion Test Control
PN1 1T 1C
PN2 2T 2C
K PNK KT KC
PNiiT PNiiC
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58. A Statistical Genomic Approach
Poi: the proportion of type i for some genetic polymorphism in the original region
PNi: the proportion of type i for some genetic polymorphism in the new region
iT: the mean response of a patient with type i polymorphism in treatment group
2C : the mean response of a patient with type i polymorphism in control group
OT=POiiT: the mean response of the treatment group in the original region (mean of a mixture distribution)
OC=POiiC: the mean response of the control group in the original region
NT=PNiiT: the mean response of the treatment group in the new region
NC=PNiiC: the mean response of the control group in the new region
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59. A Statistical Genomic Approach
If POi  PNi, OT - OC  NT - NC  Genetic polymorphism are similar between the two regions
Data on efficacy and safety can be extrapolated from the original region to the new region  Bridging studies may not be needed
If POi  PNi, OT - OC  NT - NC  Genetic polymorphism are not similar between the two regions
Extrapolation of efficacy and safety from the original region to the new region is in doubt Bridging studies may be required
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60. A Statistical Genomic Approach
The hypothesis for the bridging study is the proof of a positive treatment effect in the new region
Ho: NT - NC  0 vs. Ha: NT - NC > 0
Standard design, statistical estimation and testing procedures can be applied
Selection of different doses in the bridging study if the information on relation between the response and polymorphism is provided in CCDP
Sample size will be reduced if it is expected that
NT - NC > OT - OC (cf iressa)
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61. A Statistical Genomic Approach
Requirement of the stratified approach
(1) Diagnostic devices for identification of polymorphism
(2) proportions of types of polymorphisms in both regions
(3) the response in each type of polymorphisms, and
(4) the relationship between the response polymorphism
May be expensive for identification of polymorphism
Complication in recruitment and randomization of subjects because prevalence rates of different types of polymorphisms
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62. A Statistical Genomic Approach
Analysis of Covariance (ANCOVA) Approach
The hypothesis for the bridging study is the proof of a positive treatment effect in the new region
Ho: NT - NC  0 vs. Ha: NT - NC > 0
The quantitative genomic information is used as covariates in the model
Treatment effect is adjusted for the genomic information
Sample size may be reduced if a significant relationship between the response and genomic covariates
Need to check the treatment-by-genomic covariate interaction
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63. Summary Statistical hypothesis
Bridging studies and extrapolation
Statistical hypothesis
 Taiwan experience with bridging studies
 Overview of current statistical methods
 Proposal on statistical genomic
approaches to bridging studies
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