BRIDGING STUDIES IN CLINICAL DEVELOPMENT

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BRIDGING STUDIES IN CLINICAL DEVELOPMENTJen-pei Liu a & Shein-Chung Chow ba Department of Statistics , National Cheng-Kung University , Tainan, Taiwanb StatPlus, Inc. , Heston Hall, Suite 206, 1790 Yardley-Langhorne Road, Yardley, PA, 19067,U.S.A.Published online: 05 Oct 2011.

To cite this article: Jen-pei Liu & Shein-Chung Chow (2002) BRIDGING STUDIES IN CLINICAL DEVELOPMENT, Journal ofBiopharmaceutical Statistics, 12:3, 359-367, DOI: 10.1081/BIP-120014564

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BRIDGING STUDIES IN CLINICALDEVELOPMENT

Jen-pei Liu1,2,* and Shein-Chung Chow3

1Department of Statistics, National Cheng-Kung University,

Tainan, Taiwan2Division of Biostatistics and Bioinformatics, National Health Research

Institutes, Taipei, Taiwan3StatPlus, Inc., Heston Hall, Suite 206, 1790 Yardley-Langhorne Road,

Yardley, PA 19067

ABSTRACT

Global development of pharmaceutical products has become the key to the

success of any pharmaceutical sponsors. It is therefore crucial to address the

efficacy and safety variations of a new test pharmaceutical product among

different geographic regions due to ethnic factors. Recently, geotherapeutics

has attracted much attention from sponsors as well as regulatory authorities

from different geographic regions. To address this issue, the International

Conference on Harmonization (ICH) has published a guideline entitled

“Ethnic Factors in the Acceptability of Foreign Clinical Data,” which is

known as ICH E5 guideline. The ICH E5 guideline provides a general

framework for evaluation of the impact of ethnic factors on the efficacy,

safety, dosage, and dose regimen. We provide an overview of ICH E5

guideline including ethnic sensitivity, necessity of bridging studies, types of

bridging studies, and assessment of similarity between regions based on

bridging evidence. In addition, challenges on the establishment of regulatory

requirements, the assessment of bridging evidence, and design and analysis of

bridging studies are addressed.

359

DOI: 10.1081/BIP-120014564 1054-3406 (Print); 1520-5711 (Online)Copyright q 2002 by Marcel Dekker, Inc. www.dekker.com

*Corresponding author. E-mail: [email protected]

JOURNAL OF BIOPHARMACEUTICAL STATISTICS

Vol. 12, No. 3, pp. 359–367, 2002

©2002 Marcel Dekker, Inc. All rights reserved. This material may not be used or reproduced in any form without the express written permission of Marcel Dekker, Inc.

MARCEL DEKKER, INC. • 270 MADISON AVENUE • NEW YORK, NY 10016

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Key Words: Ethnic factors; Bridging studies; Extrapolation; Similarity

INTRODUCTION

For marketing approval of a medicine, sponsors are required to provide

substantial evidence of effectiveness and safety from adequate and well-

controlled clinical trials. The U.S. Food and Drug Administration (FDA)

recommends that at least two clinical studies (the so-called pivotal trials) in the

same targeted patient population be performed to confirm the reproducibility of

the evidence on efficacy, safety, and dose response of the study medicine.

However, after a study medicine is approved by the regulatory agency in the

original region (e.g., the United States of America), sponsors might seek

registration of the approved medicine in a new region (e.g., European Community

or Asian Pacific countries). The possible differences in ethnicity, culture, and

clinical practice between the regions and their impacts on the safety, efficacy,

dose, and dosing regimen have limited the willingness of the regulatory authority

in the new region to accept the clinical data generated in the original region.

Consequently, the regulatory authority in the new region often requests the

sponsors to repeat similar studies for obtaining all or much of the clinical data in

the new region. This extensive duplication of clinical evaluation in the new region

not only demands valuable development resources but also delays the availability

of new medicine to needy patients in the new region. To resolve this dilemma, the

International Conference on Harmonization (ICH) has recently published a

tripartite guideline entitled “Ethnic Factors in the Acceptability of Foreign

Clinical Data,” which is usually referred to as the ICH E5 guideline, to address the

above issues.[1]

The objective of the ICH E5 guideline is to provide a framework for

evaluation of the impact of ethnic factors on the efficacy and safety of a study

medicine at a particular dosage or dose regimen. In addition, it describes

regulatory strategies of minimizing duplication for clinical data and requirement

of bridging evidence for extrapolation of foreign clinical data to a new region. The

purpose of this article is to provide an overview of the ICH E5 guideline including

ethnic sensitivity, necessity of bridging studies, types of bridging studies, and the

assessment of similarity between regions based on bridging evidence.

In the next section, ethnic sensitivity, necessity of bridging studies, types of

bridging studies are discussed. The third section provides an overview of the

definition of similarity and statistical methods for assessment of similarity

between regions based on bridging evidence. A brief concluding remark regarding

challenges on the establishment of regulatory requirements, the assessment of

bridging evidence, and design and analysis of bridging studies is given in the last

section.

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ETHNIC SENSITIVITY, NECESSITY OF BRIDGING STUDIES,AND TYPES OF BRIDGING STUDIES

Ethnic Sensitivity

The ICH E5 guideline lists critical properties of a compound for assessment

of sensitivity to ethnic factors. These critical properties include linear phar-

macokinetics (PK), flat pharmacodynamic (PD), therapeutic range, degree of

metabolism, extent of bioavailability, potential for protein binding, potential for

interactions, genetic polymorphism, inter-subject variability, systemic mode of

action, and potential for inappropriate use. However, the ICH E5 guideline also

points out that no one property of the medicine is predictive of the compound’s

relative sensitivity to ethnic factors. Because of the complexity due to possible

interaction among drug’s pharmacological class, indication, and demography of

patient population, the ICH E5 does not provide a precise and definitive criterion

for evaluation of ethnic sensitivity. As a result, no probability statements can be

made for the errors resulting from the decision-making on sensitivity to ethnic

factors. Therefore, both regulatory authority in the new region and the sponsor do

not have a criteria and a method for an objective and impartial evaluation of ethnic

sensitivity and necessity of a bridging study.

Necessity of Bridging Studies

Since no well-defined and scientifically justifiable criteria for assessment of

ethnic sensitivity are indicated in the ICH E5 guideline, any proposed approach for

the assessment of the necessity of bridging studies could be subjective and

controversial and may not be accepted by the regulatory authority and sponsors in

the new region.

However, several approaches have been proposed in the literature based on

some statistical criteria. For example, Shao and Chow[2] proposed the following

reproducibility probability as a statistical guide for quantifying the likelihood that

under the same experimental conditions, a second trial conducted in the new

region can reproduce the same results of the first trial in the original region:

PðTðxÞÞ ¼ 1 2 tn22ðtn22jTðxÞÞ þ tn22ð2tn22jTðxÞÞ;

where x represents the observed data from the clinical trial conducted in the

original region, T(x ) the value of the unpaired t-statistic based on x, n the total

number of subjects, tn22 the 97.5% percentile of a central t-distribution with n 2 2

degrees of freedom, and tn22( j( ) denotes a noncentral t-distribution with n 2 2

degrees of freedom and noncentrality parameter u. The information of repro-

ducibility probability provides a guide regarding statistical inference on the

chance that clinical results observed in the original region are reproducible at the

new region.

BRIDGING STUDIES IN CLINICAL DEVELOPMENT 361



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To address the possible impact of ethnic factors, Chow et al.[3] suggested

performing a sensitivity analysis on the reproducibility probability with respect to

a sensitivity index D, which is defined as

D ¼ ð1 þ 1=mdÞ=C;

where md is the mean difference between the treatment group observed in the

original region, 1 the change of md in the new region and C represents the change

in variability in the new region. Chow et al.[3] refer to the reproducibility proba-

bility with respect to the sensitivity index, i.e., p(DT(x )) as the generalizability

probability. The concept of generalizability probability may be useful in providing

regulatory authorities with an opportunity to choose a statistical criterion for

determining whether a clinical bridging study is necessary.

On the other hand, as indicated in the U.S. Drug Master File, thousands of

medicines have been approved for various indications for different patient

populations by various regulatory authorities in different geographic regions.

Sufficient pre-approval and post-marketing experience on the critical properties

regarding ethnic sensitivities and the impact of intrinsic and extrinsic factors on

efficacy, safety, dosage, and dose regimen have been accumulated for these

medicines. Based on these data, an instrument consisting of three domains can be

developed to determine the degree of the impact of difference in ethnic factors on

the efficacy, safety, dose, and dose regimen of these medicines and consequently

the necessity of bridging studies. The first domain may include the critical

properties of the compound mentioned earlier. The second domain may consist of

intrinsic factors as discussed in Appendix A of the ICH E5 guideline. The third

domain may comprise the extrinsic ethnic factors as described in Appendix A of

the ICH E5 guideline. Within each domain, a scoring scheme for each property or

factors may be designed to characterize the degree of the impact on efficacy,

safety, dose, and dose regimen. For example, a possible scoring scheme could be a

5-point system such as 1 (no), 2 (mild), 3 (moderate), 4 (strong), and 5 (complete).

An algorithm can then be developed to provide a summary index for an overall

assessment of the impact on the efficacy, safety, dosage, and dose regimen of the

study medicine. In practice, the database of these compounds can be divided into

two data sets, namely, a training set and a validation set. Based on the summary

indices computed from the medicine in the training set, a threshold can be

determined to classify these medicines into two groups. One group consists of

medicines that are insensitive to ethnic factors and hence do not require bridging

studies. The other group contains medicines that are ethnic sensitive and hence

require bridging studies. The probability of classification error can then be

evaluated based on the validation set. Within the group of medicines with the

necessity for bridging studies, further cutoff points can be estimated for different

types of bridging studies. When a new medicine is applied for registration in the

new region, regulatory authority in the new region and the sponsor can calculate

the summary index of the study medicine to determine whether a bridging study is

necessary and what type of the bridging study is warranted. The above approach

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seems logical and acceptable to the pharmaceutical industry and regulatory

agencies. However, it requires a joint effort and close collaboration among

researchers/scientists from multiple disciplines in pharmaceutical research and

development.

Types of Bridging Studies

In general, the types of bridging studies required depend upon the ethnic

sensitivity of the study medicine, clinical experience of the drug class, extrinsic

ethnic factors, and ethnic differences between the new and original regions. As

stated in the ICH E5 guideline, a bridging study could be a PK/PD study or a

controlled clinical trial (CCT). Table 1 provides a summary of types of bridging

studies with respect to the factors of region, medical practice, drug class, and

clinical experience.

As it can be seen from Table 1, there are at least two fundamental issues in

the ICH E5 guideline: (i) sensitivity of study medicines to ethnic factors, necessity

of a bridging study, and the nature and type of bridging studies and (ii) assessment

of similarity based on bridging evidence.

ASSESSMENT OF SIMILARITY BASED ON BRIDGING EVIDENCE

According to the ICH E5 guideline, a bridging data package consists of (i)

selected information from the so-called complete clinical data package (CCDP)

that is relevant to the population of the new region and (ii) if needed, a bridging

study to extrapolate the foreign efficacy and/or safety data to the new region. In

other words, bridging evidence is actually provided either in the CCDP generated

during clinical drug development program for submission to the original region or

in a bridging study conducted in the new region after the pharmaceutical product is

approved in the original region. When the bridging evidence provided in the

CCDP could not allow extrapolation of foreign clinical data to a new region, then a

bridging study should be conducted in the new region to generate a limited amount

Table 1. Types of Bridging Studiesa

Medicine Region

Medical

Practice

Drug

Class

Clinical

Experience

Bridging

Studies

Insensitive — Similar — — No

Sensitive Similar — Sufficient No

Sensitive Dissimilar Similar Familiar — PD

Choice of dose — Different Unfamiliar Insufficient CCT

aPD, pharmacodynamics; CCT, controlled clinical trials.




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of clinical data to bridge the clinical data between the two regions. The ICH E5

guideline clearly states that assessment of the ability of extrapolation of the

foreign data relies on the similarity of dose response, efficacy, and safety between

the new and original regions, either with or without dose adjustment. However, the

ICH E5 guideline does not provide a precise definition or criteria for evaluation of

similarity. For assessment of similarity, a number of different statistical proce-

dures have been proposed based on different definitions or concepts of similarity.

For example, batch similarity in stability analysis for shelf-life estimation, simila-

rity in drug release for comparison of dissolution profiles between drug products,

similarity in drug absorption for assessment of bioequivalence between drug

products, and the concept of consistency between clinical results. Among these

definitions and concepts of similarity, bioequivalence in drug absorption and

consistency between clinical results are most relevant.

Population Similarity

Based on of the concept of similarity in drug absorption for assessment of

bioequivalence between drug products, Chow et al.[3] proposed to adopt the

concept of population bioequivalence for assessment of similarity of clinical

results between the original region and the new region. The idea is to establish

similarity according to the following aggregated equivalence (similarity) criteria,

which is similar to the one proposed in the recent FDA guidance for establishment

of population and individual bioequivalence:[4]

u ¼ðm0 2 m1Þ

2 þ s 2T1 2 s 2

T0

s 2T0

;

where s 2Tk ¼ s 2

Bk þ s 2Wk is the total variance in region k and s 2

Bk and s 2Wk are the

between-center variance and the within-center variance in region k, respectively.

We claim that clinical results in the new region are similar to those observed in the

original region if the 95% upper confidence bound of the following linearized

criterion is less than 0:

6 ¼ ðm0 2 m1Þ2 þ s 2

T1 2 ð1 þ uUÞs2T0;

where uU is the similarity margin set by the regulatory authority in the new region.

Consistency Among Studies

For the concept of consistency between clinical studies, Shih[5] suggested the

use of a predictive probability function for measuring the consistency between

clinical results from different studies. Shih’s approach is briefly outlined below.

Suppose that there are a total of H reference studies and each compares the same

two treatment groups. Let W denote the vector of standardized between-group

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differences of these H reference studies, W ¼ ðw1; . . . ;w11Þ and v is the

standardized between-group difference for the bridging study. The result of v from

the bridging study is consistent with the previous results W if and only if

pðvjWÞ $ min{pðwhjWÞ h ¼ 1; . . . ;H};

where p(vjW) is the predictive probability function that provides a measure of

plausibility of v given previous result W.

Hierarchical Model

Under a hierarchical model, on the other hand, Liu et al.[6] proposed the use

of the concept of equivalence or noninferiority for evaluation of similarity

between the new and original regions. Their approach is summarized below.

Step 1: From the CCDP, under a 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 new and original regions and equivalence limit, perform the

usual two one-sided tests procedure or one-sided noninferiority

procedure (or confidence interval).

However, one can argue that the results of clinical data in the new region are

similar to those in the original region if the new region also demonstrates a

positive treatment effect.

Bayesian Approach

Liu et al.[7] suggested an empirical Bayesian approach to provide the evi-

dence of a positive treatment effect. The results on dose response, efficacy, or

safety of the original region can be incorporated prior to evaluating a positive

treatment effect by the bridging data in the new region. In other words, for a pre-

specified significance level a, 0 , a , 1; one can conclude similarity based on

the concept of a positive treatment effect if the posterior probability is

P{a positive treatment effectjdata and prior} . 1 2 a:

Despite the above different definitions for similarity, a direct interpretation

of the ICH E5 guideline on similarity requires performing a between-region

(study) analysis to evaluate the treatment-by-region interaction. It is then very

clear that the sample size required for the test based on the treatment-by-region

interaction will be much larger than that for detection of the treatment effect




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alone.[6] This statement is true for all types of studies and for all types of

endpoints. On the other hand, one only wants to verify whether the evidence of

efficacy or safety or PK/PD properties observed in the original region can be

reproduced in the new region. In this context, for example, a statistical significance

based on a particular endpoint can also be obtained from the bridging study

conducted in new region if it had been observed in the original region. However,

an equal or even larger sample size is required to reproduce a similar statistical

significance for detection of treatment effect in the new region (see, e.g.,

Refs. [2,3,8,9]). Therefore, these arguments indicate a fundamental conflict

between the evaluation of similarity and the objective of minimizing duplication

of clinical data in the ICH E5 guideline.

Consequently, Bayesian methods have been suggested to synthesize the data

from both the bridging study and the original region to resolve this conflict.[5 – 7]

However, some difficulties also arise using the Bayesian method. First, a medicine

was approved in the original region due to its substantial evidence of efficacy and

safety based on a sufficiently large sample size. The result of the bridging studies

using empirical Bayesian approach will be overwhelmingly dominated by the

results of the original region due to an imbalance of sample sizes between the

regions. In other words, it is very difficult, if not impossible, to reverse the results

observed in the original region and even the result of the bridging study is comple-

tely opposite. In addition, the Bayesian method for evaluation of probability for

error of decision-making on similarity is still needed to work out. This error

probability is extremely crucial for the regulatory authority in the new region to

approve a medicine in their jurisdiction.

CONCLUDING REMARK

The ICH E5 guideline provides a rationale for assessment of ethnic factors in

the acceptability of foreign data for regulatory strategies of minimizing dupli-

cation of clinical data and it also describes the requirement of bridging evidence

for extrapolation of foreign clinical data to a new region. It is, however, too prema-

ture to develop statistical methods for regulatory implementation unless well-

known and scientifically justifiable criteria for (i) the evaluation of sensitivity of

medicines to ethnic factors, (ii) the assessment of necessity of a bridging study,

(iii) the determination of the nature and type of bridging studies, and (iv) the

assessment of similarity based on bridging evidence are addressed in the future

revision of the ICH E5 guideline.

ACKNOWLEDGMENTS

The first author wishes to thank the support and encouragement of the National

Health Research Institutes, Taiwan during the preparation of this manuscript. The views

expressed in this article are personal opinions of the authors and may not necessarily

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represent the position of the National Cheng-Kung University and National Health

Research Institutes, Taiwan and StatPlus, Inc., Yardley, Pennsylvania.

REFERENCES

1. ICH. International Conference on Harmonization Tripartite Guidance E5. Ethnic

Factors in the Acceptability of Foreign Data, The U.S. Federal Register, 1998;

Vol. 83, 31790–31796.

2. Shao, J.; Chow, S.C. Reproducibility Probability in Clinical Trial. Stat. Med. 2002,

21, 1727–1742.

3. Chow, S.C.; Shao, J.; Hu, O.Y.P. Assessing Sensitivity and Similarity in Bridging

Studies. J. Biopharm. Stat. 2002, 12 (3), 385–400.

4. FDA. Guidance for Industry on Statistical Approaches to Establishing Bioequiva-

lence; Center for Drug Evaluation and Research, Food and Drug Administration:

Rockville, MD, 2001.

5. Shih, W.J. Clinical Trials for Drug Registrations in Asian–Pacific Countries: Proposal

for a New Paradigm from a Statistical Perspective. Control. Clin. Trials 2001, 22,

357–366.

6. Liu, J.P.; Hsueh, H.-M.; Chen, J.J. Sample Size Requirement for Evaluation of

Bridging Evidence. Biometrical J. 2002, accepted.

7. Liu, J.P.; Hsueh, H.-M.; Hsiao, C.F. Bayesian Approach to Evaluation of the Bridging

Studies. J. Biopharm. Stat. 2002, 12 (3), 401–408.

8. Hung, H.M.J.; O’Neill, R.T.; Bauer, P.; Kohne, K. The Behavior of the P-Value When

Alternative Hypothesis Is True. Biometrics 1997, 53, 11–22.

9. Chow, S.C.; Shao, J. Statistics in Drug Research—Methodologies and Recent

Development; Marcel Dekker, Inc.: New York, 2002.




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BRIDGING STUDIES IN CLINICAL DEVELOPMENT