Title:Science-based Ethnic Bridging in Drug Development; Review of Recent Precedence and Suggested Steps Forward
Volume: 14
Issue: 3
Author(s): Ewoud-Jan van Hoogdalem*, John P. Jones III, John Constant and Meguru Achira
Affiliation:
- PRA Health Sciences, Scientific Affairs - Clinical Pharmacology, Groningen,Netherlands
Keywords:
Race, ethnicity, product label, clinical drug development, tacrolimus, antihypertensives.
Abstract: Background: Exposure, safety and/or efficacy of drugs are subject to potential differences
between human races or ethnicities, as acknowledged by regulatory guidance and by label
texts of various, but not all approved drugs.
Objective: The objective of the present review was to assess recent regulatory precedence on drug
use and race or ethnicity, with the goal of identifying opportunities for increasing the informative
value of clinical ethnic or racial bridging in drug development.
Methods: Recently, (January 2014-July 2018) FDA approved drug product label texts and approval
packages were reviewed for claims, comments and underlying data on use of the product in specific
ethnic or racial groups.
Results: Among the 266 FDA-approved products, no product with unambiguous race- or ethnicity
specific dosing instructions was retrieved. A small majority (55%) was approved with a claim or
comment on race or ethnicity, and of these, a large majority (87%) was based on population pharmacokinetic
data analysis. Statements were often related to incidence of a genotype for drug metabolizing
enzyme or for other risk factors, or were related to body weight. Absence of clinically
relevant exposure differences were often justified in terms of exposure ratios that notably exceeded
the typical 0.80-1.25 no-effect boundary.
Conclusions: Recent precedence reflected a pragmatic, descriptive approach of racial or ethnic
bridging, apparently meeting current regulatory expectations, whilst not resulting in strict guidance
to prescribers. We recommend further work on defining the objectives of bridging studies, as well
as criteria for their design and data analysis. Regarding the latter, we recommend investigating the
value of prospectively defined tests for similarity with appropriate follow-up analysis in the case
where the test has failed.
