Opportunities and Challenges Related to the Implementation of Model‐Based Bioequivalence Criteria

Abstract

The science of bioequivalence and biosimilarity has greatly evolved over the past 3 decades. Current methods for assessing bioequivalence mostly rely on noncompartmental pharmacokinetic (PK) analyses, which have proven to be reliable and robust for most products. However, the development of more complex products is forcing scientists and regulators to consider alternative approaches, including those derived from model-based population PK analyses. This article will examine the strengths and weaknesses of standard noncompartmental methods and compare them to model-based approaches, including a comparison of metrics associated with each method. Specific situations for which model-based approaches could prove to be more suitable will be presented, as well as potential bioequivalence metrics that could be considered for bioequivalence comparisons. The opportunities and challenges that are associated with these novel methods will also be discussed.

Model‐Informed Drug Development for Long‐Acting Injectable Products: Summary of American College of Clinical Pharmacology Symposium

“…M&S also can be used to identify adequate PK sampling times, to determine sample size, and to support innovative and efficient BE study designs. 16,17,26,27,[29][30][31][32][33]…”

Multivariate Assessment for Bioequivalence Based on the Correlation of Random Effect

“…In general, noncompartmental pharmacokinetic analysis has been considered as the standard approach for bioequivalence testing. 6 However, because of certain limitations of noncompartmental analysis including sufficient samples at time points post dose, observed sampling time points for AUC 0–t /AUC inf > 0.8, systemic circulation related to the exposure of site of action and linear pharmacokinetics, the model-based approach may be more appropriate in specific situations. 6 The model-based approach is individual-based, separately fitted data and is able to evaluate the pure metric of rate reflecting the individual absorption rate constants (Ka).…”

“… 6 However, because of certain limitations of noncompartmental analysis including sufficient samples at time points post dose, observed sampling time points for AUC 0–t /AUC inf > 0.8, systemic circulation related to the exposure of site of action and linear pharmacokinetics, the model-based approach may be more appropriate in specific situations. 6 The model-based approach is individual-based, separately fitted data and is able to evaluate the pure metric of rate reflecting the individual absorption rate constants (Ka). 6 As a result, model-based approaches can be beneficial for drugs with complex pharmacokinetics including nonlinear pharmacokinetics, non-elimination from the sampling compartment and endogenous homeostatic feedback mechanism, which may not be applicable to the assumption of noncompartmental analysis.…”

“… 6 The model-based approach is individual-based, separately fitted data and is able to evaluate the pure metric of rate reflecting the individual absorption rate constants (Ka). 6 As a result, model-based approaches can be beneficial for drugs with complex pharmacokinetics including nonlinear pharmacokinetics, non-elimination from the sampling compartment and endogenous homeostatic feedback mechanism, which may not be applicable to the assumption of noncompartmental analysis. 6 Furthermore, biosimilars and topical dermatological drugs are preferable candidates to apply the model-based approach due to the comparison of rate and extent of exposure at the site of action.…”

“… 6 Furthermore, biosimilars and topical dermatological drugs are preferable candidates to apply the model-based approach due to the comparison of rate and extent of exposure at the site of action. 6 .…”