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A mechanistic pharmacokinetic model with drug and antidrug antibody interplay, and its application for assessing the impact of immunogenicity response on bioequivalence testing
Author(s) -
Liao Kai H.,
Udata Chandrasekhar,
Yin Donghua,
Sewell K. Lea,
Kantaridis Constantino,
Alvarez Daniel F.,
Meng Xu
Publication year - 2020
Publication title -
british journal of clinical pharmacology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.216
H-Index - 146
eISSN - 1365-2125
pISSN - 0306-5251
DOI - 10.1111/bcp.14312
Subject(s) - immunogenicity , bioequivalence , adalimumab , biosimilar , similarity (geometry) , medicine , pharmacokinetics , pharmacology , computational biology , immunology , computer science , antibody , artificial intelligence , biology , rheumatoid arthritis , image (mathematics)
Aims Single‐dose pharmacokinetic (PK) studies in healthy subjects have been the design of choice for bioequivalence determination for decades. This preference has been recently extended to PK similarity studies of proposed biosimilars. However, PK similarity studies can be complicated by the effect of immunogenicity response on drug disposition. The impact is exacerbated when there is an imbalance in host‐specific immunological characteristics of subjects between the test and reference groups. Such complications remain poorly understood. The purpose of this communication is to show that the impact of immunogenicity response on PK similarity determination can be critical, using adalimumab as an example. Methods Data for adalimumab concentrations and immunogenicity response over 10 weeks were obtained from 133 healthy subjects receiving a 40 mg dose of Humira® in a PK similarity study. Also, a population PK model with a mechanistic construct for delineating the interplay between adalimumab disposition and antidrug antibodies response was utilized to estimate via simulation the probability that a PK similarity study would fail in typical study settings. Results The simulations showed that the immunogenicity response can have a profound impact on the outcome of PK similarity determination. As such, the probability of failing to achieve the similarity conclusion increased to 51.9%, from 13.8% in the absence of immunogenicity response. Conclusion This study provides a model‐based framework for better understanding of how a PK similarity study can be optimally designed and for interpretation of the outcome of PK similarity determination when the drug disposition is affected in the presence of immunogenicity response.