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A Model‐Based Approach to Quantify the Time‐Course of Anti‐Drug Antibodies for Therapeutic Proteins
Author(s) -
Ren Yupeng,
Li Liang,
Kirshner Susan,
Wang Yaning,
Sahajwalla Chandrahas,
Ji Ping
Publication year - 2019
Publication title -
clinical pharmacology and therapeutics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.941
H-Index - 188
eISSN - 1532-6535
pISSN - 0009-9236
DOI - 10.1002/cpt.1267
Subject(s) - drug , antibody , computational biology , pharmacology , medicine , immunology , biology
A mathematical antidrug antibody (ADA) model was developed to quantitatively assess immunogenicity for therapeutic proteins. The ADA model was built with antibody titer data in subjects from 10 clinical trials. The time course of the antibody titers was quantitatively characterized with a two‐component semimechanistic model describing the double peaks of ADA titers. The relationship between antibody titer and incidence was also explored. The ADA incidences in subjects from 12 clinical trials were used for internal and external validations. The ADA titers reasonably predicted the incidence of antibody. The model‐predicted elimination rate constant for antibody titer was 14.1 × 10 −3 day −1 and 8.1 × 10 −3 day −1 in healthy subjects and patients, respectively. This research provided a useful tool to quantitatively evaluate immunogenicity and its impact for therapeutic proteins.