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Pharmacokinetic Similarity of Biologics: Analysis Using Nonlinear Mixed‐Effects Modeling
Author(s) -
Dubois A,
Gsteiger S,
Balser S,
Pigeolet E,
Steimer J L,
Pillai G,
Mentré F
Publication year - 2012
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 - 10.1038/clpt.2011.216
Subject(s) - similarity (geometry) , pharmacokinetics , equivalence (formal languages) , crossover , biosimilar , mathematics , nonlinear system , chemistry , medicine , pharmacology , computer science , artificial intelligence , discrete mathematics , image (mathematics) , physics , quantum mechanics
Our objective was to show, using two examples, that a pharmacokinetic (PK) similarity analysis can be performed using nonlinear mixed‐effects models (NLMEM). We used two studies that compared different biosimilars: a three‐way crossover trial with somatropin and a parallel‐group trial with epoetin‐α. For both data sets, the results of NLMEM‐based analysis were compared with those of noncompartmental analysis (NCA). For the latter analysis, we performed an NLMEM‐based equivalence Wald test on secondary parameters of the model: the area under the curve and the maximal concentration. Somatropin PK was described by a one‐compartment model and epoetin‐α PK by a two‐compartment model with linear and Michaelis–Menten elimination. For both studies, similarity of PK was demonstrated by means of both NCA and NLMEM, and both methods led to similar results. Therefore, for establishing similarity, PK data can be analyzed by either of the methods. NCA is an easier approach because it does not require data modeling; however, NLMEM leads to a better understanding of the underlying biological system. Clinical Pharmacology & Therapeutics (2012); 91 2, 234–242. doi: 10.1038/clpt.2011.216