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Use of population approach non-linear mixed effects models in the evaluation of biosimilarity of monoclonal antibodies

PURPOSE: Population pharmacokinetic analyses (PPK) have been used to establish bioequivalence for small molecules and some biologicals. We investigated whether PPK could also be useful in biosimilarity testing for monoclonal antibodies (MAbs). METHODS: Data from a biosimilarity trial with two trastu...

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Autores principales: Reijers, Joannes A. A., van Donge, T., Schepers, F. M. L., Burggraaf, J., Stevens, J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5055907/
https://www.ncbi.nlm.nih.gov/pubmed/27515979
http://dx.doi.org/10.1007/s00228-016-2101-6
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author Reijers, Joannes A. A.
van Donge, T.
Schepers, F. M. L.
Burggraaf, J.
Stevens, J.
author_facet Reijers, Joannes A. A.
van Donge, T.
Schepers, F. M. L.
Burggraaf, J.
Stevens, J.
author_sort Reijers, Joannes A. A.
collection PubMed
description PURPOSE: Population pharmacokinetic analyses (PPK) have been used to establish bioequivalence for small molecules and some biologicals. We investigated whether PPK could also be useful in biosimilarity testing for monoclonal antibodies (MAbs). METHODS: Data from a biosimilarity trial with two trastuzumab products were used to build population pharmacokinetic models. First, a combined model was developed and similarity between test and reference product was evaluated by performing a covariate analysis with trastuzumab drug product (test or reference) on all model parameters. Next, two separate models were developed, one for each drug product. The model structure and parameters were compared and evaluated for differences. RESULTS: Drug product could not be identified as statistically significant covariate on any parameter in the combined model, and the addition of drug product as covariate did not improve the model fit. A similar structural model described both the test and reference data best. Only minor differences were found between the estimated parameters from these separate models. CONCLUSIONS: PPK can also be used to support a biosimilarity claim for a MAb. However, in contrast to the standard non-compartmental analysis, there is less experience with a PPK approach. Here, we describe two methods of how PPK can be incorporated in biosimilarity testing for complex therapeutics. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00228-016-2101-6) contains supplementary material, which is available to authorized users.
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spelling pubmed-50559072016-10-26 Use of population approach non-linear mixed effects models in the evaluation of biosimilarity of monoclonal antibodies Reijers, Joannes A. A. van Donge, T. Schepers, F. M. L. Burggraaf, J. Stevens, J. Eur J Clin Pharmacol Pharmacokinetics and Disposition PURPOSE: Population pharmacokinetic analyses (PPK) have been used to establish bioequivalence for small molecules and some biologicals. We investigated whether PPK could also be useful in biosimilarity testing for monoclonal antibodies (MAbs). METHODS: Data from a biosimilarity trial with two trastuzumab products were used to build population pharmacokinetic models. First, a combined model was developed and similarity between test and reference product was evaluated by performing a covariate analysis with trastuzumab drug product (test or reference) on all model parameters. Next, two separate models were developed, one for each drug product. The model structure and parameters were compared and evaluated for differences. RESULTS: Drug product could not be identified as statistically significant covariate on any parameter in the combined model, and the addition of drug product as covariate did not improve the model fit. A similar structural model described both the test and reference data best. Only minor differences were found between the estimated parameters from these separate models. CONCLUSIONS: PPK can also be used to support a biosimilarity claim for a MAb. However, in contrast to the standard non-compartmental analysis, there is less experience with a PPK approach. Here, we describe two methods of how PPK can be incorporated in biosimilarity testing for complex therapeutics. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00228-016-2101-6) contains supplementary material, which is available to authorized users. Springer Berlin Heidelberg 2016-08-11 2016 /pmc/articles/PMC5055907/ /pubmed/27515979 http://dx.doi.org/10.1007/s00228-016-2101-6 Text en © The Author(s) 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Pharmacokinetics and Disposition
Reijers, Joannes A. A.
van Donge, T.
Schepers, F. M. L.
Burggraaf, J.
Stevens, J.
Use of population approach non-linear mixed effects models in the evaluation of biosimilarity of monoclonal antibodies
title Use of population approach non-linear mixed effects models in the evaluation of biosimilarity of monoclonal antibodies
title_full Use of population approach non-linear mixed effects models in the evaluation of biosimilarity of monoclonal antibodies
title_fullStr Use of population approach non-linear mixed effects models in the evaluation of biosimilarity of monoclonal antibodies
title_full_unstemmed Use of population approach non-linear mixed effects models in the evaluation of biosimilarity of monoclonal antibodies
title_short Use of population approach non-linear mixed effects models in the evaluation of biosimilarity of monoclonal antibodies
title_sort use of population approach non-linear mixed effects models in the evaluation of biosimilarity of monoclonal antibodies
topic Pharmacokinetics and Disposition
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5055907/
https://www.ncbi.nlm.nih.gov/pubmed/27515979
http://dx.doi.org/10.1007/s00228-016-2101-6
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