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Aggregation Time Machine: A Platform for the Prediction and Optimization of Long-Term Antibody Stability Using Short-Term Kinetic Analysis

[Image: see text] Monoclonal antibodies are the fastest growing class of therapeutics. However, aggregation limits their shelf life and can lead to adverse immune responses. Assessment and optimization of the long-term antibody stability are therefore key challenges in the biologic drug development....

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Autores principales: Bunc, Marko, Hadži, San, Graf, Christian, Bončina, Matjaž, Lah, Jurij
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2022
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8842250/
https://www.ncbi.nlm.nih.gov/pubmed/35090111
http://dx.doi.org/10.1021/acs.jmedchem.1c02010
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author Bunc, Marko
Hadži, San
Graf, Christian
Bončina, Matjaž
Lah, Jurij
author_facet Bunc, Marko
Hadži, San
Graf, Christian
Bončina, Matjaž
Lah, Jurij
author_sort Bunc, Marko
collection PubMed
description [Image: see text] Monoclonal antibodies are the fastest growing class of therapeutics. However, aggregation limits their shelf life and can lead to adverse immune responses. Assessment and optimization of the long-term antibody stability are therefore key challenges in the biologic drug development. Here, we present a platform based on the analysis of temperature-dependent aggregation data that can dramatically shorten the assessment of the long-term aggregation stability and thus accelerate the optimization of antibody formulations. For a set of antibodies used in the therapeutic areas from oncology to rheumatology and osteoporosis, we obtain an accurate prediction of aggregate fractions for up to three years using the data obtained on a much shorter time scale. Significantly, the strategy combining kinetic and thermodynamic analysis not only contributes to a better understanding of the molecular mechanisms of antibody aggregation but has already proven to be very effective in the development and production of biological therapeutics.
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spelling pubmed-88422502022-02-15 Aggregation Time Machine: A Platform for the Prediction and Optimization of Long-Term Antibody Stability Using Short-Term Kinetic Analysis Bunc, Marko Hadži, San Graf, Christian Bončina, Matjaž Lah, Jurij J Med Chem [Image: see text] Monoclonal antibodies are the fastest growing class of therapeutics. However, aggregation limits their shelf life and can lead to adverse immune responses. Assessment and optimization of the long-term antibody stability are therefore key challenges in the biologic drug development. Here, we present a platform based on the analysis of temperature-dependent aggregation data that can dramatically shorten the assessment of the long-term aggregation stability and thus accelerate the optimization of antibody formulations. For a set of antibodies used in the therapeutic areas from oncology to rheumatology and osteoporosis, we obtain an accurate prediction of aggregate fractions for up to three years using the data obtained on a much shorter time scale. Significantly, the strategy combining kinetic and thermodynamic analysis not only contributes to a better understanding of the molecular mechanisms of antibody aggregation but has already proven to be very effective in the development and production of biological therapeutics. American Chemical Society 2022-01-28 2022-02-10 /pmc/articles/PMC8842250/ /pubmed/35090111 http://dx.doi.org/10.1021/acs.jmedchem.1c02010 Text en © 2022 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by/4.0/Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Bunc, Marko
Hadži, San
Graf, Christian
Bončina, Matjaž
Lah, Jurij
Aggregation Time Machine: A Platform for the Prediction and Optimization of Long-Term Antibody Stability Using Short-Term Kinetic Analysis
title Aggregation Time Machine: A Platform for the Prediction and Optimization of Long-Term Antibody Stability Using Short-Term Kinetic Analysis
title_full Aggregation Time Machine: A Platform for the Prediction and Optimization of Long-Term Antibody Stability Using Short-Term Kinetic Analysis
title_fullStr Aggregation Time Machine: A Platform for the Prediction and Optimization of Long-Term Antibody Stability Using Short-Term Kinetic Analysis
title_full_unstemmed Aggregation Time Machine: A Platform for the Prediction and Optimization of Long-Term Antibody Stability Using Short-Term Kinetic Analysis
title_short Aggregation Time Machine: A Platform for the Prediction and Optimization of Long-Term Antibody Stability Using Short-Term Kinetic Analysis
title_sort aggregation time machine: a platform for the prediction and optimization of long-term antibody stability using short-term kinetic analysis
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8842250/
https://www.ncbi.nlm.nih.gov/pubmed/35090111
http://dx.doi.org/10.1021/acs.jmedchem.1c02010
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