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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....
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2022
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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. |
format | Online Article Text |
id | pubmed-8842250 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
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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