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A single molecular descriptor to predict solution behavior of therapeutic antibodies
Despite the therapeutic success of monoclonal antibodies (mAbs), early identification of developable mAb drug candidates with optimal manufacturability, stability, and delivery attributes remains elusive. Poor solution behavior, which manifests as high solution viscosity or opalescence, profoundly a...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for the Advancement of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7457339/ https://www.ncbi.nlm.nih.gov/pubmed/32923611 http://dx.doi.org/10.1126/sciadv.abb0372 |
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author | Kingsbury, Jonathan S. Saini, Amandeep Auclair, Sarah Marie Fu, Li Lantz, Michaela M. Halloran, Kevin T. Calero-Rubio, Cesar Schwenger, Walter Airiau, Christian Y. Zhang, Jifeng Gokarn, Yatin R. |
author_facet | Kingsbury, Jonathan S. Saini, Amandeep Auclair, Sarah Marie Fu, Li Lantz, Michaela M. Halloran, Kevin T. Calero-Rubio, Cesar Schwenger, Walter Airiau, Christian Y. Zhang, Jifeng Gokarn, Yatin R. |
author_sort | Kingsbury, Jonathan S. |
collection | PubMed |
description | Despite the therapeutic success of monoclonal antibodies (mAbs), early identification of developable mAb drug candidates with optimal manufacturability, stability, and delivery attributes remains elusive. Poor solution behavior, which manifests as high solution viscosity or opalescence, profoundly affects the developability of mAb drugs. Using a diverse dataset of 59 mAbs, including 43 approved products, and an array of molecular descriptors spanning colloidal, conformational, charge-based, hydrodynamic, and hydrophobic properties, we show that poor solution behavior is prevalent (>30%) in mAbs and is singularly predicted (>90%) by the diffusion interaction parameter (k(D)), a dilute-solution measure of colloidal self-interaction. No other descriptor, individually or in combination, was found to be as effective as k(D). We also show that well-behaved mAbs, a substantial subset of which bear high positive charge and pI, present no disadvantages with respect to pharmacokinetics in humans. Here, we provide a systematic framework with quantitative thresholds for selecting well-behaved therapeutic mAbs during drug discovery. |
format | Online Article Text |
id | pubmed-7457339 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | American Association for the Advancement of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-74573392020-09-11 A single molecular descriptor to predict solution behavior of therapeutic antibodies Kingsbury, Jonathan S. Saini, Amandeep Auclair, Sarah Marie Fu, Li Lantz, Michaela M. Halloran, Kevin T. Calero-Rubio, Cesar Schwenger, Walter Airiau, Christian Y. Zhang, Jifeng Gokarn, Yatin R. Sci Adv Research Articles Despite the therapeutic success of monoclonal antibodies (mAbs), early identification of developable mAb drug candidates with optimal manufacturability, stability, and delivery attributes remains elusive. Poor solution behavior, which manifests as high solution viscosity or opalescence, profoundly affects the developability of mAb drugs. Using a diverse dataset of 59 mAbs, including 43 approved products, and an array of molecular descriptors spanning colloidal, conformational, charge-based, hydrodynamic, and hydrophobic properties, we show that poor solution behavior is prevalent (>30%) in mAbs and is singularly predicted (>90%) by the diffusion interaction parameter (k(D)), a dilute-solution measure of colloidal self-interaction. No other descriptor, individually or in combination, was found to be as effective as k(D). We also show that well-behaved mAbs, a substantial subset of which bear high positive charge and pI, present no disadvantages with respect to pharmacokinetics in humans. Here, we provide a systematic framework with quantitative thresholds for selecting well-behaved therapeutic mAbs during drug discovery. American Association for the Advancement of Science 2020-08-05 /pmc/articles/PMC7457339/ /pubmed/32923611 http://dx.doi.org/10.1126/sciadv.abb0372 Text en Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). https://creativecommons.org/licenses/by-nc/4.0/ https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (https://creativecommons.org/licenses/by-nc/4.0/) , which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited. |
spellingShingle | Research Articles Kingsbury, Jonathan S. Saini, Amandeep Auclair, Sarah Marie Fu, Li Lantz, Michaela M. Halloran, Kevin T. Calero-Rubio, Cesar Schwenger, Walter Airiau, Christian Y. Zhang, Jifeng Gokarn, Yatin R. A single molecular descriptor to predict solution behavior of therapeutic antibodies |
title | A single molecular descriptor to predict solution behavior of therapeutic antibodies |
title_full | A single molecular descriptor to predict solution behavior of therapeutic antibodies |
title_fullStr | A single molecular descriptor to predict solution behavior of therapeutic antibodies |
title_full_unstemmed | A single molecular descriptor to predict solution behavior of therapeutic antibodies |
title_short | A single molecular descriptor to predict solution behavior of therapeutic antibodies |
title_sort | single molecular descriptor to predict solution behavior of therapeutic antibodies |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7457339/ https://www.ncbi.nlm.nih.gov/pubmed/32923611 http://dx.doi.org/10.1126/sciadv.abb0372 |
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