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In vitro and in silico assessment of the developability of a designed monoclonal antibody library

Wolf Pérez, Adriana-Michelle ; Sormanni, Pietro ; Andersen, Jonathan Sonne ; Sakhnini, Laila Ismail LU orcid ; Rodriguez-Leon, Ileana ; Bjelke, Jais Rose ; Gajhede, Annette Juhl ; De Maria, Leonardo ; Otzen, Daniel E and Vendruscolo, Michele , et al. (2018) In mAbs 11(2). p.388-400
Abstract

Despite major advances in antibody discovery technologies, the successful development of monoclonal antibodies (mAbs) into effective therapeutic and diagnostic agents can often be impeded by developability liabilities, such as poor expression, low solubility, high viscosity and aggregation. Therefore, strategies to predict at the early phases of antibody development the risk of late-stage failure of antibody candidates are highly valuable. In this work, we employ the in silico solubility predictor CamSol to design a library of 17 variants of a humanized mAb predicted to span a broad range of solubility values, and we examine their developability potential with a battery of commonly used in vitro and in silico assays. Our results... (More)

Despite major advances in antibody discovery technologies, the successful development of monoclonal antibodies (mAbs) into effective therapeutic and diagnostic agents can often be impeded by developability liabilities, such as poor expression, low solubility, high viscosity and aggregation. Therefore, strategies to predict at the early phases of antibody development the risk of late-stage failure of antibody candidates are highly valuable. In this work, we employ the in silico solubility predictor CamSol to design a library of 17 variants of a humanized mAb predicted to span a broad range of solubility values, and we examine their developability potential with a battery of commonly used in vitro and in silico assays. Our results demonstrate the ability of CamSol to rationally enhance mAb developability, and provide a quantitative comparison of in vitro developability measurements with each other and with more resource-intensive solubility measurements, as well as with in silico predictors that offer a potentially faster and cheaper alternative. We observed a strong correlation between predicted and experimentally determined solubility values, as well as with measurements obtained using a panel of in vitro developability assays that probe non-specific interactions. These results indicate that computational methods have the potential to reduce or eliminate the need of carrying out laborious in vitro quality controls for large numbers of lead candidates. Overall, our study provides support to the emerging view that the implementation of in silico tools in antibody discovery campaigns can ensure rapid and early selection of antibodies with optimal developability potential.

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publishing date
type
Contribution to journal
publication status
published
subject
in
mAbs
volume
11
issue
2
pages
13 pages
publisher
Taylor & Francis
external identifiers
  • pmid:30523762
  • scopus:85060257724
ISSN
1942-0862
DOI
10.1080/19420862.2018.1556082
language
English
LU publication?
no
id
dd01c5da-01db-4751-8701-569096e854b6
date added to LUP
2019-06-17 16:56:36
date last changed
2024-06-26 20:10:26
@article{dd01c5da-01db-4751-8701-569096e854b6,
  abstract     = {{<p>Despite major advances in antibody discovery technologies, the successful development of monoclonal antibodies (mAbs) into effective therapeutic and diagnostic agents can often be impeded by developability liabilities, such as poor expression, low solubility, high viscosity and aggregation. Therefore, strategies to predict at the early phases of antibody development the risk of late-stage failure of antibody candidates are highly valuable. In this work, we employ the in silico solubility predictor CamSol to design a library of 17 variants of a humanized mAb predicted to span a broad range of solubility values, and we examine their developability potential with a battery of commonly used in vitro and in silico assays. Our results demonstrate the ability of CamSol to rationally enhance mAb developability, and provide a quantitative comparison of in vitro developability measurements with each other and with more resource-intensive solubility measurements, as well as with in silico predictors that offer a potentially faster and cheaper alternative. We observed a strong correlation between predicted and experimentally determined solubility values, as well as with measurements obtained using a panel of in vitro developability assays that probe non-specific interactions. These results indicate that computational methods have the potential to reduce or eliminate the need of carrying out laborious in vitro quality controls for large numbers of lead candidates. Overall, our study provides support to the emerging view that the implementation of in silico tools in antibody discovery campaigns can ensure rapid and early selection of antibodies with optimal developability potential.</p>}},
  author       = {{Wolf Pérez, Adriana-Michelle and Sormanni, Pietro and Andersen, Jonathan Sonne and Sakhnini, Laila Ismail and Rodriguez-Leon, Ileana and Bjelke, Jais Rose and Gajhede, Annette Juhl and De Maria, Leonardo and Otzen, Daniel E and Vendruscolo, Michele and Lorenzen, Nikolai}},
  issn         = {{1942-0862}},
  language     = {{eng}},
  month        = {{12}},
  number       = {{2}},
  pages        = {{388--400}},
  publisher    = {{Taylor & Francis}},
  series       = {{mAbs}},
  title        = {{In vitro and in silico assessment of the developability of a designed monoclonal antibody library}},
  url          = {{http://dx.doi.org/10.1080/19420862.2018.1556082}},
  doi          = {{10.1080/19420862.2018.1556082}},
  volume       = {{11}},
  year         = {{2018}},
}