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

Research output: Contribution to journalArticle

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 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.

Details

Authors
  • Adriana-Michelle Wolf Pérez
  • Pietro Sormanni
  • Jonathan Sonne Andersen
  • Laila Ismail Sakhnini
  • Ileana Rodriguez-Leon
  • Jais Rose Bjelke
  • Annette Juhl Gajhede
  • Leonardo De Maria
  • Daniel E Otzen
  • Michele Vendruscolo
  • Nikolai Lorenzen
External organisations
  • Novo Nordisk A/S
  • Aarhus University
  • University of Cambridge
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Biochemistry and Molecular Biology
Original languageEnglish
Pages (from-to)388-400
Number of pages13
JournalmAbs
Volume11
Issue number2
Publication statusPublished - 2018 Dec 14
Publication categoryResearch
Peer-reviewedYes
Externally publishedYes