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Research Article

An integrated mammalian library approach for optimization and enhanced microfluidics-assisted antibody hit discovery

, , , , , , & show all
Pages 74-82 | Received 21 Nov 2022, Accepted 22 Jan 2023, Published online: 10 Feb 2023
 

Abstract

Recent years have seen the development of a variety of mammalian library approaches for display and secretion mode. Advantages include library approaches for engineering, preservation of precious immune repertoires and their repeated interrogation, as well as screening in final therapeutic format and host. Mammalian display approaches for antibody optimization exploit these advantages, necessitating the generation of large libraries but in turn enabling early screening for both manufacturability and target specificity. For suitable libraries, high antibody integration rates and resulting monoclonality need to be balanced – we present a solution for sufficient transmutability and acceptable monoclonality by applying an optimized ratio of coding to non-coding lentivirus. The recent advent of microfluidic-assisted hit discovery represents a perfect match to mammalian libraries in secretion mode, as the lower throughput fits well with the facile generation of libraries comprising a few million functional clones. In the presented work, Chinese Hamster Ovary cells were engineered to both express the target of interest and secrete antibodies in relevant formats, and specific clones were strongly enriched by high throughput screening for autocrine cellular binding. The powerful combination of mammalian secretion libraries and microfluidics-assisted hit discovery could reduce attrition rates and increase the probability to identify the best possible therapeutic antibody hits faster.

Authors contribution

AD, RG, SJ were involved in design and interpretation of the data; RGa, KK, HMM, DY, SPT conducted and interpreted experiments; AD drafted the paper; all authors revised it critically for intellectual content and approved the version to be published.

Acknowledgements

We thank Matthias Peipp for hints on NKG2D surface expression constructs, as well as Roland Schucht and Tom Wahlicht for methodology input and support. and were created using BioRender.com.

Disclosure statement

The authors are affiliated to Merck Healthcare KGaA, EMD Serono Inc. or Syngene International Limited, and confirm that there are no potential conflicts of interests.

Data availability statement

The data that support the findings of this study are available from the corresponding author, AD, upon reasonable request

Additional information

Funding

The authors are employees of Merck Healthcare KGaA, EMD Serono Inc. or Syngene International Limited, respectively. No additional funding was received.