Data-Driven Antibody Engineering Using Genedata Biologics™

Wendt, Maria; Cappuccilli, Guido

doi:10.1007/978-1-4939-6857-2_15

Cited by 1 publication

(1 citation statement)

References 8 publications

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“…Figure 1 schematically shows the flow of the individual work steps along the MSAT engineering value chain, which are all supported by a customized version of Genedata Biologics™ (GDB) 23 software. In-silico MSAT design, as well as all data management activities and associated automated lab unit operations (LUO), are illustrated by the example of a bispecific tetravalent CODV-Ig molecule.…”

Section: Resultsmentioning

confidence: 99%

An end-to-end automated platform process for high-throughput engineering of next-generation multi-specific antibody therapeutics

Furtmann

Schneider

Spindler

et al. 2021

mAbs

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Next-generation multi-specific antibody therapeutics (MSATs) are engineered to combine several functional activities into one molecule to provide higher efficacy compared to conventional, mono-specific antibody therapeutics. However, highly engineered MSATs frequently display poor yields and less favorable drug-like properties (DLPs), which can adversely affect their development. Systematic screening of a large panel of MSAT variants in very high throughput (HT) is thus critical to identify potent molecule candidates with good yield and DLPs early in the discovery process. Here we report on the establishment of a novel, format-agnostic platform process for the fast generation and multiparametric screening of tens of thousands of MSAT variants. To this end, we have introduced full automation across the entire value chain for MSAT engineering. Specifically, we have automated the in-silico design of very large MSAT panels such that it reflects precisely the wet-lab processes for MSAT DNA library generation. This includes mass saturation mutagenesis or bulk modular cloning technologies while, concomitantly, enabling library deconvolution approaches using HT Sanger DNA sequencing. These DNA workflows are tightly linked to fully automated downstream processes for compartmentalized mammalian cell transfection expression, and screening of multiple parameters. All sub-processes are seamlessly integrated with tailored workflow supporting bioinformatics. As described here, we used this platform to perform multifactor optimization of a next-generation bispecific, cross-over dual variable domain-Ig (CODV-Ig). Screening of more than 25,000 individual protein variants in mono- and bispecific format led to the identification of CODV-Ig variants with over 1,000-fold increased potency and significantly optimized production titers, demonstrating the power and versatility of the platform.

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Section: Resultsmentioning

confidence: 99%