Evidence map›Paper›PMID 34382900›Full record

ArticlemAbs

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

Norbert Furtmann, Marion Schneider, Nadja Spindler, Bjoern Steinmann, Ziyu Li, Ingo Focken, Joachim Meyer, Dilyana Dimova, Katja Kroll, Wulf Dirk Leuschner and 7 more

Open access · goldAbstract readVideo-Audio Media
In one paragraph

Article in mAbs. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
2.4field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 21 citations in OpenAlex.

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  10. Nanopore Sequencing for Mixed Samples.Methods in molecular biology (Clifton, N.J.) · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors at 2 institutions in 2 countries.

Norbert FurtmannR&D Large Molecules Research Platform Germany, Sanofi-Aventis Deutschland GmbH, Industriepark Höchst, Frankfurt Am Main, Germany.
Marion SchneiderR&D Large Molecules Research Platform Germany, Sanofi-Aventis Deutschland GmbH, Industriepark Höchst, Frankfurt Am Main, Germany.
Nadja SpindlerR&D Large Molecules Research Platform Germany, Sanofi-Aventis Deutschland GmbH, Industriepark Höchst, Frankfurt Am Main, Germany.
Bjoern SteinmannR&D Large Molecules Research Platform Germany, Sanofi-Aventis Deutschland GmbH, Industriepark Höchst, Frankfurt Am Main, Germany.
Ziyu LiR&D Integrated Drug Discovery Germany, Sanofi-Aventis Deutschland GmbH, Industriepark Höchst, Frankfurt Am Main, Germany.
Ingo FockenR&D Large Molecules Research Platform Germany, Sanofi-Aventis Deutschland GmbH, Industriepark Höchst, Frankfurt Am Main, Germany.ORCID 0000-0002-9604-0538
Joachim MeyerDigital R&D, Sanofi-Aventis Deutschland GmbH, Industriepark Höchst, Frankfurt Am Main, Germany.
Dilyana DimovaR&D Large Molecules Research Platform Germany, Sanofi-Aventis Deutschland GmbH, Industriepark Höchst, Frankfurt Am Main, Germany.
Katja KrollR&D Large Molecules Research Platform Germany, Sanofi-Aventis Deutschland GmbH, Industriepark Höchst, Frankfurt Am Main, Germany.
Wulf Dirk LeuschnerR&D Large Molecules Research Platform Germany, Sanofi-Aventis Deutschland GmbH, Industriepark Höchst, Frankfurt Am Main, Germany.
Audrey DebeaumontR&D Large Molecules Research Platform Germany, Sanofi-Aventis Deutschland GmbH, Industriepark Höchst, Frankfurt Am Main, Germany.
Magali MathieuR&D Integrated Drug Discovery France, Sanofi, Vitry Sur Seine Cedex, France.
Christian LangeR&D Large Molecules Research Platform Germany, Sanofi-Aventis Deutschland GmbH, Industriepark Höchst, Frankfurt Am Main, Germany.
Werner DittrichR&D Large Molecules Research Platform Germany, Sanofi-Aventis Deutschland GmbH, Industriepark Höchst, Frankfurt Am Main, Germany.
Jochen KruipIA Specialty Care Digital Innovation Biologics, Sanofi-Aventis Deutschland GmbH, Frankfurt Am Main, Germany.
Thorsten SchmidtR&D Large Molecules Research Platform Germany, Sanofi-Aventis Deutschland GmbH, Industriepark Höchst, Frankfurt Am Main, Germany.ORCID 0000-0001-9952-8881
Joerg BirkenfeldR&D Large Molecules Research Platform Germany, Sanofi-Aventis Deutschland GmbH, Industriepark Höchst, Frankfurt Am Main, Germany.ORCID 0000-0002-0611-0396
Sanofi (Germany) · DESanofi (France) · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Antibodies, BispecificAntibodies, MonoclonalAutomation, LaboratoryGene LibraryProtein EngineeringEscherichia coliHEK293 CellsHumansRecombinant ProteinsAntibodies, BispecificAntibodies, MonoclonalRecombinant ProteinsBispecific antibodiesdata analyticsdevelopabilityhigh throughput screeninglab automationprotein engineering

Identifiers

PMID34382900
PMCPMC8366542
OpenAlexW3187790401

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.