Evidence map›Paper›PMID 40032656›Full record

ArticlemAbs2025

Optimizing asymmetric antibody purification: a semi-automated process and its digital integration.

Christophe Prince, Despoina Georgiadou, Manuela Machatti, Matthias Hermann, Erwin van Puijenbroek

Abstract read
In one paragraph

Article in mAbs, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

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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

2 citing papers in PubMed.

  1. Review
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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

5 authors.

Christophe PrinceRoche Pharma Research & Early Development, Roche Innovation Center Zurich, Schlieren, Switzerland.
Despoina GeorgiadouRoche Pharma Research & Early Development, Roche Innovation Center Zurich, Schlieren, Switzerland.
Manuela MachattiRoche Pharma Research and Early Development (pRED), Roche Innovation Center Munich, Penzberg, Germany.
Matthias HermannRoche Pharma Research & Early Development, Roche Innovation Center Zurich, Schlieren, Switzerland.
Erwin van PuijenbroekRoche Pharma Research & Early Development, Roche Innovation Center Zurich, Schlieren, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over the past decades, immunization and display technologies have considerably increased the potential for generating new binders against cell surface targets. Concomitantly, the complexity of biologic therapeutic drugs has also increased, with new asymmetric formats such as bispecific antibodies or antibody fusion proteins making the supply of molecules for preclinical drug discovery more challenging. The purification of those molecules is crucial, and an efficient purification platform for drug discovery research units should have multiple aims. First, it needs to deliver the highest quality proteins for research activities at a fast pace in order to increase screening capacities. Second, it has to deliver protein with sufficient yield in order to cover the project requirements and minimize the repetition of production cycles. Through a case study for a bispecific antibody, we describe a semi-automated and digitalized purification platform aiming at accelerating and optimizing the supply of asymmetric antibodies for drug discovery. We show how the automation of repetitive tasks and the digitalization of the process can lead to increased throughput in the context of complex purifications, including a cation exchange chromatography separation step. Furthermore, we highlight how process digitalization leads to enhanced data capture and accessibility, facilitating decision-making along the purification process. With a maximal throughput of 36 asymmetric antibodies per week and data proving the consistency of the quality delivered, this platform represents a step forward in the supply of complex antibody formats for preclinical drug discovery.

Indexed as

Antibodies, BispecificAnimalsAutomationChromatography, Ion ExchangeDrug DiscoveryHumansAntibodies, BispecificAutomationbispecific antibodieshigh-throughputprocess digitalizationprotein purification

Identifiers

PMID40032656
PMCPMC11916402

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.