Evidence map›Paper›PMID 39994880›Full record

ArticleBiotechnology and bioengineering2025

Multiple Use of Regenerated Depth Filters in Antibody Purification Processes.

Bernhard Spensberger, Ferdinand Stueckler, Marc Pompiati, Christoph Feistl, Thorsten Lemm, Roberto Falkenstein

Abstract read
In one paragraph

Article in Biotechnology and bioengineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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

1 citing paper in PubMed.

  1. Article
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

6 authors.

Bernhard SpensbergerRoche Diagnostics GmbH, Penzberg, Germany.
Ferdinand StuecklerRoche Diagnostics GmbH, Penzberg, Germany.
Marc PompiatiRoche Diagnostics GmbH, Penzberg, Germany.
Christoph FeistlRoche Diagnostics GmbH, Penzberg, Germany.
Thorsten LemmRoche Diagnostics GmbH, Penzberg, Germany.
Roberto FalkensteinRoche Diagnostics GmbH, Penzberg, Germany.ORCID 0000-0003-3753-2812

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

During the manufacturing of therapeutic antibodies, disposable depth filters are used after affinity chromatography to remove haze and process-related impurities such as host cell proteins (HCP) and DNA known as critical quality attributes. The present study reports on the regeneration of depth filters allowing their reuse for at least 10 times while retaining sufficiently high clarification capacity. Three filter types were evaluated including standard cellulose-based and fully synthetic matrix materials using acidic or alkaline solutions in alternating cycles of loading and regeneration. Both alkaline and acidic solutions were effective, however, overall acidic regeneration of the filter material appeared superior for multiple use. This was especially evident for the silica-containing XOSP filter, where HCP and DNA were almost completely removed and remained low over 10 applications. Simultaneously preserved product quality indicated a high resistance of the filter matrix toward regeneration. These unexpected findings offer improved flexibility for available filter capacity in downstream processing along with ecologic advantages over the single use applications. Regarding the carbon footprint of the filtration process, calculated potential savings by a factor of four can be achieved, mainly accounting for reduced plastic waste. Therefore, depth filter reuse supports sustainability and carbon dioxide reduction during production processes.

Indexed as

AntibodiesChromatography, AffinityFiltrationAnimalsDNAAntibodiesDNAantibodycarbon footprintdepth filter reusedownstream purificationimpurity removalregenerationsustainability

Identifiers

PMID39994880
PMCPMC12067032

What OpenQuestion holds

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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.