Evidence map›Paper›PMID 39905691›Full record

ReviewBiotechnology and bioengineering2025

Chromatography in Downstream Processing of Recombinant Adeno-Associated Viruses: A Review of Current and Future Practises.

Julius Klemens Lorek, Madelène Isaksson, Bernt Nilsson

Abstract readReview
In one paragraph

Review 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 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
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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

3 authors.

Julius Klemens LorekDepartment of Process and Life Science Engineering, Lund University, Lund, Sweden.ORCID http://orcid.org/0000-0001-9387-9461
Madelène IsakssonDepartment of Process and Life Science Engineering, Lund University, Lund, Sweden.
Bernt NilssonDepartment of Process and Life Science Engineering, Lund University, Lund, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recombinant adeno-associated virus (rAAV) has emerged as an attractive gene delivery vector platform to treat both rare and pervasive diseases. With more and more rAAV-based therapies entering late-stage clinical trials and commercialization, there is an increasing pressure on the rAAV manufacturing process to accelerate drug development, account for larger trials, and commercially provide high doses. Still, many of the pre-clinical and clinical manufacturing processes are tied to outdated technologies, which results in substantial production expenses. Those processes face challenges including low productivity and difficult scalability, which limits its ability to provide for required dosages which in turn influences the accessibility of the drug. And as upstream efforts are expected to increase productivities, the downstream part needs to adapt with more scalable and efficient technologies. In this review, both traditional and novel rAAV downstream technologies are presented and discussed. Traditional rAAV downstream processes are based on density gradient ultracentrifugation and have been shown to effectively purify rAAVs with high yields and purities. However, those processes lack scalability and efficiency, which is why novel rAAV downstream processes based on column-chromatography have emerged as an attractive alternative and show potential for integration in continuous processes, following the principle of next-generation manufacturing.

Indexed as

ChromatographyDependovirusGenetic VectorsGenetic TherapyHumanscolumn‐chromatographycontinuous biomanufacturinggene therapyrAAV downstream processingrAAV manufacturingrecombinant Adeno‐associated virus

Identifiers

PMID39905691
PMCPMC11975191

What OpenQuestion holds

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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.