Evidence map›Paper›PMID 33738328›Full record

ReviewMolecular therapy. Methods & clinical development2021

Analytical methods for process and product characterization of recombinant adeno-associated virus-based gene therapies.

Andreas L Gimpel, Georgios Katsikis, Sha Sha, Andrew John Maloney, Moo Sun Hong, Tam N T Nguyen, Jacqueline Wolfrum, Stacy L Springs, Anthony J Sinskey, Scott R Manalis and 2 more

Open access · goldAbstract readReview
In one paragraph

Review in Molecular therapy. Methods & clinical development, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 85 papers.

0numbers the graph read from it
0cells of the map it votes in
85citing papers in PubMed
9.7field-weighted citation impact, top 1% 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

85 citing papers in PubMed, 171 citations in OpenAlex.

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  13. pH-dependent DNA degradation pathways for adeno-associated virus gene therapy.Molecular therapy. Methods & clinical development · 2025
    Article
  14. Article
  15. Article
  16. Residual DNA impurities in AAV vectors-nature and transcription.Molecular therapy. Methods & clinical development · 2025
    Article
  17. Article
  18. Article
  19. Article
  20. A clinician's guide to AAV production - How manufacturing platforms shape vector properties.Medizinische Genetik : Mitteilungsblatt des Berufsverbandes Medizinische Genetik e.V · 2025
    Article

25 more citing papers are in PubMed but not listed here.

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

12 authors at 2 institutions in 2 countries.

Andreas L GimpelDepartment of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Georgios KatsikisKoch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
Sha ShaDepartment of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA.
Andrew John MaloneyDepartment of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Moo Sun HongDepartment of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Tam N T NguyenDepartment of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Jacqueline WolfrumCenter for Biomedical Innovation, Massachusetts Institute of Technology, Cambridge, MA, USA.
Stacy L SpringsCenter for Biomedical Innovation, Massachusetts Institute of Technology, Cambridge, MA, USA.
Anthony J SinskeyDepartment of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA.
Scott R ManalisKoch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
Paul W BaroneCenter for Biomedical Innovation, Massachusetts Institute of Technology, Cambridge, MA, USA.
Richard D BraatzDepartment of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Massachusetts Institute of Technology · USETH Zurich · CH

Funding

Continuous Viral Vector Manufacturing based on Mechanistic Modeling and Novel Process AnalyticsR01FD006584 · FDA · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI BRAATZ, RICHARD DEAN, SINSKEY, ANTHONY J · 2018 to 2020
$1.8M
FDA HHS R01 FD006584
6 · The paper itself

Abstract

The optimization of upstream and downstream processes for production of recombinant adeno-associated virus (rAAV) with consistent quality depends on the ability to rapidly characterize critical quality attributes (CQAs). In the context of rAAV production, the virus titer, capsid content, and aggregation are identified as potential CQAs, affecting the potency, purity, and safety of rAAV-mediated gene therapy products. Analytical methods to measure these attributes commonly suffer from long turnaround times or low throughput for process development, although rapid, high-throughput methods are beginning to be developed and commercialized. These methods are not yet well established in academic or industrial practice, and supportive data are scarce. Here, we review both established and upcoming analytical methods for the quantification of rAAV quality attributes. In assessing each method, we highlight the progress toward rapid, at-line characterization of rAAV. Furthermore, we identify that a key challenge for transitioning from traditional to newer methods is the scarcity of academic and industrial experience with the latter. This literature review serves as a guide for the selection of analytical methods targeting quality attributes for rapid, high-throughput process characterization during process development of rAAV-mediated gene therapies.

Indexed as

AAVadeno-associated virusCQAscritical quality attributesgene therapiesprocess characterizationprocess developmentprocess understandingviral vectors

Identifiers

PMID33738328
PMCPMC7940698
OpenAlexW3130024205

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.