Evidence map›Paper›PMID 36504719›Full record

ArticleFrontiers in molecular biosciences2022

Quality assessment of virus-like particle: A new transmission electron microscopy approach.

Salomé De Sá Magalhães, Emiliana De Santis, Saba Hussein-Gore, Mathieu Colomb-Delsuc, Eli Keshavarz-Moore

Abstract read
In one paragraph

Article in Frontiers in molecular biosciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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  7. Emerging Perspectives on Prime Editor Delivery to the Brain.Pharmaceuticals (Basel, Switzerland) · 2024
    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.

Salomé De Sá MagalhãesDepartment of Biochemical Engineering, University College London, UCL, London, United Kingdom.
Emiliana De SantisNational Physical Laboratory, NPL, Teddington, United Kingdom.
Saba Hussein-GoreVironova AB, Stockholm, Sweden.
Mathieu Colomb-DelsucVironova AB, Stockholm, Sweden.
Eli Keshavarz-MooreDepartment of Biochemical Engineering, University College London, UCL, London, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Transmission electron microscopy (TEM) is a gold standard analytical method for nanoparticle characterization and is playing a valuable role in virus-like particle (VLP) characterization extending to other biological entities such as viral vectors. A dedicated TEM facility is a challenge to both small and medium-sized enterprises (SMEs) and companies operating in low-and-middle income countries (LMICs) due to high start-up and running costs. A low-voltage TEM solution with assisted image acquisition and analysis such as the MiniTEM system, coupled with Vironova Imaging and Analysis Software (VIAS) could provide an affordable and practical alternative. The MiniTEM system has a small footprint and software that enables semi-automated data collection and image analysis workflows using built-in deep learning methods (convolutional neural networks) for automation in analysis, increasing speed of information processing and enabling scaling to larger datasets. In this perspective we outline the potential and challenges in the use of TEM as mainstream analytical tool in manufacturing settings. We highlight the rationale and preliminary findings from our proof-of-concept study aiming to develop a method to assess critical quality attributes (CQAs) of VLPs and facilitate adoption of TEM in manufacturing settings. In our study we explored all the steps, from sample preparation to data collection and analysis using synthetic VLPs as model systems. The applicability of the method in product development was verified at pilot-scale during the technology transfer of dengue VLPs development from a university setting to an LMIC- based vaccine manufacturing company, demonstrating the applicability of this analytical technique to VLP vaccine characterization.

Indexed as

CNNCQALMICSMEsTEMvaccinesVLP

Identifiers

PMID36504719
PMCPMC9732438

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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.