Evidence map›Paper›PMID 30027813›Full record

ArticleSLAS technology2018

Rapid Microbiology Screening in Pharmaceutical Workflows.

C Surrette, B Scherer, A Corwin, G Grossmann, A M Kaushik, K Hsieh, P Zhang, J C Liao, P K Wong, T H Wang and 1 more

Open access · hybridAbstract read
In one paragraph

Article in SLAS technology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.9field-weighted citation impact, top 28% 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

9 citing papers in PubMed, 18 citations in OpenAlex.

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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

11 authors at 4 institutions in 1 country.

C Surrette1 Electronics Organization, GE Global Research Center, Niskayuna, NY, USA.
B Scherer1 Electronics Organization, GE Global Research Center, Niskayuna, NY, USA.
A Corwin1 Electronics Organization, GE Global Research Center, Niskayuna, NY, USA.
G Grossmann2 Biology and Physics, GE Global Research Center, Niskayuna, NY, USA.
A M Kaushik3 Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
K Hsieh3 Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
P Zhang3 Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
J C Liao4 Department of Urology, Stanford University School of Medicine, Stanford, CA, USA.
P K Wong5 Department of Biomedical Engineering, Pennsylvania State University, University Park, PA, USA.
T H Wang3 Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
C M Puleo1 Electronics Organization, GE Global Research Center, Niskayuna, NY, USA.
GE Global Research (United States) · USJohns Hopkins University · USPennsylvania State University · USStanford University · US

Funding

A Droplet-based single cell platform for pathogen identification and ASTR01AI117032 · NIAID · JOHNS HOPKINS UNIVERSITY · PI LIAO, JOSEPH C, WANG, TZA-HUEI JEFF · 2015 to 2019
$5.7M
NIAID NIH HHS R01 AI117032
6 · The paper itself

Abstract

Recently advances in miniaturization and automation have been utilized to rapidly decrease the time to result for microbiology testing in the clinic. These advances have been made due to the limitations of conventional culture-based microbiology methods, including agar plate and microbroth dilution, which have long turnaround times and require physicians to treat patients empirically with antibiotics before test results are available. Currently, there exist similar limitations in pharmaceutical sterility and bioburden testing, where the long turnaround times associated with standard microbiology testing drive costly inefficiencies in workflows. These include the time lag associated with sterility screening within drug production lines and the warehousing cost and time delays within supply chains during product testing. Herein, we demonstrate a proof-of-concept combination of a rapid microfluidic assay and an efficient cell filtration process that enables a path toward integrating rapid tests directly into pharmaceutical microbiological screening workflows. We demonstrate separation and detection of Escherichia coli directly captured and analyzed from a mammalian (i.e., CHO) cell culture with a 3.0 h incubation. The demonstration is performed using a membrane filtration module that is compatible with sampling from bioreactors, enabling in-line sampling and process monitoring.

Indexed as

AnimalsBacteriaBioreactorsCHO CellsColoring AgentsCricetinaeCricetulusFiltrationIndicators and ReagentsMicrobiological TechniquesMicrofluidicsPhotochemistryTechnology, PharmaceuticalColoring AgentsIndicators and Reagentsbacteriabioburdencell processingcell therapymicrofluidicpathogenpharmaceuticalrapid microbiologyscreeningsterility

Identifiers

PMID30027813
PMCPMC6363118
OpenAlexW2884818311

What OpenQuestion holds

Textmetadata
LicenceTDM
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.