Evidence map›Paper›PMID 34664208›Full record

ArticlePharmaceutical research2021

Droplet-Based Microfluidic Tool to Quantify Viscosity of Concentrating Protein Solutions.

Deyu Yang, Maryam Daviran, Kelly M Schultz, Lynn M Walker

Abstract read
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In one paragraph

Article in Pharmaceutical research, 2021. 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

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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. Review
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

4 authors.

Deyu YangDepartment of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA, 15213, USA.
Maryam DaviranDepartment of Chemical and Biomolecular Engineering, Lehigh University, 111 Research Dr., Iacocca Hall, Bethlehem, PA, 18015, USA.
Kelly M SchultzDepartment of Chemical and Biomolecular Engineering, Lehigh University, 111 Research Dr., Iacocca Hall, Bethlehem, PA, 18015, USA.
Lynn M WalkerDepartment of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA, 15213, USA. lwalker@andrew.cmu.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeMeasurement of the viscosity of concentrated protein solutions is vital for the manufacture and delivery of protein therapeutics. Conventional methods for viscosity measurements require large solution volumes, creating a severe limitation during the early stage of protein development. The goal of this work is to develop a robust technique that requires minimal sample.

methodsIn this work, a droplet-based microfluidic device is developed to quantify the viscosity of protein solutions while concentrating in micrometer-scale droplets. The technique requires only microliters of sample. The corresponding viscosity is characterized by multiple particle tracking microrheology (MPT).

resultsWe show that the viscosities quantified in the microfluidic device are consistent with macroscopic results measured by a conventional rheometer for poly(ethylene) glycol (PEG) solutions. The technique was further applied to quantify viscosities of well-studied lysozyme and bovine serum albumin (BSA) solutions. Comparison to both macroscopic measurements and models (Krieger-Dougherty model) demonstrate the validity of the approach.

conclusionThe droplet-based microfluidic device provides accurate quantitative values of viscosity over a range of concentrations for protein solutions with small sample volumes (~ μL) and high compositional resolution. This device will be extended to study the effect of different excipients and other additives on the viscosity of protein solutions.

Indexed as

ExcipientsMicrofluidicsMuramidasePolyethylene GlycolsRheologySerum Albumin, BovineSingle Molecule ImagingSolutionsViscosityExcipientsMuramidasePolyethylene GlycolsSerum Albumin, BovineSolutionsConcentrationHigh Compositional resolutionMicrofluidicsProteinsViscosity

Identifiers

PMID34664208

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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.