Evidence map›Paper›PMID 41544820›Full record

ReviewAdvanced drug delivery reviews2026

Optical imaging and spectroscopic characterization of subvisible particles in protein therapeutics.

Brian S Wong, Jing Ling, Yongchao Su, Dan Fu

Abstract readReview
In one paragraph

Review in Advanced drug delivery reviews, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Brian S WongDepartment of Chemistry, University of Washington, Seattle, WA 98195, United States.
Jing LingPharmaceutical Sciences and Clinical Supply, Merck & Co., Inc., Rahway, NJ 07065, United States.
Yongchao SuPharmaceutical Sciences and Clinical Supply, Merck & Co., Inc., Rahway, NJ 07065, United States.
Dan FuDepartment of Chemistry, University of Washington, Seattle, WA 98195, United States. Electronic address: danfu@uw.edu.

Funding

Non-perturbative imaging of intracellular drug exposure and drug response of kinase inhibitors - Admin SuppR35GM133435 · NIGMS · UNIVERSITY OF WASHINGTON · PI Dan Fu · 2019 to 2026
$2.8M
NIGMS NIH HHS R35 GM133435
6 · The paper itself

Abstract

The presence of subvisible particles in protein-based pharmaceutics is a critical quality attribute that is highly regulated due to potential risks to product stability, quality, bioavailability, and patient safety. While numerous analytical technologies have been developed to measure and analyze these particles, optical characterization methods are widely used for their simplicity, robustness, and versatility. Selecting the appropriate technique from a vast array of optical spectroscopy and imaging methods can be overwhelming, but it is crucial for successful characterization. For example, compendial methods such as light obscuration are most commonly used but can underestimate particle counts and are unable to provide chemical identification. This review article aims to provide a comprehensive comparison of optical particle characterization techniques, detailing their physical principles, applications, strengths, and weaknesses. We evaluate methods based on elastic light scattering, flow-based imaging, particle tracking, and vibrational spectroscopy. We highlight the inherent trade-off between analytical throughput and information content, aiming to guide the rational selection of analytical tools for the comprehensive characterization of subvisible particles in protein therapeutics.

Indexed as

Optical ImagingProteinsAnimalsHumansParticle SizeSpectrum AnalysisProteinsAggregationLight scatteringMicroscopyParticle characterizationProtein therapeuticsSpectroscopySubvisible particles

Identifiers

PMID41544820
PMCPMC12900661

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.