Evidence map›Paper›PMID 37415319›Full record

ArticlemAbs

Prediction of long-term polysorbate degradation according to short-term degradation kinetics.

Sisi Zhang, Caterina Riccardi, Dane Carlson, Douglas Kamen, Kenneth S Graham, Mohammed Shameem, Hanne Bak, Hui Xiao, Ning Li

Abstract read
In one paragraph

Article in mAbs. 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

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

1 citing paper in PubMed.

  1. Article
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

9 authors.

Sisi ZhangAnalytical Chemistry, Regeneron Pharmaceuticals, Tarrytown, NY, USA.
Caterina RiccardiFormulation Group, Regeneron Pharmaceuticals, Tarrytown, NY, USA.
Dane CarlsonFormulation Group, Regeneron Pharmaceuticals, Tarrytown, NY, USA.
Douglas KamenFormulation Group, Regeneron Pharmaceuticals, Tarrytown, NY, USA.
Kenneth S GrahamFormulation Group, Regeneron Pharmaceuticals, Tarrytown, NY, USA.
Mohammed ShameemFormulation Group, Regeneron Pharmaceuticals, Tarrytown, NY, USA.
Hanne BakPreclinical Manufacturing and Process Development, Tarrytown, NY, USA.
Hui XiaoAnalytical Chemistry, Regeneron Pharmaceuticals, Tarrytown, NY, USA.
Ning LiAnalytical Chemistry, Regeneron Pharmaceuticals, Tarrytown, NY, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Polysorbates (PSs) are a class of surfactants commonly used in the formulation of protein therapeutic agents to provide protection against denaturation and aggregation. When the PS in these drug formulations degrades, loss of stabilization of the protein therapeutic and formulation may occur, resulting in particulate formation or other undesirable changes in product critical quality attributes. Here, we present a simplified platform to predict long-term PS20 and PS80 degradation for monoclonal antibody drugs containing the PS-degrading enzyme lysosomal acid lipase. The platform was based on a temperature-dependent equation derived from existing PS20 degradation stability data. Accurate prediction of both PS20 and PS80 hydrolysis for as long as 2 years was achieved through short-term kinetics studies performed within 2 weeks. This platform substantially shortens the time required to determine the long-term stability of PS degradation and therefore can be used to guide the purification process and optimization of antibody formulations.

Indexed as

PolysorbatesSurface-Active AgentsHydrolysisKineticsTemperaturePolysorbatesSurface-Active AgentsFree fatty acidslipase activitylong-term stabilitypolysorbate hydrolysisshort-term kinetics

Identifiers

PMID37415319
PMCPMC10332185

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.