Evidence map›Paper›PMID 34907498›Full record

ArticleAAPS PharmSciTech2021

Unexplored Excipients in Biotherapeutic Formulations: Natural Osmolytes as Potential Stabilizers Against Thermally Induced Aggregation of IgG1 Biotherapeutics.

Purva P Bhojane, Srishti Joshi, Sushree Jagriti Sahoo, Anurag S Rathore

Abstract read
In one paragraph

Article in AAPS PharmSciTech, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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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

4 citing papers in PubMed.

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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

4 authors.

Purva P BhojaneDepartment of Chemical Engineering, Indian Institute of Technology, Hauz Khas, New Delhi, 110016, India.
Srishti JoshiDepartment of Chemical Engineering, Indian Institute of Technology, Hauz Khas, New Delhi, 110016, India.
Sushree Jagriti SahooDepartment of Chemical Engineering, Indian Institute of Technology, Hauz Khas, New Delhi, 110016, India.
Anurag S RathoreDepartment of Chemical Engineering, Indian Institute of Technology, Hauz Khas, New Delhi, 110016, India. asrathore@biotechcmz.com.ORCID http://orcid.org/0000-0002-5913-4244

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Monoclonal antibodies (mAbs), while incredibly successful, are prone to a variety of degradation pathways, the most significant of which is aggregation. One of the most commonly used strategy to overcome protein aggregation is addition of excipients to the formulation. Osmolytes such as trehalose, sucrose, and glycine are widely used. In this paper, we explore potential use of naturally occurring osmolytes such as betaine, sarcosine, ectoine, and hydroxyectoine for reducing aggregation of mAb therapeutics. Experimentation has been performed on two IgG1 mAbs via accelerated stability studies. A variety of analytical tools have been used for monitoring the impact, dynamic light scattering (DLS) for colloidal stability, Fourier transform infrared (FTIR) spectroscopy and fluorescence spectroscopy for conformational stability and the higher order structure (HOS), and differential scanning calorimetry (DSC) for thermal stability. No significant impact of osmolyte addition was observed on protein structure, on comparative Fc receptor (FcRn) binding, and on biocompatibility as per our hemolytic assay. Our results rank the osmolytes' stabilizing trend to be sarcosine > betaine > hydroxyectoine > ectoine. Sarcosine emerged as the most successful osmolyte rendering highest degree of protection against aggregation. Our data support the prospect of using these osmolytes as successful excipients for mAb formulations.

Indexed as

ExcipientsImmunoglobulin GAntibodies, MonoclonalCalorimetry, Differential ScanningProtein AggregatesAntibodies, MonoclonalExcipientsImmunoglobulin GProtein AggregatesBiotherapeuticsFormulationMonoclonal antibodyOsmolyteStability

Identifiers

PMID34907498
PMCPMC8670780

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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.