Evidence map›Paper›PMID 32531452›Full record

ReviewInternational journal of pharmaceutics2020

Protein aggregation and immunogenicity of biotherapeutics.

Ngoc B Pham, Wilson S Meng

Abstract readReview
In one paragraph

Review in International journal of pharmaceutics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers.

0numbers the graph read from it
0cells of the map it votes in
73citing 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

73 citing papers in PubMed.

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13 more citing papers are in PubMed but not listed here.

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

2 authors.

Ngoc B PhamGraduate School of Pharmaceutical Sciences, School of Pharmacy, Duquesne University, Pittsburgh, PA 15282, United States.
Wilson S MengGraduate School of Pharmaceutical Sciences, School of Pharmacy, Duquesne University, Pittsburgh, PA 15282, United States; McGowan Institute for Regenerative Medicine, University of Pittsburgh, PA 15219, United States. Electronic address: meng@duq.edu.

Funding

Induction of allogeneic tolerance with bioengineered thymus organoidsR01AI123392 · NIAID · ALLEGHENY-SINGER RESEARCH INSTITUTE · PI FAN, YONG · 2016 to 2019
$1.5M
DEVELOPMENT OF A REGULATORY T CELL MIMETIC FOR TOLERANCE INDUCTION IN SKIN TRANSPLANTATIONR21AI139828 · NIAID · DUQUESNE UNIVERSITY · PI MENG, WILSON S · 2019 to 2020
$378k
NIAID NIH HHS R01 AI123392NIAID NIH HHS R21 AI139828
6 · The paper itself

Abstract

Recombinant proteins are the mainstay of biopharmaceuticals. A key challenge in the manufacturing and formulation of protein biologic products is the tendency for the active pharmaceutical ingredients to aggregate, resulting in irreversible drug loss, and an increase in immunogenicity risk. While the molecular mechanisms of protein aggregation have been discussed extensively in the literature, knowledge gaps remain in connecting the phenomenon in the context of immunogenicity of biotherapeutics. In this review, we discussed factors that drive aggregation of pharmaceutical recombinant proteins, and highlighted methods of prediction and mitigation that can be deployed through the development stages, from formulation to bioproduction. The purpose is to stimulate new dialogs that would bridge the interface between physical characterizations of protein aggregates in biotherapeutics and the functional attributes of the immune system.

Indexed as

Antibodies, MonoclonalBiological ProductsDrug StabilityHumansHydrogen-Ion ConcentrationProtein AggregatesRecombinant ProteinsTechnology, PharmaceuticalAntibodies, MonoclonalBiological ProductsProtein AggregatesRecombinant ProteinsAntibodiesAnti-drugBioprocessingHigh-concentration protein formulationsMonoclonal antibodiesT cell epitopes

Identifiers

PMID32531452
PMCPMC7362938

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.