Multi-attribute monitoring (MAM) methodology for glycosylated subunit vaccines

Many protein-based vaccines comprise viral surface proteins which are chosen for their ability to stimulate the immune system. These vaccine molecules are often heavily glycosylated, and glycosylation plays critical roles in the immunological and stability properties of vaccines. The structural characterization and product quality attribute monitoring of such complex vaccine therapeutics during process development and manufacturing is very challenging. High throughput monitoring of multiple molecular attributes, particularly glycosylation, of recombinant glycoprotein subunit vaccines are needed to support entire vaccine production processes. Multi-attribute monitoring (MAM) technology involves assessing multiple critical molecular attributes of molecules in one set of analyses in an automated fashion, for product quality attribute requirements. MAM is still in the early development stages and is currently applied to therapeutics with very low levels of glycosylation such as monoclonal antibodies. MAM on glycoproteins with a higher number of glycosylation sites with high glycan heterogeneity such as subunit vaccine molecules is challenging as each glycan site and glycan modification exponentially increases data processing complexity. We developed a MAM workflow to perform detailed structural characterization of subunit protein vaccines, monitoring critical parameters such as intact mass, sequence identity, protein clipping, glycosylation, other post-translational modifications, and host cell proteins (HCP). By using a combination of software tools and product process monitoring strategy, we performed data processing at multiple steps and identified key attributes for each vaccine candidate under the development pipeline. Further, a high-throughput critical attribute monitoring MAM workflow was developed to support the influenza and HIV vaccine development processes including cell line selection, cell clone selection, cell culture optimization, stability study evaluation and final vaccine product characterization.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2025-11-21
DOI
https://doi.org/10.1038/s41598-025-24922-8
Primary Topic
vaccines and immunoinformatics approaches
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Multi-attribute monitoring (MAM) methodology for glycosylated subunit vaccines

Yanhong Yang, Lisa M. Miller Jenkins, Daniel B. Gowetski, Kevin Carlton et al.
Scientific Reports
vaccines and immunoinformatics approaches
article

Multi-attribute monitoring (MAM) methodology for glycosylated subunit vaccines

Yanhong Yang, Lisa M. Miller Jenkins, Daniel B. Gowetski, Kevin Carlton, Lisa A. Kueltzo, Q. Paula Lei, Nathan Barefoot, Shuzhen Yang, Elizabeth Scheideman, Ivan Loukinov, Jason G. Gall, Asif Shajahan, Jeremy J. Wolff, Rong Jiang, David Alejandro Cubides Maldonado, C. Carruthers, Dorra Benmohamed, Valerie Ficca
article en

Abstract

Many protein-based vaccines comprise viral surface proteins which are chosen for their ability to stimulate the immune system. These vaccine molecules are often heavily glycosylated, and glycosylation plays critical roles in the immunological and stability properties of vaccines. The structural characterization and product quality attribute monitoring of such complex vaccine therapeutics during process development and manufacturing is very challenging. High throughput monitoring of multiple molecular attributes, particularly glycosylation, of recombinant glycoprotein subunit vaccines are needed to support entire vaccine production processes. Multi-attribute monitoring (MAM) technology involves assessing multiple critical molecular attributes of molecules in one set of analyses in an automated fashion, for product quality attribute requirements. MAM is still in the early development stages and is currently applied to therapeutics with very low levels of glycosylation such as monoclonal antibodies. MAM on glycoproteins with a higher number of glycosylation sites with high glycan heterogeneity such as subunit vaccine molecules is challenging as each glycan site and glycan modification exponentially increases data processing complexity. We developed a MAM workflow to perform detailed structural characterization of subunit protein vaccines, monitoring critical parameters such as intact mass, sequence identity, protein clipping, glycosylation, other post-translational modifications, and host cell proteins (HCP). By using a combination of software tools and product process monitoring strategy, we performed data processing at multiple steps and identified key attributes for each vaccine candidate under the development pipeline. Further, a high-throughput critical attribute monitoring MAM workflow was developed to support the influenza and HIV vaccine development processes including cell line selection, cell clone selection, cell culture optimization, stability study evaluation and final vaccine product characterization.

Scientific ReportsVol. 15(1)
National Institutes of Health (US), National Institute of Allergy and Infectious Diseases (US), National Cancer Institute (US), Center for Cancer Research (US)
Openalex Percentile: Top 68%
vaccines and immunoinformatics approaches
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.