Evidence map›Paper›PMID 36526726›Full record

ReviewNature protocols2023

Comprehensive multi-attribute method workflow for biotherapeutic characterization and current good manufacturing practices testing.

Silvia Millán-Martín, Craig Jakes, Sara Carillo, Richard Rogers, Da Ren, Jonathan Bones

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature protocols, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
2.6field-weighted citation impact, top 9% of its field
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

15 citing papers in PubMed, 39 citations in OpenAlex.

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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

6 authors at 3 institutions in 2 countries.

Silvia Millán-MartínNational Institute for Bioprocessing Research and Training, Dublin, Ireland.
Craig JakesNational Institute for Bioprocessing Research and Training, Dublin, Ireland.
Sara CarilloNational Institute for Bioprocessing Research and Training, Dublin, Ireland.
Richard RogersUmoja Biopharma, Seattle, WA, USA.
Da RenAmgen Inc., Process Development, Thousand Oaks, CA, USA.
Jonathan BonesNational Institute for Bioprocessing Research and Training, Dublin, Ireland. jonathan.bones@nibrt.ie.ORCID 0000-0002-8978-2592
National Institute for Bioprocessing Research and Training · IEUniversity College Dublin · IEAmgen (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The multi-attribute method (MAM) is a liquid chromatography-mass spectrometry (LC-MS)-based method that is used to directly characterize and monitor numerous product quality attributes (PQAs) at the amino acid level of a biopharmaceutical product. MAM enables identity testing based on primary sequence verification, detection and quantitation of post-translational modifications and impurities. This ability to simultaneously and directly determine PQAs of therapeutic proteins makes MAM a more informative, streamlined and productive workflow than conventional chromatographic and electrophoretic assays. MAM relies on proteolytic digestion of the sample followed by reversed-phase chromatographic separation and high-resolution LC-MS analysis in two phases. First, a discovery study to determine quality attributes for monitoring is followed by the creation of a targeted library based on high-resolution retention time plus accurate mass analysis. The second aspect of MAM is the monitoring phase based on the target peptide library and new peak detection using differential analysis of the data to determine the presence, absence or change of any species that might affect the activity or stability of the biotherapeutic. The sample preparation process takes between 90 and 120 min, whereas the time spent on instrumental and data analyses might vary from one to several days for different sample sizes, depending on the complexity of the molecule, the number of attributes to be monitored and the information to be detailed in the final report. MAM is developed to be used throughout the product life cycle, from process development through upstream and downstream processes to quality control release or under current good manufacturing practices regulations enforced by regulatory agencies.

Indexed as

Antibodies, MonoclonalProtein Processing, Post-TranslationalChromatography, LiquidMass SpectrometryWorkflowAntibodies, Monoclonal

Identifiers

PMID36526726
OpenAlexW4311685820

What OpenQuestion holds

Textmetadata
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.