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Record W2809336329 · doi:10.1016/j.jpba.2018.06.025

27Al and 31P NMR spectroscopy method development to quantify aluminum phosphate in adjuvanted vaccine formulations

2018· article· en· W2809336329 on OpenAlexafffund
Rahima Khatun, Howard N. Hunter, Yi Sheng, Bruce Carpick, Marina Kirkitadze

Bibliographic record

VenueJournal of Pharmaceutical and Biomedical Analysis · 2018
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Response and Inflammation
Canadian institutionsSanofi (Canada)York University
FundersMitacsUniversity of TorontoYork UniversitySanofi PasteurGovernment of Ontario
KeywordsChemistryPhosphateNuclear magnetic resonance spectroscopyAluminiumSpectroscopyOrganic chemistry

Abstract

fetched live from OpenAlex

A novel qNMR method is described for the quantitative determination of total aluminum and phosphate in aluminum phosphate (AlPO 4 ) adjuvanted vaccine samples using solution 27 Al and 31 P nuclear magnetic resonance (NMR) spectroscopy. External standard calibrations of AlPO 4 solutions established excellent linearity in the range of 15–40 × 10 −3 M and additional studies determined the level of detection for both nuclei. A commercialized combination vaccine product (Quadracel®), along with several individual adsorbed antigen components used in the vaccine were employed as model systems for method development. The developed method is also capable of quantitating the free phosphate (i.e. the fraction not bound to AlPO 4 particles) in adjuvanted vaccines. This study is the first demonstration of a solution NMR method that is suitable for measuring total aluminum, and free and total phosphate concentrations in vaccine formulations consisting of antigen(s) adsorbed to aluminum adjuvant, in a single analytical workflow.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.357
Teacher spread0.337 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations13
Published2018
Admission routes2
Has abstractyes

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