Evidence map›Paper›PMID 29110294›Full record

ArticleAAPS PharmSciTech2018

Chemometric Methods to Quantify 1D and 2D NMR Spectral Differences Among Similar Protein Therapeutics.

Kang Chen, Junyong Park, Feng Li, Sharadrao M Patil, David A Keire

Abstract read
In one paragraph

Article in AAPS PharmSciTech, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Structural Relationships to Efficacy for Prazole-Derived Antivirals.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Selective suppression of excipient signals in 2DJournal of biomolecular NMR · 2018
    Article
  17. Article
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

5 authors.

Kang ChenDivision of Pharmaceutical Analysis, Office of Testing and Research, Office of Pharmaceutical Quality, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, 20993, USA. kang.chen@fda.hhs.gov.
Junyong ParkDepartment of Mathematics and Statistics, University of Maryland Baltimore County, Baltimore, Maryland, 21250, USA.
Feng LiDepartment of Mathematics and Statistics, University of Maryland Baltimore County, Baltimore, Maryland, 21250, USA.
Sharadrao M PatilDivision of Pharmaceutical Analysis, Office of Testing and Research, Office of Pharmaceutical Quality, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, 20993, USA.
David A KeireDivision of Pharmaceutical Analysis, Office of Testing and Research, Office of Pharmaceutical Quality, Center for Drug Evaluation and Research, US Food and Drug Administration, St. Louis, Missouri, 63110, USA.

Funding

Intramural FDA HHS FD999999
6 · The paper itself

Abstract

NMR spectroscopy is an emerging analytical tool for measuring complex drug product qualities, e.g., protein higher order structure (HOS) or heparin chemical composition. Most drug NMR spectra have been visually analyzed; however, NMR spectra are inherently quantitative and multivariate and thus suitable for chemometric analysis. Therefore, quantitative measurements derived from chemometric comparisons between spectra could be a key step in establishing acceptance criteria for a new generic drug or a new batch after manufacture change. To measure the capability of chemometric methods to differentiate comparator NMR spectra, we calculated inter-spectra difference metrics on 1D/2D spectra of two insulin drugs, Humulin R® and Novolin R®, from different manufacturers. Both insulin drugs have an identical drug substance but differ in formulation. Chemometric methods (i.e., principal component analysis (PCA), 3-way Tucker3 or graph invariant (GI)) were performed to calculate Mahalanobis distance (D

Indexed as

InsulinInsulin, Regular, HumanMagnetic Resonance SpectroscopyPrincipal Component AnalysisProteinsInsulinInsulin, Regular, HumanProteinsdistance ratiograph invariantMahalanobis distancePCATucker3

Identifiers

PMID29110294
PMCPMC6995279

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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.