Skip to main content
padlock icon - secure page this page is secure

Detection of Drug Active Ingredients by Chemometric Processing of Solid-State NMR Spectrometry Data—The Case of Acetaminophen

Buy Article:

$45.00 + tax (Refund Policy)

This paper presents a preliminary study in building discriminant models from solid-state NMR spectrometry data to detect the presence of acetaminophen in over-the-counter pharmaceutical formulations. The dataset, containing 11 spectra of pure substances and 21 spectra of various formulations, was processed by partial least squares discriminant analysis (PLS-DA). The model found coped with the discrimination, and its quality parameters were acceptable. It was found that standard normal variate preprocessing had almost no influence on unsupervised investigation of the dataset. The influence of variable selection with the uninformative variable elimination by PLS method was studied, reducing the dataset from 7601 variables to around 300 informative variables, but not improving the model performance. The results showed the possibility to construct well-working PLS-DA models from such small datasets without a full experimental design.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics

Document Type: Research Article

Publication date: 01 May 2012

More about this publication?
  • The Journal of AOAC INTERNATIONAL publishes refereed papers and reviews in the fields of chemical, biological and toxicological analytical chemistry for the purpose of showcasing the most precise, accurate and sensitive methods for analysis of foods, food additives, supplements and contaminants, cosmetics, drugs, toxins, hazardous substances, pesticides, feeds, fertilizers and the environment available at that point in time. The scope of the Journal includes unpublished original research describing new analytical methods, techniques and applications; improved approaches to sampling, both in the field and the laboratory; better methods of preparing samples for analysis; collaborative studies substantiating the performance of a given method; statistical techniques for evaluating data. The Journal will also publish other articles of general interest to its audience, e.g., technical communications; cautionary notes; comments on techniques, apparatus, and reagents.
  • Information for Authors
  • Submit a Paper
  • Subscribe to this Title
  • Information for Advertisers
  • Journal Information
  • Masthead
  • Ingenta Connect is not responsible for the content or availability of external websites
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more