By Topic

Multivariate Data Analysis for Drug Identification Using Energy-Dispersive X-Ray Diffraction

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

6 Author(s)
Cook, E.J. ; Dept. of Med. Phys. & Bioeng., Univ. Coll. London, London ; Pani, S. ; George, L. ; Hardwick, S.
more authors

Preliminary studies have shown the effectiveness of multivariate analysis (MVA) for drug identification from energy-dispersive X-ray diffraction patterns. A statistical model to predict drug content from the diffraction profile of a sample of mixed composition was developed by applying MVA to both experimental and simulated data. Separate data-sets were used for building and testing the models. Both experimental and simulated data were used and the MVA predictions compared. Experimental data included diffraction patterns from small (5 mm diameter) drug samples with various cutting agents, acquired with a HPGe detector; simulated data included diffraction patterns of samples including materials simulating drugs (i.e., materials featuring sharp diffraction peaks in the relevant momentum transfer range) and typical packaging materials. Both a HPGe detector (energy resolution 0.7 keV at 59.5 keV) and a CZT detector (energy resolution 4 keV at all energies) were simulated. MVA was used to predict the drug content. In all cases different statistics were applied to assess the detection limits of the models. Multivariate analysis has proved effective in both identifying the presence of a drug and its concentration. Due to the large contribution to peak broadening given by angular resolution, no significant decrease in accuracy has been found when using CZT with respect to HPGe data.

Published in:

Nuclear Science, IEEE Transactions on  (Volume:56 ,  Issue: 3 )