TY - JOUR
T1 - Development of visual peak selection system based on multi-ISs normalization algorithm to apply to methamphetamine impurity profiling
AU - Lee, Hun Joo
AU - Han, Eunyoung
AU - Lee, Jaesin
AU - Chung, Heesun
AU - Min, Sung Gi
N1 - Funding Information:
This research was supported by grants 1315000560 from the National Forensic Service in 2013, Priority Research Centers Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2016R1A6A1A03007648), Republic of Korea. The authors would like to thank Jaewon LEE, in Cheminet and Sangeun LEE and Hyo-Jung Kim in Duksung Women’s University for their technical help and comments.
Publisher Copyright:
© 2016 Elsevier Ireland Ltd
PY - 2016/11/1
Y1 - 2016/11/1
N2 - The aim of this study is to improve resolution of impurity peaks using a newly devised normalization algorithm for multi-internal standards (ISs) and to describe a visual peak selection system (VPSS) for efficient support of impurity profiling. Drug trafficking routes, location of manufacture, or synthetic route can be identified from impurities in seized drugs. In the analysis of impurities, different chromatogram profiles are obtained from gas chromatography and used to examine similarities between drug samples. The data processing method using relative retention time (RRT) calculated by a single internal standard is not preferred when many internal standards are used and many chromatographic peaks present because of the risk of overlapping between peaks and difficulty in classifying impurities. In this study, impurities in methamphetamine (MA) were extracted by liquid–liquid extraction (LLE) method using ethylacetate containing 4 internal standards and analyzed by gas chromatography-flame ionization detection (GC-FID). The newly developed VPSS consists of an input module, a conversion module, and a detection module. The input module imports chromatograms collected from GC and performs preprocessing, which is converted with a normalization algorithm in the conversion module, and finally the detection module detects the impurities in MA samples using a visualized zoning user interface. The normalization algorithm in the conversion module was used to convert the raw data from GC-FID. The VPSS with the built-in normalization algorithm can effectively detect different impurities in samples even in complex matrices and has high resolution keeping the time sequence of chromatographic peaks the same as that of the RRT method. The system can widen a full range of chromatograms so that the peaks of impurities were better aligned for easy separation and classification. The resolution, accuracy, and speed of impurity profiling showed remarkable improvement.
AB - The aim of this study is to improve resolution of impurity peaks using a newly devised normalization algorithm for multi-internal standards (ISs) and to describe a visual peak selection system (VPSS) for efficient support of impurity profiling. Drug trafficking routes, location of manufacture, or synthetic route can be identified from impurities in seized drugs. In the analysis of impurities, different chromatogram profiles are obtained from gas chromatography and used to examine similarities between drug samples. The data processing method using relative retention time (RRT) calculated by a single internal standard is not preferred when many internal standards are used and many chromatographic peaks present because of the risk of overlapping between peaks and difficulty in classifying impurities. In this study, impurities in methamphetamine (MA) were extracted by liquid–liquid extraction (LLE) method using ethylacetate containing 4 internal standards and analyzed by gas chromatography-flame ionization detection (GC-FID). The newly developed VPSS consists of an input module, a conversion module, and a detection module. The input module imports chromatograms collected from GC and performs preprocessing, which is converted with a normalization algorithm in the conversion module, and finally the detection module detects the impurities in MA samples using a visualized zoning user interface. The normalization algorithm in the conversion module was used to convert the raw data from GC-FID. The VPSS with the built-in normalization algorithm can effectively detect different impurities in samples even in complex matrices and has high resolution keeping the time sequence of chromatographic peaks the same as that of the RRT method. The system can widen a full range of chromatograms so that the peaks of impurities were better aligned for easy separation and classification. The resolution, accuracy, and speed of impurity profiling showed remarkable improvement.
KW - Impurity profiling
KW - Methamphetamine
KW - Methamphetamine impurity profiling
KW - Normalization algorithm
UR - http://www.scopus.com/inward/record.url?scp=84990222462&partnerID=8YFLogxK
U2 - 10.1016/j.forsciint.2016.09.019
DO - 10.1016/j.forsciint.2016.09.019
M3 - Article
C2 - 27718476
AN - SCOPUS:84990222462
SN - 0379-0738
VL - 268
SP - 116
EP - 122
JO - Forensic Science International
JF - Forensic Science International
ER -