TY - GEN
T1 - Smartphone-based thin layer chromatography for the discrimination of falsified medicines
AU - Yu, Hojeong
AU - Le, Huy
AU - Lumetta, Steven
AU - Cunningham, Brian T.
AU - Kaale, Eliangiringa
AU - Layloff, Thomas
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/1/5
Y1 - 2016/1/5
N2 - Identification of counterfeit and substandard drugs, which pose severe risks to patient safety is increasingly important, as inauthentic drugs become more commonplace in developing parts of the world. Though thin layer chromatography (TLC) performed with laboratory-based instruments enables accurate analysis of suspect medicines, there is tremendous interest in development of an inexpensive mobile platform that would broaden the applicability of TLC to remote pharmacies and clinics that presently do not have access to laboratory analysis. In this work, we demonstrate identification and characterization of pharmaceutical products via TLC using a custom cradle that interfaces with a smartphone. A UV lamp integrated within the cradle illuminates a TLC plate loaded with calibration standards and an aliquot of a drug of unknown concentration. Phosphorescence from the plate surface excited by UV light reveals principal spots. Two independent image processing approaches were developed to enable image processing to be performed locally with the smartphone processor, or remotely by a server running MatLab routines on uploaded images. Both approaches report the intensity and travel distance of spots within a TLC plate. The system is able to discern 5% medicine concentration differences and to deliver analytical results that are identical to those obtained by a laboratory TLC densitometer.
AB - Identification of counterfeit and substandard drugs, which pose severe risks to patient safety is increasingly important, as inauthentic drugs become more commonplace in developing parts of the world. Though thin layer chromatography (TLC) performed with laboratory-based instruments enables accurate analysis of suspect medicines, there is tremendous interest in development of an inexpensive mobile platform that would broaden the applicability of TLC to remote pharmacies and clinics that presently do not have access to laboratory analysis. In this work, we demonstrate identification and characterization of pharmaceutical products via TLC using a custom cradle that interfaces with a smartphone. A UV lamp integrated within the cradle illuminates a TLC plate loaded with calibration standards and an aliquot of a drug of unknown concentration. Phosphorescence from the plate surface excited by UV light reveals principal spots. Two independent image processing approaches were developed to enable image processing to be performed locally with the smartphone processor, or remotely by a server running MatLab routines on uploaded images. Both approaches report the intensity and travel distance of spots within a TLC plate. The system is able to discern 5% medicine concentration differences and to deliver analytical results that are identical to those obtained by a laboratory TLC densitometer.
KW - falsified medicine detection
KW - pharmaceutical compound analysis
KW - smartphone sensing
KW - thin layer chromatography
UR - http://www.scopus.com/inward/record.url?scp=85010991393&partnerID=8YFLogxK
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U2 - 10.1109/ICSENS.2016.7808847
DO - 10.1109/ICSENS.2016.7808847
M3 - Conference contribution
AN - SCOPUS:85010991393
T3 - Proceedings of IEEE Sensors
BT - IEEE Sensors, SENSORS 2016 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 15th IEEE Sensors Conference, SENSORS 2016
Y2 - 30 October 2016 through 2 November 2016
ER -