Detection of Counterfeit Medicines Using Hyperspectral Sensing

2020 ◽  
Author(s):  
Sujit R Shinde ◽  
Karan Bhavsar ◽  
Sanjay Kimbahune ◽  
Sundeep Khandelwal ◽  
Avik Ghose ◽  
...  
Keyword(s):  
Counterfeit Medicines ◽  
Hyperspectral Sensing

scholarly journals Proof-of-Concept of Detection of Counterfeit Medicine through Polymeric Materials Analysis of Plastics Packaging

Polymers ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 2185
Author(s):  
Mohammad Salim ◽  
Riyanto Teguh Widodo ◽  
Mohamed Ibrahim Noordin
Keyword(s):  
Polymeric Materials ◽  
Proof Of Concept ◽  
Scanning Calorimetry ◽  
Counterfeit Drug ◽  
Drug Products ◽  
Counterfeit Medicines ◽  
Counterfeit Medicine ◽  
Counterfeit Pharmaceuticals ◽  
Purge Gas ◽  
Sample Set

The detection of counterfeit pharmaceuticals is always a major challenge, but the early detection of counterfeit medicine in a country will reduce the fatal risk among consumers. Technically, fast laboratory testing is vital to develop an effective surveillance and monitoring system of counterfeit medicines. This study proposed the combination of Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) and Differential Scanning Calorimetry (DSC) for the quick detection of counterfeit medicines, through the polymer analysis of blister packaging materials. A sample set containing three sets of original and counterfeit medicine was analyzed using ATR-FTIR and DSC, while the spectra from ATR-FTIR were employed as a fingerprint for the polymer characterization. Intending to analyze the polymeric material of each sample, DSC was set at a heating rate of 10 °C min−l and within a temperature range of 0- 400 °C, with nitrogen as a purge gas at a flow rate of 20 ml min−an. The ATR-FTIR spectra revealed the chemical characteristics of the plastic packaging of fake and original medicines. Further analysis of the counterfeit medicine’s packaging with DSC exhibited a distinct difference from the original due to the composition of polymers in the packaging material used. Overall, this study confirmed that the rapid analysis of polymeric materials through ATR-FTIR and comparing DSC thermograms of the plastic in their packaging effectively distinguished counterfeit drug products.

scholarly journals The Deviation between Dairy Cow Metabolizable Energy Requirements and Pasture Supply on a Dairy Farm Using Proximal Hyperspectral Sensing

Agriculture ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 240
Author(s):  
Federico Duranovich ◽  
Nicolás López-Villalobos ◽  
Nicola Shadbolt ◽  
Ina Draganova ◽  
Ian Yule ◽  
...  
Keyword(s):  
Milk Fat ◽  
Supply And Demand ◽  
Dairy Farm ◽  
Energy System ◽  
Metabolizable Energy ◽  
Feeding Strategies ◽  
Canopy Reflectance ◽  
Estimate Variance ◽  
Hyperspectral Sensing ◽  
Daily Total

This study aimed at determining the extent to which the deviation of daily total metabolizable energy (MEt) requirements of individual cows from the metabolizable energy (ME) supplied per cow (DME) varied throughout the production season in a pasture-based dairy farm using proximal hyperspectral sensing (PHS). Herd tests, milk production, herbage and feed allocation data were collected during the 2016–2017 and 2017–2018 production seasons at Dairy 1, Massey University, New Zealand. Herbage ME was determined from canopy reflectance acquired using PHS. Orthogonal polynomials were used to model lactation curves for yields of milk, fat, protein and live weights of cows. Daily dietary ME supplied per cow to the herd and ME requirements of cows were calculated using the Agricultural Food and Research Council (AFRC) energy system of 1993. A linear model including the random effects of breed and cow was used to estimate variance components for DME. Daily herd MEt estimated requirements oscillated between a fifth above or below the ME supplied throughout the production seasons. DME was mostly explained by observations made within a cow rather than between cows or breeds. Having daily estimates of individual cow requirements for MEt in addition to ME dietary supply can potentially contribute to achieving a more precise fit between supply and demand for feed in a pasture-based dairy farm by devising feeding strategies aimed at reducing DME.

Counterfeit medicines as global treat

2010 ◽  
Vol 12 (3,4) ◽  
pp. 179-192
Author(s):  
Maria Dolores Cabezas
Keyword(s):  
Counterfeit Medicines

scholarly journals Contact Reflectance Spectroscopy for Rapid, Accurate, and Nondestructive Phytophthora infestans Clonal Lineage Discrimination

2020 ◽  
Vol 110 (4) ◽  
pp. 851-862 ◽  
Author(s):  
Kaitlin M. Gold ◽  
Philip A. Townsend ◽  
Eric R. Larson ◽  
Ittai Herrmann ◽  
Amanda J. Gevens
Keyword(s):  
Phytophthora Infestans ◽  
Time Course ◽  
The United States ◽  
Leaf Mass Per Area ◽  
Clonal Lineage ◽  
Laboratory Equipment ◽  
Lineage Differentiation ◽  
Potato Foliage ◽  
Shortwave Infrared ◽  
Hyperspectral Sensing

Populations of Phytophthora infestans, the oomycete causal agent of potato late blight in the United States, are predominantly asexual, and isolates are characterized by clonal lineage or asexual descendants of a single genotype. Current tools for clonal lineage identification are time consuming and require laboratory equipment. We previously found that foliar spectroscopy can be used for high-accuracy pre- and postsymptomatic detection of P. infestans infections caused by clonal lineages US-08 and US-23. In this work, we found subtle but distinct differences in spectral responses of potato foliage infected by these clonal lineages in both growth-chamber time-course experiments (12- to 24-h intervals over 5 days) and naturally infected samples from commercial production fields. In both settings, we measured continuous visible to shortwave infrared reflectance (400 to 2,500 nm) on leaves using a portable spectrometer with contact probe. We consistently discriminated between infections caused by the two clonal lineages across all stages of disease progression using partial least squares (PLS) discriminant analysis, with total accuracies ranging from 88 to 98%. Three-class random forest differentiation between control, US-08, and US-23 yielded total discrimination accuracy ranging from 68 to 76%. Differences were greatest during presymptomatic infection stages and progressed toward uniformity as symptoms advanced. Using PLS-regression trait models, we found that total phenolics, sugar, and leaf mass per area were different between lineages. Shortwave infrared wavelengths (>1,100 nm) were important for clonal lineage differentiation. This work provides a foundation for future use of hyperspectral sensing as a nondestructive tool for pathovar differentiation.

scholarly journals An Investigation into the Quality of Medicines in Yangon, Myanmar

Pharmacy ◽  
2018 ◽  
Vol 6 (3) ◽  
pp. 96 ◽  
Author(s):  
Md. Islam ◽  
Naoko Yoshida ◽  
Kazuko Kimura ◽  
Chisana Uwatoko ◽  
Mohammad Rahman ◽  
...  
Keyword(s):  
Poor Quality ◽  
Cefuroxime Axetil ◽  
Quality Analysis ◽  
Content Uniformity ◽  
Counterfeit Medicines ◽  
Ceftriaxone Sodium ◽  
Substandard Medicines ◽  
Dissolution Tests ◽  
Microbial Assay

Many poor-quality medicines are supplied to patients mainly in developing countries. No systematic survey on counterfeit medicines has been conducted in Myanmar since 1999. The purpose of this study was to investigate the current situation of substandard or counterfeit medicines in Myanmar. Samples of oral medicines, cefuroxime axetil (CXM), donepezil hydrochloride (DN) and omeprazole (OM), and injections, ceftriaxone sodium (CTRX), and gentamicin sulfate (GM), were collected from pharmacies, hospitals, and wholesalers in Yangon, Myanmar in 2014. Authenticity and quality were verified. There were 221 (94%) foreign medicines among 235 collected samples. Five samples of GM and 1 DN sample were not registered with the Food and Drug Administration, Myanmar. In quality analysis, 36 samples out of 177 (20.3%) did not pass quantity tests, 27 samples out of 176 (15.3%) did not pass content uniformity tests, and 23 out of 128 samples (18.0%) did not pass dissolution tests. Three of the unregistered GM samples failed in both identification and microbial assay tests. Counterfeit GM is being sold in Yangon. Also, the quality of OM is a matter of concern. Poor-quality medicines were frequently found among the products of a few manufacturers. Regular surveys to monitor counterfeit and substandard medicines in Myanmar are recommended.

Estimating Water Stress in Plants Using Hyperspectral Sensing

2004 ◽  
Author(s):  
Carol L. Jones ◽  
Paul R. Weckler ◽  
Niels O. Maness ◽  
Marvin L. Stone ◽  
Roshani Jayasekara
Keyword(s):  
Water Stress ◽  
Hyperspectral Sensing

scholarly journals Sensing Technology Survey for Obstacle Detection in Vegetation

2021 ◽  
Vol 1 (3) ◽  
pp. 672-685
Author(s):  
Shreya Lohar ◽  
Lei Zhu ◽  
Stanley Young ◽  
Peter Graf ◽  
Michael Blanton
Keyword(s):  
Autonomous Vehicles ◽  
Weather Conditions ◽  
Climatic Conditions ◽  
Obstacle Detection ◽  
Agricultural Field ◽  
Thermal Camera ◽  
Agricultural Vehicles ◽  
Sensing Systems ◽  
Sensing Technology ◽  
Hyperspectral Sensing

This study reviews obstacle detection technologies in vegetation for autonomous vehicles or robots. Autonomous vehicles used in agriculture and as lawn mowers face many environmental obstacles that are difficult to recognize for the vehicle sensor. This review provides information on choosing appropriate sensors to detect obstacles through vegetation, based on experiments carried out in different agricultural fields. The experimental setup from the literature consists of sensors placed in front of obstacles, including a thermal camera; red, green, blue (RGB) camera; 360° camera; light detection and ranging (LiDAR); and radar. These sensors were used either in combination or single-handedly on agricultural vehicles to detect objects hidden inside the agricultural field. The thermal camera successfully detected hidden objects, such as barrels, human mannequins, and humans, as did LiDAR in one experiment. The RGB camera and stereo camera were less efficient at detecting hidden objects compared with protruding objects. Radar detects hidden objects easily but lacks resolution. Hyperspectral sensing systems can identify and classify objects, but they consume a lot of storage. To obtain clearer and more robust data of hidden objects in vegetation and extreme weather conditions, further experiments should be performed for various climatic conditions combining active and passive sensors.

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