Tackling Poor Specificity of Cocaine Color Tests by Electrochemical Strategies

Jong, Mats de; Florea, Anca; Eliaerts, Joy; Durme, Filip Van; Samyn, Nele; Wael, Karolien De

doi:10.1021/acs.analchem.8b00876

Cited by 42 publications

(72 citation statements)

References 17 publications

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“…10 A well-known limitation of these cobalt(II)thiocyanate-based tests is their false-positive (FP) response to several common adulterants such as levamisole and lidocaine. 11 This is a major drawback as levamisole is one of the most frequently used cutting agents, present in more than 40% of seized cocaine samples. 12 It is therefore not unlikely to encounter pure levamisole, or…”

Section: Introductionmentioning

confidence: 99%

“…16 Also, electrochemical tests that can overcome the specificity issues of the Scott test have been developed. 11,17 However, both electrochemical tests and ATR-FT-IR spectroscopy still require touching and handling of sample material. Raman spectroscopy and near-infrared (NIR) spectroscopy are two techniques that can analyze through the packaging material without handling the sample and can be operated by minimally trained staff.…”

Section: Introductionmentioning

confidence: 99%

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Rapid and robust on‐scene detection of cocaine in street samples using a handheld near‐infrared spectrometer and machine learning algorithms

Kranenburg

Verduin

Weesepoel

et al. 2020

Drug Testing and Analysis

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On-scene drug detection is an increasingly significant challenge due to the fastchanging drug market as well as the risk of exposure to potent drug substances. Conventional colorimetric cocaine tests involve handling of the unknown material and are prone to false-positive reactions on common pharmaceuticals used as cutting agents. This study demonstrates the novel application of 740-1070 nm small-wavelength-range near-infrared (NIR) spectroscopy to confidently detect cocaine in case samples. Multistage machine learning algorithms are used to exploit the limited spectral features and predict not only the presence of cocaine but also the concentration and sample composition. A model based on more than 10,000 spectra from case samples yielded 97% true-positive and 98% true-negative results. The practical applicability is shown in more than 100 case samples not included in the model design. One of the most exciting aspects of this on-scene approach is that the model can almost instantly adapt to changes in the illicit-drug market by updating metadata with results from subsequent confirmatory laboratory analyses. These results demonstrate that advanced machine learning strategies applied on limited-range NIR spectra from economic handheld sensors can be a valuable procedure for rapid on-site detection of illicit substances by investigating officers. In addition to forensics, this interesting approach could be beneficial for screening and classification applications in the pharmaceutical, food-safety, and environmental domains.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Rapid and robust on‐scene detection of cocaine in street samples using a handheld near‐infrared spectrometer and machine learning algorithms

Kranenburg

Verduin

Weesepoel

et al. 2020

Drug Testing and Analysis

View full text Add to dashboard Cite

show abstract

“…The complexation with the cobalt thiocyanate in the cocaine colorimetric test could also take place in the presence of other compounds, causing the test to turn blue, thus leading to a false positive result. Moreover the test is influenced by temperature and the color interpretation is subjective (De Jong et al, 2018b ). Therefore, (bio)sensing strategies in detecting drugs offer a clear advantage compared to colorimetric tests, with increased selectivity and comparable analysis time.…”

Section: Future Perspectivesmentioning

confidence: 99%

Tackling the Problem of Sensing Commonly Abused Drugs Through Nanomaterials and (Bio)Recognition Approaches

et al. 2020

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We summarize herein the literature in the last decade, involving the use of nanomaterials and various (bio)recognition elements, such as antibodies, aptamers and molecularly imprinted polymers, for the development of sensitive and selective (bio)sensors for illicit drugs with a focus on electrochemical transduction systems. The use and abuse of illicit drugs remains an increasing challenge for worldwide authorities and, therefore, it is important to have accurate methods to detect them in seized samples, biological fluids and wastewaters. They are recently classified as the latest group of “emerging pollutants,” as their consumption has increased tremendously in recent years. Nanomaterials, antibodies, aptamers and molecularly imprinted polymers have gained much attention over the last decade in the development of (bio)sensors for a myriad of applications. The applicability of these (nano)materials, functionalized or not, has significantly increased, and are therefore highly suitable for use in the detection of drugs. Lately, such functionalized nanoscale materials have assisted in the detection of illicit drugs fingerprints, providing large surface area, functional groups and unique properties that facilitate sensitive and selective sensing. The review discusses the types of commonly abused drugs and their toxicological implications, classification of functionalized nanomaterials (graphene, carbon nanotubes), their fabrication, and their application on real samples in different fields of forensic science. Biosensors for drugs of abuse from the last decade's literature are then exemplified. It also offers insights into the prospects and challenges of bringing the functionalized nanobased technology to the end user in the laboratories or in-field.

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“…For a substance such as cocaine, the most common presumptive test being used is the Scott color test. As can been seen in Table , the sensitivity and specificity of this test are 0.68, 0.75 respectively (de Jong et al, ), giving an LR for a positive result of 2.72 (Table ). As shown in the earlier examples, if we wish to assess the posterior probabilities provided by a specific test, we need to assign relevant, reliable prior probabilities (which could be informed by studies on prevalence) in the circumstances being examined.…”

Section: Introductionmentioning

confidence: 98%

“…Because of this risk of misleading inferences from negative results, the development of presumptive tests has concentrated on improving the sensitivity and specificity (and hence the magnitude of the LRs) of such tests. For example, an electrochemical test for the detection of cocaine has improved the sensitivity and specificity of cocaine detection to 0.93 and 0.86 respectively (de Jong et al, ) (Table ). This leads to an increased LR for positive detection (6.64 for the electrochemical test compared to 2.72 for the color test) and a decrease in the LR for a negative detection (0.08 for the electrochemical test compared to 0.43 for the color test).…”

Section: Introductionmentioning

confidence: 99%

Presumptive drug testing—The importance of considering prior probabilities

Maskell

Jackson

2020

WIREs Forensic Science

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Presumptive drug testing is commonly used in both the clinical and forensic fields to allow rapid identification of the presence and/or usage of drugs. Because the tests generally have a high sensitivity and specificity (often >90%), then a positive test result may be taken to mean there is a high probability that a targeted drug is present. This assumption is, however, incorrect. This paper demonstrates how, in order to assess the positive predictive value (PPV) of a test, it is necessary to take into account, along with the sensitivity and specificity of the test, the prevalence of the drug in the population being investigated. We demonstrate how an alternative, Bayesian approach to assessing the posterior probability of a drug being present mimics the conventional calculation of PPVs but, because a Bayesian approach requires case‐specific prior probabilities, the posterior probabilities are more meaningful than PPV in any one specific case. The effectiveness of presumptive test results in cases such as drink‐spiking, drug‐driving, testing of drugs during seizures and the confirmation of initial presumptive test results is explored. In order to exploit the potential of presumptive drug testing, it is important that the prevalence of the targeted drugs in relevant populations is understood but, more importantly, it is important to consider using a Bayesian approach in order to tailor results to the specific individual or drug batch being tested. This article is categorized under: Toxicology > Analytical Toxicology Jurisprudence and Regulatory Oversight > Expert Evidence and Narrative

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Tackling Poor Specificity of Cocaine Color Tests by Electrochemical Strategies

Cited by 42 publications

References 17 publications

Rapid and robust on‐scene detection of cocaine in street samples using a handheld near‐infrared spectrometer and machine learning algorithms

Rapid and robust on‐scene detection of cocaine in street samples using a handheld near‐infrared spectrometer and machine learning algorithms

Tackling the Problem of Sensing Commonly Abused Drugs Through Nanomaterials and (Bio)Recognition Approaches

Presumptive drug testing—The importance of considering prior probabilities

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