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Establishing chemical profiling for ecstasy tablets based on trace element levels and support vector machine

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Abstract

Ecstasy is an amphetamine-type substance that belongs to a popular group of illicit drugs known as “club drugs” whose consumption is rising in Brazil. The effects caused by this substance in the human organism are mainly psychological, including hallucinations, euphoria and other stimulant effects. The distribution of this drug is illegal, and effective strategies are required in order to detain its growth. One possible way to obtain useful information on ecstasy trafficking routes, sources of supply, clandestine laboratories and synthetic protocols is by its chemical components. In this paper, we present a data mining and predictive analysis for ecstasy tablets seized in two cities of São Paulo state (Brazil), Campinas and Ribeirão Preto, based on their chemical profile. We use the concentrations of 25 elements determined in the ecstasy samples by ICP-MS as our descriptive variables. We develop classification models based on support vector machines capable of predicting in which of the two cities an arbitrary ecstasy sample was most likely to have been seized. Our best model achieved a 81.59% prediction accuracy. The F-score measure shows that Se, Mo and Mg are the most significant elements that differentiate the samples from the two cities, and they alone are capable of yielding an SVM model which achieved the highest prediction accuracy.

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Acknowledgements

The authors are grateful to Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) for financial support.

Funding

This study was funded by São Paulo Research Foundation (FAPESP) and the National Council for Technological and Scientific Development (CNPq).

Author information

Authors and Affiliations

  1. Instituto de Informática, Universidade Federal de Goiás, Goiânia, Goiás, Brazil

    Camila Maione & Rommel M. Barbosa

  2. Laboratório de Toxicologia e Essencialidade de Metais, Depto. de Análises Clínicas, Toxicológicas e Bromatológicas, Faculdade de Ciências Farmacêuticas de Ribeirão Preto-USP, Ribeirão Prêto, São Paulo, Brazil

    Vanessa C. de Oliveira Souza & Fernando Barbosa Jr.

  3. Laboratório de Química e Toxicologia Forense, Instituto de Criminalística de São Paulo, São Paulo, São Paulo, Brazil

    Loraine R. Togni & Jose L. da Costa

  4. Centro de Controle de Intoxicação, Universidade de Campinas, Campinas, São Paulo, Brazil

    Jose L. da Costa

  5. Department of Chemistry, University of Central Florida, Orlando, FL, USA

    Andres D. Campiglia

  6. Center for Forensic Science, University of Central Florida, Orlando, FL, USA

    Andres D. Campiglia

Authors
  1. Camila Maione
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  2. Vanessa C. de Oliveira Souza
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  3. Loraine R. Togni
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  4. Jose L. da Costa
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  5. Andres D. Campiglia
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  6. Fernando Barbosa Jr.
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  7. Rommel M. Barbosa
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Corresponding author

Correspondence to Rommel M. Barbosa.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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Maione, C., Souza, V.C.O., Togni, L.R. et al. Establishing chemical profiling for ecstasy tablets based on trace element levels and support vector machine. Neural Comput & Applic 30, 947–955 (2018). https://doi.org/10.1007/s00521-016-2736-3

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  • DOI: https://doi.org/10.1007/s00521-016-2736-3

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