Unconventional matrices such as faneras (hairs) in the detection of drugs of abuse for the purposes of forensic toxicological investigation

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Erika Gabriela Collaguazo Enriquez
María Eugenia Lucena de Ustáriz


Introduction: At present, hair has been used as an unconventional matrix for the identification of substances of abuse, taking into account its advantages and disadvantages, as well as the application of adequate collection and conservation methods, knowing that these do not require high demands compared to samples such as urine, blood and other biological fluids. Objective: To identify the usefulness of non-conventional matrices such as faneras (hairs) in the detection of drugs of abuse for the purposes of forensic toxicology research. Methodology: The research is of bibliographic design, with a descriptive level of cross section and mixed character in which the review of written or digitized documents in the scientific literature about unconventional matrices such as faneras (hairs) in the detection of drugs of abuse. Results: A meticulous analysis was carried out, using the investigations of various authors about the use of faneras (hairs) in the detection of substances of abuse for the purposes of forensic toxicology research. Conclusion: the utility of the non-conventional matrix (hair) lies in the main characteristics that it presents: easy collection, conservation, storage, non-invasive procedure, allows to identify long periods of substance use, as well as the limitations that it has, in the field of quantification of very low concentrations of the substances of abuse found in this biological sample, confirmation methods with high costs are applied there. Area of study: Criminalistics / Forensics. Specific area of study: Law-Criminalistics.


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Collaguazo Enriquez, E. G., & Lucena de Ustáriz , M. E. (2023). Unconventional matrices such as faneras (hairs) in the detection of drugs of abuse for the purposes of forensic toxicological investigation. Ciencia Digital, 7(3), 25-37. https://doi.org/10.33262/cienciadigital.v7i3.2585


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