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Systematic Comparison of Pre-Treatment Parameters in Forensic Hair Analysis and Investigating Hair-Drug Interactions

NCJ Number
303406
Date Published
2020
Length
166 pages
Annotation

This is the dissertation report on the methodology and findings of research that addressed persistent interpretive challenges in the analysis of human head hair for the detection of abused substances.

Abstract

This report notes that these challenges are caused by a lack of standardization in analytical approaches and poor understanding of the biases that result from physicochemical interactions between major hair components (for example, melanin) and drug of abuse. Some of the uncertainty regarding optimal techniques for the pre-treatment of hair specimens results from the unknown nature of the interaction between drugs and hair components, particularly melanin. A second focus of this study was interactions with selected drugs and melanin by UV/Visible spectroscopy. Another source of uncertainty in hair analysis to detect drugs is the lack of standardization in the analytical approach to hair testing. As a complex solid sample matrix, hair requires pre-treatment measures that include decontamination, homogenization, and extraction to remove a drug from the hair component to enable analysis. Thus, a focus of this research was to conduct a comprehensive comparison of the efficacy of decontamination and extraction variables through the statistical design of experiments. The project found that a minimum of four consecutive washes were necessary for the decontamination of hair, and solvent swelling of the matrix resulted in the highest extraction of the five analytes studied. The other major finding of this research was that the interaction between eumelanin and drugs is a result of ionic interactions and van der Waals forces. Also, association constants between drugs and eumelanin were found to provide additional insight regarding the strength of interactions between drugs with different physicochemical properties and eumelanin. 29 tables, 27 figures, and a listing of project-related publications

Date Published: January 1, 2020