Assessing Hair Decontamination Protocols for Diazepam, Heroin, Cocaine and Δ9-Tetrahydrocannabinol by Statistical Design of Experiments

Prior to toxicological analysis, hair as a matrix requires pre-treatment measures including decontamination, homogenization and extraction. Decontamination is performed to differentiate between drug present from superficial deposition and drug incorporated from systemic distribution following ingestion. There are many methods for decontamination of hair samples, mostly developed by empirically using a traditional “one factor at a time” approach, in which one independent variable at a time is changed to observe the effect on the dependent variable. The goal of the present work was to compare the efficacy of decontamination protocols using statistical “design of experiments” (DoE), which allows for analysis of multiple variables and interactions within a single experiment. Decontamination parameters included identity of aqueous and organic wash solutions, number of sequential aqueous and organic washes, order of aqueous and organic washes, and duration of each wash. DoE studies were completed to identify optimal decontamination conditions for four abused drugs with varying physiochemical properties. For this purpose, drug-free human hair was externally contaminated with diazepam, heroin, cocaine or Δ9-tetrahydrocannabinol. Each analyte was found to have a unique set of decontamination conditions that were most effective. These included three 30-min washes with methanol followed by three with 1% sodium dodecyl sulfide for diazepam, three 30-s washes with dichloromethane followed by one with water for heroin, one 30-s wash with 1% sodium dodecyl sulfate followed by three with dichloromethane for cocaine and three 30-min washes with water followed by one with methanol for Δ9-tetrahydrocannabinol. The results provide proof-of-principle for a DoE approach to identify effective parameters for hair decontamination for a physicochemically diverse group of drugs. The major advantage of DoE is to elucidate combinations of parameters that result in effective removal of surface contamination, a goal that would be challenging to accomplish using a one factor at a time approach.