In vitro studies of drug transformations: application to forensic toxicology

The forensic toxicologist faces challenges in the detection of drugs and poisons in biological samples due to transformations which occur both during life and after death. For example, changes can result from drug metabolism during life or from the use of formalin solution for post mortem embalming purposes. The former requires the identification of drug metabolites and the latter the identification of chemical reaction products in order to know which substances had been administered. The work described in this thesis was aimed at providing ways of tackling these challenges and was divided into two parts. Part 1 investigated the use of in vitro drug metabolism by human liver microsomes (HLM) to obtain information on drug metabolites and Part 2 investigated the chemical reactions of drugs and a carbamate pesticide with formalin solution and formalin-blood. The initial aim of part I was to develop an in vitro metabolism method using HLM, based on a literature review of previous studies of this type. MDMA was chosen as a model compound to develop the HLM method because its metabolism was known and standards of its metabolites were commercially available. In addition, a sensitive and selective method was developed for the identification and quantitation of hydrophilic phase I drug metabolites using LC/MS/MS with a conventional reverse-phase (C18) column. In order to obtain suitable retention factors for polar drug metabolites on this column, acetyl derivatives were evaluated for converting the metabolites to more lipophilic compounds and an optimal separation system was developed. Acetate derivatives were found to be stable in the HPLC mobile phase and to provide good chromatographic separation of the target analytes. In vitro metabolism of MDMA and, subsequently, of other drugs involved incubation of 4 µg drug substance in pH 7.4 buffer with an NADPH generating system (NGS) at 37oC for 90 min with addition of more NGS after 30 min. The reaction was stopped at 90 min by the addition of acetonitrile before extraction of the metabolites. Acetate derivatives of MDMA metabolites were identified by LC/MS/MS using multiple reaction monitoring (MRM). Three phase I metabolites (both major and minor metabolites) of MDMA were detected in HLM samples. 3,4-dihydroxy-methamphetamine and 4-hydroxy-3-methoxymethamphetamine were found to be major metabolites of MDMA whereas 3,4-methylenedioxyamphetamine was found to be a minor metabolite. Subsequently, ten MDMA positive urines were analysed to compare the metabolite patterns with those produced by HLM. An LC/MS method for MDMA and its metabolites in urine samples was developed and validated. The method demonstrated good linearity, accuracy and precision and insignificant matrix effects, with limits of quantitation of 0.025 µg/ml. Moreover, derivatives of MDMA and its metabolites were quantified in all 10 positive human urine samples. The urine metabolite pattern was found to be similar to that from HLM. The second aim of Part 1 was to use the HLM system to study the metabolism of some new psychoactive substances, whose misuse worldwide has necessitated the development of analytical methods for these drugs in biological specimens. Methylone and butylone were selected as representative cathinones and para-methoxyamphetamine (PMA) was chosen as a representative ring-substituted amphetamine, because of the involvement of these drugs in recent drug-related deaths, because of a relative lack of information on their metabolism, and because reference standards of their metabolites were not commercially available. An LC/MS/MS method for the analysis of methylone, butylone, PMA and their metabolites was developed. Three phase I metabolites of methylone and butylone were detected in HLM samples. Ketone reduction to β-OH metabolites and demethylenation to dihydroxy-metabolites were found to be major phase I metabolic pathways of butylone and methylone whereas N-demethylation to nor-methylone and nor-butylone were found to be minor pathways. Also, demethylation to para-hydroxyamphetamine was found to be a major phase I metabolic pathway of PMA whereas β-hydroxylation to β-OH-PMA was found to be a minor pathway. Formaldehyde is used for embalming, to reduce decomposition and preserve cadavers, especially in tropical countries such as Thailand. Drugs present in the body can be exposed to formaldehyde resulting in decreasing concentrations of the original compounds and production of new substances. The aim of part II of the study was to evaluate the in vitro reactions of formaldehyde with selected drug groups including amphetamines (amphetamine, methamphetamine and MDMA), benzodiazepines (alprazolam and diazepam), opiates (morphine, hydromorphone, codeine and hydrocodone) and with a carbamate insecticide (carbosulfan). The study would identify degradation products to serve as markers for the parent compounds when these were no longer detectable. Drugs standards were spiked in 10% formalin solution and 10% formalin blood. Water and whole blood without formalin were used for controls. Samples were analysed by LC/MS/MS at different times from the start, over periods of up to 30 days. Amphetamine, methamphetamine and MDMA were found to rapidly convert to methamphetamine, DMA and MDDMA respectively, in both formalin solution and formalin blood, confirming the Eschweiler-Clarke reaction between amine-containing compounds and formaldehyde. Alprazolam was found to be unstable whereas diazepam was found to be stable in both formalin solution and water. Both were found to hydrolyse in formalin solution and to give open-ring alprazolam and open-ring diazepam. Other alprazolam conversion products attached to paraformaldehyde were detected in both formalin solution and formalin blood. Morphine and codeine were found to be more stable than hydromorphone and hydrocodone in formalin solution. Conversion products of hydromorphone and hydrocodone attached to paraformaldehyde were tentatively identified in formalin solution. Moreover, hydrocodone and hydromorphone rapidly decreased within 24 h in formalin blood and could not be detected after 7 days. Carbosulfan was found to be unstable in formalin solution and was rapidly hydrolysed within 24 h, whereas in water it was stable up to 48 h. Carbofuran was the major degradation product, plus smaller amounts of other products, 3-ketocarbofuran and 3-hydrocarbofuran. By contrast, carbosulfan slowly hydrolysed in formalin-blood and was still detected after 15 days. It was concluded that HLM provide a useful tool for human drug metabolism studies when ethical considerations preclude their controlled administration to humans. The use of chemical derivatisation for hydrophilic compounds such as polar drug metabolites for analysis by LC/MS/MS with a conventional C18 column is effective and inexpensive, and suitable for routine use in the identification and quantitation of drugs and their metabolites. The detection of parent drugs and their metabolites or conversion and decomposition products is potentially very useful for the interpretation of cases in forensic toxicology, especially when the original compounds cannot be observed.

Applied evolution: An integrated approach to studying life history traits in response to drug selection

The use of chemical control measures to reduce the impact of parasite and pest species has frequently resulted in the development of resistance. Thus, resistance management has become a key concern in human and veterinary medicine, and in agricultural production. Although it is known that factors such as gene flow between susceptible and resistant populations, drug type, application methods, and costs of resistance can affect the rate of resistance evolution, less is known about the impacts of density-dependent eco-evolutionary processes that could be altered by drug-induced mortality. The overall aim of this thesis was to take an experimental evolution approach to assess how life history traits respond to drug selection, using a free-living dioecious worm (Caenorhabditis remanei) as a model. In Chapter 2, I defined the relationship between C. remanei survival and Ivermectin dose over a range of concentrations, in order to control the intensity of selection used in the selection experiment described in Chapter 4. The dose-response data were also used to appraise curve-fitting methods, using Akaike Information Criterion (AIC) model selection to compare a series of nonlinear models. The type of model fitted to the dose response data had a significant effect on the estimates of LD50 and LD99, suggesting that failure to fit an appropriate model could give misleading estimates of resistance status. In addition, simulated data were used to establish that a potential cost of resistance could be predicted by comparing survival at the upper asymptote of dose-response curves for resistant and susceptible populations, even when differences were as low as 4%. This approach to dose-response modeling ensures that the maximum amount of useful information relating to resistance is gathered in one study. In Chapter 3, I asked how simulations could be used to inform important design choices used in selection experiments. Specifically, I focused on the effects of both within- and between-line variation on estimated power, when detecting small, medium and large effect sizes. Using mixed-effect models on simulated data, I demonstrated that commonly used designs with realistic levels of variation could be underpowered for substantial effect sizes. Thus, use of simulation-based power analysis provides an effective way to avoid under or overpowering a study designs incorporating variation due to random effects. In Chapter 4, I 3 investigated how Ivermectin dosage and changes in population density affect the rate of resistance evolution. I exposed replicate lines of C. remanei to two doses of Ivermectin (high and low) to assess relative survival of lines selected in drug-treated environments compared to untreated controls over 10 generations. Additionally, I maintained lines where mortality was imposed randomly to control for differences in density between drug treatments and to distinguish between the evolutionary consequences of drug treatment versus ecological processes affected by changes in density-dependent feedback. Intriguingly, both drug-selected and random-mortality lines showed an increase in survivorship when challenged with Ivermectin; the magnitude of this increase varied with the intensity of selection and life-history stage. The results suggest that interactions between density-dependent processes and life history may mediate evolved changes in susceptibility to control measures, which could result in misleading conclusions about the evolution of heritable resistance following drug treatment. In Chapter 5, I investigated whether the apparent changes in drug susceptibility found in Chapter 4 were related to evolved changes in life-history of C. remanei populations after selection in drug-treated and random-mortality environments. Rapid passage of lines in the drug-free environment had no effect on the measured life-history traits. In the drug-free environment, adult size and fecundity of drug-selected lines increased compared to the controls but drug selection did not affect lifespan. In the treated environment, drug-selected lines showed increased lifespan and fecundity relative to controls. Adult size of randomly culled lines responded in a similar way to drug-selected lines in the drug-free environment, but no change in fecundity or lifespan was observed in either environment. The results suggest that life histories of nematodes can respond to selection as a result of the application of control measures. Failure to take these responses into account when applying control measures could result in adverse outcomes, such as larger and more fecund parasites, as well as over-estimation of the development of genetically controlled resistance. In conclusion, my thesis shows that there may be a complex relationship between drug selection, density-dependent regulatory processes and life history of populations challenged with control measures. This relationship could have implications for how resistance is monitored and managed if life histories of parasitic species show such eco-evolutionary responses to drug application.