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Measurement and modellingof pharmaceutical bioconcentration in an aquatic invertebrate, Gammarus pulex.

Student thesis: Doctoral ThesisDoctor of Philosophy

The aim of this work was to understand the bioconcentration potential of pharmaceuticals in a freshwater invertebrate. The novelty of this work lies in several parts of which the most important was that a computational model was developed to successfully predict bioconcentration in invertebrates, which has not been achieved previously. For the first time, a developed analytical method using liquid chromatography tandem mass spectrometry (LC-MS/MS) was used to determine the occurrence of pharmaceuticals in Gammarus pulex across several tributaries of the River Thames (London, UK). The occurrence reached low level ng g-1 concentrations and indicated that further experiments were needed to determine the accumulation potential.
Toxicokinetic exposures were performed to characterise the bioconcentration potential of 16 pharmaceuticals. The determined bioconcentration factors (BCFs) remained below regulatory thresholds indicative of bioaccumulation, which contrasted field-derived bioaccumulation factors that would have triggered regulatory guidelines. However, the standardised models employed for kinetic BCF estimation were evaluated and it was found that model assumptions concerning the uptake rate constant were not reliable, leading to extremely important implications for regulatory bodies. In addition, the developed LC-MS/MS method determined phase I and phase II metabolites in G. pulex, indicating that these organisms are capable of extensive biotransformation of pharmaceuticals.
To further understand uptake mechanisms such as passive diffusion, a modelling approach using artificial neural networks were developed to characterise the uptake of pharmaceuticals onto passive sampling devices. No previous investigations have aimed to predict uptake onto polar organic chemical integrative sampler devices and this work represented the first of its kind. The passive sampling models demonstrated good predictive accuracy at a fraction of the cost and time required by experimental measurements. Furthermore, the modelling gave mechanistic insight into molecular descriptors that were related to uptake onto passive samplers. The modelling approach was extended to predict bioconcentration of pharmaceuticals in fish and G. pulex using data from the literature and data determined from the toxicokinetic experiments presented here. Interestingly, the fish-based model could not be used to predict the invertebrate data. This indicated that either the class of compounds (pharmaceuticals) or the fish-to-invertebrate bioconcentration data could not be cross predicted. Thus, a standalone model was developed for the invertebrates and showed good predictive accuracy for this species. Overall, the work presented herein has achieved novel impact to address the lack of knowledge concerning bioconcentration in invertebrates.
Original languageEnglish
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Award date2017

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