Concordant spatio-temporal patterns of brain activation in zebrafish exposed to compounds with similar pharmacodynamics or with similar seizurogenic potential.

Abstract

Abstract Drug development is a highly resource intensive process that uses large numbers of animals for assessing the safety and efficacy of drugs prior to clinical testing. Improving the efficiency of drug development in terms of financial expenditure and number of animals used is therefore of utmost concern, not only to industry, but also to animal welfare organisations such as the NC3Rs. Poor efficiency in drug development largely stems from drug attrition, particularly attrition in the latter stages of the testing due to the large amount of resources expended at the point of failure. It is therefore imperative that deleterious off-target effects are identified as early as possible. However, typically, identification of seizure as a side-effect of drugs is performed in the later stages of development due to the highly intensive and low-throughput nature of seizure assays. At which point, if a compound fails, a large amount of resources have been squandered. There therefore exists a need for high-throughput and relatively inexpensive seizure liability assays that can be used early in drug development to prevent compounds destined for failure undergoing unnecessary resource intensive testing. In this thesis we propose a refined approach using non-invasive imaging techniques in non-protected life stage zebrafish as a method for the detection of seizurogenic compounds early in drug development. In addition, we highlight its utility for elucidating the pharmacodynamics of compounds. In this study, a transgenic zebrafish line containing a GCaMP6s calcium sensor under the control of the pan-neuronal promoter elavl3 was used for functional profiling of compounds with varied pharmacologies. Light sheet microscopy was used to record fluorescent activity in three spatial dimensions over time (4-dimensions) from the zebrafish brain after exposure to forty-three different compounds with varied pharmacodynamics and seizure liability profiles. Hierarchical clustering was employed in order to assess if compounds with seizurogenic activity or similar pharmacodynamics elicited specific functional brain activity. It was found that compounds with dopaminergic and serotonergic mechanisms of action elicited highly specific and similar brain activity patterns and that non-seizurogenic drugs also clustered separately from seizurogenic ones. Subsequent analyses, focussed on the utilisation of machine learning techniques, developing a model that could be used to discriminate between compounds with and without potentially seizurogenic effects. It is clear, from the analyses presented here, that drugs do in fact elicit specific brain patterns in zebrafish and that these brain patterns are effectively detected using light sheet microscopy. This system is highly applicable for use within the drug industry and even in its relatively preliminary stages provided an accurate method of discriminating between compounds based on their physiological effects in zebrafish.