High-throughput Behavioural Phenotyping to Identify Small Molecule Biologics for the Treatment of Neurological Disorders

I aim to develop a high-throughput in vivo screening platform to identify small molecule biologics capable of treating epilepsy. Using automated quantitative phenotyping, I will explore how the diverse chemo-structural space covered by Affimer libraries can modulate the behaviour of a whole-organism model (C. elegans). Affimers are renewable binding agents that target protein domains in a highly specific manner and can augment cellular processes. My technology will enable the targeted, and comprehensive, screening of libraries to identify Affimers that beneficially alter neurological processes to rescue aberrant behavioural phenotypes. I will generate a panel of C. elegans mutants containing patient-specific variants in a gene associated with the onset of a severe form of epilepsy in humans. These strains will constitute “patient avatars” of epilepsy. The distance between the “healthy” wild-type and patient avatars treated with different Affimers in multi-dimensional phenospace can be readily quantified and used as a measure of strain fitness. This method also permits the detection of side effects during screening to enhance the clinical translatability of my results. I have designed my technology to be universally applicable for investigating additional patient avatars, meaning the success of this project will be useful for the study of many neurological disorders.