Mycobacteria cause a range of disease including tuberculosis (TB) in both humans and animals. TB is responsible for almost 2 million deaths per year in people, and is responsible for huge economic costs worldwide in agriculture. The reliable diagnosis of TB is seen as the cornerstone to every approach to controlling and eliminating these infections, however there a large gaps in research currently being performed. Thus, there is a great need for novel methods of detecting TB. Current diagnostics are either insensitive or ill-suited to the needs of clinicians/researchers. Diagnostics need to be cheap, robust, require minimal training, usable in a low resource setting, have a high sensitivity and specificity and ideally can detect antimicrobial resistance.
With the Bloomsbury SET fellowship I will develop a novel diagnostic platform technology that has the ability address all these needs, with the potential to revolutionise the detection of TB and other pathogens in humans and animals. Pilot data generated will lead to a patent filing and further development of the technology to appeal to consumer needs, both in the human and veterinary field.