Over $3 Million Funding for Adaptive Diagnostics for Emerging Pandemic Threats in Regional Australia
17 November 2021 | 2 MINS
Dr Tim Inglis's group's successful bid for an NHMRC IDEAS grant will fund a three year project on Adaptive Diagnostics for Emerging Pathogenic Threats (ADEPT). The project aims to translate advances made during the COVID pandemic to provide more timely pathology laboratory support to regional communities when the next pandemic comes.
There is a dual use element to this project which seeks to exploit these advances to address regional capability gaps in diagnosing drug resistant bacterial infections. ADEPT includes data science, health economics and medical anthropology and will be driven in collaboration with Prof Mark Reynolds of the UWA School of Physics, Mathematics and Computing, and Prof Suzanne Robinson of the Curtin University School of Population Health.
As the COVID pandemic has yet to reach its end, the biggest risk to this project is disruption from a further surge in cases as the project gets under way. Fortunately, a key to the project design is close collaboration with PathWest Laboratory Medicine, who will continue their service even if our university campuses have to shut. There are several innovative laboratory technologies that will be put through their paces in new pathology lab settings, which may present organisational and logistic challenges not normally seen in single centre research projects. Another important risk is the regulatory burden associated with novel diagnostic technologies.
“ADEPT is the next step in a journey to bridge the gap between the infection diagnostic services concentrated in the Perth Metro area, and the rest of the State. Catching up with our diagnostic support for regional, rural and remote communities is something we had to do in a hurry when COVID first arrived here. Turning some of the lessons learned into a broader benefit to regional communities is what ADEPT will do. ,”Associate Professor tim inglis
In 10 years, the research group hopes to have a mature network of clinical laboratory nodes that are receptive to socially appropriate, affordable, just-in-time diagnostic technology, supported by a data-driven early warning systems.
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