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Affordable near-patient diagnostics to distinguish infectious diseases in the Philippines (AND2ID in Ph)

Funder: UK Research and InnovationProject code: MR/R025444/1
Funded under: MRC Funder Contribution: 406,350 GBP

Affordable near-patient diagnostics to distinguish infectious diseases in the Philippines (AND2ID in Ph)

Description

Acute fever may be caused by a range of pathogens, but clinical symptoms may be too non-specific to differentiate the causative organism, so correct diagnosis requires pathogen-specific diagnostic tests. These diagnostics are too expensive for routine use in resource-limited settings. This means that many patients are treated empirically with broad spectrum antibiotics, which may be unecessary, toxic, and increase the risk of antimicrobial resistance. Conversely delayed diagnosis and treatment may lead to poor outcomes. A barrier to low-cost diagnostics in the Philippines, arises from a value chain that spans the world, without Purchasing Power Parity (PPP). If we could use technologies that can be manufactured locally, using local resources, then we have the first step to providing affordable diagnostics in resource poor areas, and delivering a sustained improvement in healthcare, while also developing the local economy. We have made an enzyme (BOON-enzyme) that can do these tests and can be produced almost anywhere without special facilities. We have made the enzyme pink, so that you can see that it has been produced and we have a way of making it stick to sand so that it is very stable. We are going to use one of these enzymes - BOON-Taq in polymerase chain reaction (PCR) - to perform a clinical study in patients with suspected dengue and leptospirosis at the University of Santo Tomas in Manila, to assess the impact of the use of diagnostics on the patient pathway and the disease burden. As a result of these trials we will design a diagnostic kit that can be taken out to rural clinics and we will undertake clinical trials in such a clinic. We will support the study by developing a healthcare economics model of the impact of diagnostics on the patient pathway.

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