Tuberculosis

Tuberculosis (TB) affects nine million people annually. On average, an untreated patient infects 15 others. Early case detection and treatment are crucial to stop the epidemic. Sputum smear fluorescence microscopy is the recommended method to detect TB but accessibility to it is limited in resource-poor settings. Combining a specialized lens, image processing software and widely available camera phones, this innovation will create an easy-to-use, intelligent sputum smear reader that will help improve TB diagnosis.

Tuberculosis was responsible for 3800 deaths everyday in 2010. A quick and accurate diagnostic tool for latent and drug-resistant tuberculosis could save a quarter of lives claimed by tuberculosis annually. We are proposing to develop a novel single diagnostic assay which is rapid, highly sensitive and can diagnose active, latent and drug-resistant tuberculosis.

This project aims to evaluate the usefulness of sweat in early and accurate diagnosis. Sweat, a common symptom in TB, is been used extensively in cystic fibrosis. This idea will assist in global plan to control TB. It helps patients take a pro-active role in diagnosis at very little expense, so it can be involved early in the diagnostic process. We hope that a TB sweat test will be developed if this idea is successful in Nigeria.

Our bold idea is to develop a low-cost platform for rapid detection of tuberculosis in low-income countries. Here, at the Department of Biomedical Engineering of McGill University and in collaboration with the BigTech Labs in India, we will design and build a low-cost and electricity free thermal cycler that amplifies the myobacteria’s DNA in sputum samples. We envision that our device will be extremely useful in remote areas, where access to standard lab infrastructure is limited. Follow Mohsen Akbari on Twitter @sina_a81  "

The project addresses the need for sensitive point-of-care diagnostic tools for tuberculosis in HIV infected people by optimising the LAM assay with biosensor and aptamer technology. Implications are a reduction of time to diagnosis tuberculosis, leading to better management and decreased spread of tuberculosis.