According to the World Health Organization’s Global Tuberculosis Report, an estimated 8.6 million people developed tuberculosis (TB) and 1.3 million died from the disease in 2012, mostly in developing countries. With drug resistance spreading and nearly one third of the world’s population harboring asymptomatic infections, TB has the potential to become a global health crisis. Tuberculosis is a challenging disease to manage because it is slow and costly to diagnose and takes several months of strict drug regimens to treat. In developing countries, the task of diagnosing TB falls primarily on microscopy clinics that are often underfunded and lack proper quality assurance and safety precautions, causing inconsistent test results, poor sensitivity, and a general lack of access.
Intellectual Ventures Laboratory, in partnership with IV’s Global Good program, has undertaken several efforts to improve the quality of TB diagnostics in developing countries. Sample preparation for sputum, the standard clinical sample for TB diagnostics, is a significant challenge for diagnosis. Our team of engineers and chemists are working to develop novel methods for concentrating and capturing bacteria from sputum that provide high sensitivity and a simplified user-experience for lab technicians.
Our team is also developing novel optical detection methods for automated identification of Mycobacterium tuberculosis, the bacterium that causes TB. Some of our other efforts include developing microscope stains for identifying drug resistance, faster methods of bacterial culture, and research into new TB biomarkers.
With the help of TB experts from around the world IV Lab is working to develop new TB diagnostic technologies compatible with developing world health systems that are faster, and more sensitive, consistent, and accessible.
Wilson, Benjamin K. and Vigil, Genevieve D. “Automated bacterial identification by angle resolved dark-field imaging”, Biomedical Optics Express Vol. 4, Iss. 9, (2014): pp. 1692–1701
Tuberculosis is stronger and more prevalent than ever.
of the world
Published TB diagnostic research.
Automated Bacterial Identification by Angle Resolved Dark-field Imaging
ABSTRACT: We propose and demonstrate a dark-field imaging technique capable of automated identification of individual bacteria. An 87-channel multispectral system capable of angular and spectral resolution was used to measure the scattering spectrum of various bacteria in culture smears. Spectra were compared between various species and between various preparations of the same species. A 15-channel system was then used to prove the viability of bacterial identification with a relatively simple microscope system. A simple classifier was able to identify four of six bacterial species with greater than 90% accuracy in bacteria-by-bacteria testing.Learn More
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