Revolutionizing How We Detect Tuberculosis
We know that Mycobacterium tuberculosis infects nearly one-third of the world's population, kills about 1.8 million people annually and is becoming increasingly drug-resistant. So why has so little about detection and treatment for tuberculosis changed in recent history?
Poor detection is a major stumbling block for those trying to fight the disease. "The diagnostics are ridiculous, they are antiquated, non-standardised and imprecise," laments Dr Tony Fauci, Director of the US National Institute of Allergy and Infectious Diseases. Even the most commonly used and reliable techniques require laboratory infrastructure and personnel resources -- often unavailable in the places where TB is most prevalent.
Take the most common detection method, microscopic analysis of a sputum (or phlegm) smear. To begin with, it relies on expensive laboratory equipment and trained staff. Meanwhile the method, virtually unchanged since the 1800s, can take several days -- if not weeks -- to process. What's more, it doesn't identify TB bacteria 100% of the time. In fact, it only identifies the bacteria in about 3 out of 4 people that have it. It also concentrates just on pulmonary TB infections, ignoring the occurrence of non-pulmonary and latent TB. (While someone who has a latent form of TB can't transmit it to others, the infection can turn into an active infection later on.)
The Tuberculin Skin Test, or Mantoux test, can detect latent tuberculosis, but also presents many challenges. For one, a patient must wait several days to have the results read by a trained professional, which means they have to visit a clinic more than once. When the closest clinic is a two-days walk away and/or a visit costs you half a month's earnings, this becomes a virtual impossibility. Even if you can manage the burden, the nature of the test and human error in reading results often results in a high degree of false positives. False positive results lead to wasted resources for treatment and, most alarmingly, the exponential spread of multi-drug resistant (MDR) and extremely drug resistant (XDR) TB.
All this is grim -- but a group of researchers at Colorado State University may have figured out how to overcome these obstacles.
Currently, they're developing a device that can rapidly diagnose the TB bacteria with a high level of sensitivity and specificity at the point of care.
Nathan Proper, an electrical engineering student working on the project, tells me that the ultimate goal of the project is to create a “robust and portable" device that can be used in "resource-limited areas” and administered by people with limited training. It would give rapid results (within hours, not days), be easily transportable, achieve a high sensitivity and yet be affordable for use in the developing world. The Field-Friendly Tuberculosis Detector (as they're calling it) could mean a breakthrough in TB detection in the developing world.
The actual science behind it is undoubtedly way too complicated for most of us to understand (something about a "fluorescence-based surface immunoassay" and "NHS-ester-amine chemistry"). But the potential for success is hard to mistake. Unlike other detection systems, this device doesn't rely on the detection of antibodies the body develops when exposed to TB (and remain in the body even after the active bacteria is gone). Instead, it identifies molecules specific to tuberculosis that are present in the bloodstream of an infected person. Experiments using controlled solutions of the bacteria on a table-top model have proved that the concept can work.
The project is far from completion. Researchers still must conclude experiments using serums laced with pathogens. It may be a few years until an affordable (and portable) model can start being tested in the field, but the concept is getting lots of exposure already. The project is still in developing stages, says project's director Diego Kapf -- but on this World Tuberculosis Day, let's hope that their work can evolve into a tool that will save many future lives.
Photo Credit: kaibara87







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