Tuberculosis claims more lives every year than AIDS. This is because, of the 19 anti-TB drugs available, doctors don’t always know which ones will work for whom. Thus, even though tuberculosis is curable, a delayed diagnosis of drug-resistant tuberculosis can mean patients are on ineffective medication for up to 7 years.
Currently, there are no tools to diagnose drug-resistant tuberculosis quickly and comprehensively. AarogyaAI aims to diagnose drug-resistant tuberculosis in a few hours so that a patient can be prescribed effective treatment, instantly. We use a DNA sequence from the patient which is uploaded to our SaaS. Our machine learning algorithm then gives an output report of a comprehensive drug susceptibility status of the patient.
In the long run, we will be able to predict the patterns of evolution of the bacteria and future drug resistance patterns. Our data analytics dashboard will provide valuable insight into bacterial phylogeny, its geographical influences amongst other statistics. This would greatly benefit public health programs in strategically placing PHCs as well as pharma companies to improve supply chain logistics and drug development.