Understanding pharmacokinetic - pharmacodynamic determinants of outcome to inform dose optimisation for non-MDR TB re-treatment patients in Vietnam

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TB remains a major global public health problem burden, with 9.6 million new cases and 1.2 million deaths in 2014. Vietnam is ranked 12th among the 22 highest TB burden countries (TB). 140 new cases were reported per 100,000 population in 2014. National TB Control Programme data indicates that 6 months of first-line month therapy for new TB patients is not successful in 10% of cases (some patients are still unwell at the end, and others relapse after apparent cure). Only 20-30% of unsuccessful treatments can be attributed to major problems with antibiotic resistance, which requires specialist management. The remainder go on to receive a standard "Category 2" treatment regimen, which is internationally approved but has not been carefully studied. Unfortunately, re-treatment patients on this regimen do not always do well; in Vietnam, the Category 2 regimen results in only 60-75% treatment success. The reason why patients may fail two rounds of treatment is not well understood. One reason could be that the levels of drug in the body (a study known as pharmacokinetics) of some patients is too low to kill the infection. This problem could also be worsened by the fact that the drug levels required to kill the bacteria causing TB (known as Mycobacterium tuberculosis) are not the same in every patient i.e. some patients are infected with a strain of the M. tuberculosis bacteria which can survive higher concentrations of drugs than others. In this project we will focus on the retreatment patient group to determine whether clinical outcome can be explained by measuring individual patient drug levels and carefully studying the ability of TB drugs to kill M tuberculosis. The project will use advanced analytical techniques to measure drug level in patient's blood samples and a number of new laboratory techniques to study how well the drugs kill each M. tuberculosis strain. All of this information will then be combined and analysed using mathematical models to; (i) determine whether the laboratory/analytical measurements can explain the low treatment success rates and (ii) determine whether this information can be used in the future to improve treatment by predicting bad outcomes at an early stage and recommending a better drug course. Data obtained from this study will be shared with other researchers working on TB around the world and will contribute to the wider discussion on tackling TB by designing better treatment. Significantly, this project aims to also increase the local capacity for advanced studies of this type by providing training and mentoring to our Vietnamese colleagues in all of the methodological areas described.