TY - JOUR T1 - Integrating drug concentrations and minimum inhibitory concentrations with Bayesian-dose optimisation for multidrug-resistant tuberculosis JF - European Respiratory Journal JO - Eur Respir J SP - 312 LP - 313 DO - 10.1183/09031936.00081313 VL - 43 IS - 1 AU - Shashikant Srivastava AU - Tawanda Gumbo Y1 - 2014/01/01 UR - http://erj.ersjournals.com/content/43/1/312.abstract N2 - To the Editor:The problems of multidrug-resistant (MDR) tuberculosis (TB), extensively drug-resistant (XDR) TB, and even “totally drug-resistant” TB (a term that is still debated), have exposed two important clinical issues [1, 2]. The first issue involves figuring out a way to prevent these difficult-to-treat diseases. The second issue is treating patients with drug-resistant TB [3]. In the meantime even the current susceptibility breakpoints have been challenged as being too high, so that potentially more drug-resistant TB exists than anticipated [4]. This latter aspect suggests that we need a better idea of the minimum inhibitory concentrations (MICs) to both first-line drugs and second-line drugs. Here we propose the use of MICs and drug concentrations to calculate pharmacokinetic/pharmacodynamics (PK/PD) target exposures and then to use Bayesian-feedback dosing as an integrated solution that could improve treatment outcomes.PK/PD relationships are deterministic, which means that the PK/PD parameters and exposures associated with certain degrees of microbial responses can be … ER -