Abstract
Tuberculosis remains a major infectious cause of morbidity and mortality worldwide. Current antibiotic regimens, constructed prior to the development of modern pharmacokinetic-pharmacodynamic (PK–PD) tools, are based on incomplete understanding of exposure–response relationships in drug susceptible and multidrug resistant tuberculosis. Preclinical and population PK data suggest that clinical PK–PD studies may enable therapeutic drug monitoring for some agents and revised dosing for others. Future clinical PK–PD challenges include: incorporation of PK methods to assay free concentrations for all active metabolites; selection of appropriate early outcome measures which reflect therapeutic response; elucidation of genetic contributors to interindividual PK variability; conduct of targeted studies on special populations (including children); and measurement of PK–PD parameters at the site of disease.
Highlights
51 Mukamolova GV, Turapov O, Malkin J, Woltmann G, Barer MR
Clinical PK–PD studies have an important role to play in achieving that goal
No writing assistance was utilized in the production of this manuscript
Summary
Settings include the use of dried blood spot methods to store and transport samples [25,26,27], urine colorimetry to detect low rifampicin exposure [28] or co-culturing patients’ Mtb isolate with their plasma on treatment in liquid culture to give an indication of the relative activity of the treatment regimen [29]. For some antituberculous drugs (e.g., amikacin [30], kanamycin [30], moxifloxacin [31] and linezolid [32] in MDR-TB) limited plasma sampling strategies have sought to determine which single time-point measurements best represent more complex PK indices. For other antibiotics (e.g., rifampicin) Bayesian statistical techniques have been deployed to calculate AUCs from sparse sampling strategies (often two to three blood draws) [33]. It is recognized that antibiotic PK parameters such as AUC and Cmax should be related to the MIC of each drug for the infecting Mtb isolate. Lack of detailed epidemiological data on MIC distributions for Mtb from most highincidence TB settings [35,36] makes calculation of AUC/MIC and CMax/MIC more important for clinical pharmacology studies than for murine or HFS models.
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