Limited Sampling Strategies Using Linear Regression and the Bayesian Approach for Therapeutic Drug Monitoring of Moxifloxacin in Tuberculosis Patients.

Therapeutic drug monitoring (TDM) of moxifloxacin is recommended to improve the response to tuberculosis treatment and reduce acquired drug resistance. Limited sampling strategies (LSSs) are able to reduce the burden of TDM by using a small number of appropriately timed samples to estimate the parameter of interest, the area under the concentration-time curve. This study aimed to develop LSSs for moxifloxacin alone (MFX) and together with rifampin (MFX+RIF) in tuberculosis (TB) patients. Population pharmacokinetic (popPK) models were developed for MFX (n = 77) and MFX+RIF (n = 24). In addition, LSSs using Bayesian approach and multiple linear regression were developed. Jackknife analysis was used for internal validation of the popPK models and multiple linear regression LSSs. Clinically feasible LSSs (one to three samples, 6-h timespan postdose, and 1-h interval) were tested. Moxifloxacin exposure was slightly underestimated in the one-compartment models of MFX (mean -5.1%, standard error [SE] 0.8%) and MFX+RIF (mean -10%, SE 2.5%). The Bayesian LSSs for MFX and MFX+RIF (both 0 and 6 h) slightly underestimated drug exposure (MFX mean -4.8%, SE 1.3%; MFX+RIF mean -5.5%, SE 3.1%). The multiple linear regression LSS for MFX (0 and 4 h) and MFX+RIF (1 and 6 h), showed mean overestimations of 0.2% (SE 1.3%) and 0.9% (SE 2.1%), respectively. LSSs were successfully developed using the Bayesian approach (MFX and MFX+RIF; 0 and 6 h) and multiple linear regression (MFX, 0 and 4 h; MFX+RIF, 1 and 6 h). These LSSs can be implemented in clinical practice to facilitate TDM of moxifloxacin in TB patients.

Population Pharmacokinetic Model and Limited Sampling Strategies for Personalized Dosing of Levofloxacin in Tuberculosis Patients.

Levofloxacin is an antituberculosis drug with substantial interindividual pharmacokinetic variability; therapeutic drug monitoring (TDM) could therefore be helpful to improve treatment results. TDM would be more feasible with limited sampling strategies (LSSs), a method to estimate the area under the concentration curve for the 24-h dosing interval (AUC0-24) by using a limited number of samples. This study aimed to develop a population pharmacokinetic (popPK) model of levofloxacin in tuberculosis patients, along with LSSs using a Bayesian and multiple linear regression approach. The popPK model and Bayesian LSS were developed using data from 30 patients and externally validated with 20 patients. The LSS based on multiple linear regression was internally validated using jackknife analysis. Only clinically suitable LSSs (maximum time span, 8 h; minimum interval, 1 h; 1 to 3 samples) were tested. Performance criteria were root-mean-square error (RMSE) of <15%, mean prediction error (MPE) of <5%, and r2 value of >0.95. A one-compartment model with lag time best described the data while only slightly underestimating the AUC0-24 (mean, -7.9%; standard error [SE], 1.7%). The Bayesian LSS using 0- and 5-h postdose samples (RMSE, 8.8%; MPE, 0.42%; r2 = 0.957) adequately estimated the AUC0-24, with a mean underestimation of -4.4% (SE, 2.7%). The multiple linear regression LSS using 0- and 4-h postdose samples (RMSE, 7.0%; MPE, 5.5%; r2 = 0.977) was internally validated, with a mean underestimation of -0.46% (SE, 2.0%). In this study, we successfully developed a popPK model and two LSSs that could be implemented in clinical practice to assist TDM of levofloxacin. (This study has been registered at ClinicalTrials.gov under identifier NCT01918397.).

Systematic Review of Salivary Versus Blood Concentrations of Antituberculosis Drugs and Their Potential for Salivary Therapeutic Drug Monitoring.

BACKGROUND: Therapeutic drug monitoring is useful in the treatment of tuberculosis to assure adequate exposure, minimize antibiotic resistance, and reduce toxicity. Salivary therapeutic drug monitoring could reduce the risks, burden, and costs of blood-based therapeutic drug monitoring. This systematic review compared human pharmacokinetics of antituberculosis drugs in saliva and blood to determine if salivary therapeutic drug monitoring could be a promising alternative. METHODS: On December 2, 2016, PubMed and the Institute for Scientific Information Web of Knowledge were searched for pharmacokinetic studies reporting human salivary and blood concentrations of antituberculosis drugs. Data on study population, study design, analytical method, salivary Cmax, salivary area under the time-concentration curve, plasma/serum Cmax, plasma/serum area under the time-concentration curve, and saliva-plasma or saliva-serum ratio were extracted. All included articles were assessed for risk of bias. RESULTS: In total, 42 studies were included in this systematic review. For the majority of antituberculosis drugs, including the first-line drugs ethambutol and pyrazinamide, no pharmacokinetic studies in saliva were found. For amikacin, pharmacokinetic studies without saliva-plasma or saliva-serum ratios were found. CONCLUSIONS: For gatifloxacin and linezolid, salivary therapeutic drug monitoring is likely possible due to a narrow range of saliva-plasma and saliva-serum ratios. For isoniazid, rifampicin, moxifloxacin, ofloxacin, and clarithromycin, salivary therapeutic drug monitoring might be possible; however, a large variability in saliva-plasma and saliva-serum ratios was observed. Unfortunately, salivary therapeutic drug monitoring is probably not possible for doripenem and amoxicillin/clavulanate, as a result of very low salivary drug concentrations.

Corrigendum to "Mass spectrometry for therapeutic drug monitoring of anti-tuberculosis drugs" [Clin. Mass Spectrom. 14(Part A) (2019) 34-45].

[This corrects the article DOI: 10.1016/j.clinms.2018.10.002.].

Population Pharmacokinetics and Bayesian Dose Adjustment to Advance TDM of Anti-TB Drugs.

Tuberculosis (TB) is still the number one cause of death due to an infectious disease. Pharmacokinetics and pharmacodynamics of anti-TB drugs are key in the optimization of TB treatment and help to prevent slow response to treatment, acquired drug resistance, and adverse drug effects. The aim of this review was to provide an update on the pharmacokinetics and pharmacodynamics of anti-TB drugs and to show how population pharmacokinetics and Bayesian dose adjustment can be used to optimize treatment. We cover aspects on preclinical, clinical, and population pharmacokinetics of different drugs used for drug-susceptible TB and multidrug-resistant TB. Moreover, we include available data to support therapeutic drug monitoring of these drugs and known pharmacokinetic and pharmacodynamic targets that can be used for optimization of therapy. We have identified a wide range of population pharmacokinetic models for first- and second-line drugs used for TB, which included models built on NONMEM, Pmetrics, ADAPT, MWPharm, Monolix, Phoenix, and NPEM2 software. The first population models were built for isoniazid and rifampicin; however, in recent years, more data have emerged for both new anti-TB drugs, but also for defining targets of older anti-TB drugs. Since the introduction of therapeutic drug monitoring for TB over 3 decades ago, further development of therapeutic drug monitoring in TB next steps will again depend on academic and clinical initiatives. We recommend close collaboration between researchers and the World Health Organization to provide important guideline updates regarding therapeutic drug monitoring and pharmacokinetics/pharmacodynamics.

Mass spectrometry for therapeutic drug monitoring of anti-tuberculosis drugs.

Therapeutic drug monitoring (TDM) uses drug concentrations, primarily from plasma, to optimize drug dosing. Optimisation of drug dosing may improve treatment outcomes, reduce toxicity and reduce the risk of acquired drug resistance. The aim of this narrative review is to outline and discuss the challenges of developing multi-analyte assays for anti-tuberculosis (TB) drugs using liquid chromatography-tandem mass spectrometry (LC-MS/MS) by reviewing the existing literature in the field. Compared to other analytical methods, LC-MS/MS offers higher sensitivity and selectivity while requiring relatively low sample volumes. Additionally, multi-analyte assays are easier to perform since adequate separation and short run times are possible even when non-selective sample preparation techniques are used. However, challenges still exist, especially when optimizing LC separation techniques for assays that include analytes with differing chemical properties. Here, we have identified seven multi-analyte assays for first-line anti-TB drugs that use various solvents for sample preparation and mobile phase separation. Only two multi-analyte assays for second-line anti-TB drugs were identified (including either nine or 20 analytes), with each using different protein precipitation methods, mobile phases and columns. The 20 analyte assay did not include bedaquiline, delamanid, meropenem or imipenem. For these drugs, other assays with similar methodologies were identified that could be incorporated in the development of a future comprehensive multi-analyte assay. TDM is a powerful methodology for monitoring patient's individual treatments in TB programmes, but its implementation will require different approaches depending on available resources. Since TB is most-prevalent in low- and middle-income countries where resources are scarce, a patient-centred approach using sampling methods other than large volume blood draws, such as dried blood spots or saliva collection, could facilitate its adoption and use. Regardless of the methodology of collection and analysis, it will be critical that laboratory proficiency programmes are in place to ensure adequate quality control. It is our intent that the information contained in this review will contribute to the process of assembling comprehensive multiplexed assays for the dynamic monitoring of anti-TB drug treatment in affected individuals.