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INTRODUCTION: An effective rifampicin-resistant tuberculosis (RR-TB) treatment regimen should include prevention of resistance amplification. While bedaquiline (BDQ) has been recommended in all-oral RR-TB treatment regimen since 2019, resistance is rising at alarming rates. This may be due to BDQ's delayed bactericidal effect, which increases the risk of selecting for resistance to fluoroquinolones and/or BDQ in the first week of treatment when the bacterial load is highest. We aim to strengthen the first week of treatment with the injectable drug amikacin (AMK). To limit the ototoxicity risk while maximising the bactericidal effect, we will evaluate the safety of adding a 30 mg/kg AMK injection on the first and fourth day of treatment. METHODS AND ANALYSIS: We will conduct a single-arm clinical trial on 20 RR-TB patients nested within an operational study called ShoRRT (All oral Shorter Treatment Regimen for Drug resistant Tuberculosis). In addition to all-oral RR-TB treatment, patients will receive two doses of AMK. The primary safety endpoint is any grade 3-4 adverse event during the first 2 weeks of treatment related to the use of AMK. With a sample size of 20 patients, we will have at least 80% statistical power to support the alternative hypothesis, indicating that less than 14% of patients treated with AMK experience a grade 3-4 adverse event related to its use. Safety data obtained from this study will inform a larger multicountry study on using two high doses of AMK to prevent acquired resistance. ETHICS AND DISSEMINATION: Approval was obtained from the ethics committee of Rwanda, Rwanda Food and Drug Authority, Universitair Ziekenhuis, the Institute of Tropical Medicine ethics review board. All participants will provide informed consent. Study results will be disseminated through peer-reviewed journals and conferences. TRIAL REGISTRATION NUMBER: NCT05555303.

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OBJECTIVES: Participation in an external (interlaboratory) quality control (QC) programme is an essential part of quality assurance as it provides laboratories with valuable insights into their analytical performance. We describe the 10 year results of an international QC programme for the measurement of anti-tuberculosis (TB) drugs. METHODS: Each year, two rounds were organized in which serum (or plasma) samples, spiked with known concentrations of anti-TB drugs, were provided to participating laboratories for analysis. Reported measurements within 80%-120% of weighed-in concentrations were considered accurate. Mixed model linear regression was performed to assess the effect of the measured drug, concentration level, analytical technique and performing laboratory on the absolute inaccuracy. RESULTS: By 2022, 31 laboratories had participated in the QC programme and 13 anti-TB drugs and metabolites were included. In total 1407 measurements were reported. First-line TB drugs (isoniazid, rifampicin, pyrazinamide and ethambutol) represented 58% of all measurements. Overall, 83.2% of 1407 measurements were accurate, and the median absolute inaccuracy was 7.3% (IQR, 3.3%-15.1%). The absolute inaccuracy was related to the measured anti-TB drug and to the performing laboratory, but not to the concentration level or to the analytical technique used. The median absolute inaccuracies of rifampicin and isoniazid were relatively high (10.2% and 10.9%, respectively). CONCLUSIONS: The 10 year results of this external QC programme illustrate the need for continuous external QC for the measurement of anti-TB drugs for research and patient care purposes, because one in six measurements was inaccurate. Participation in the programme alerts laboratories to previously undetected analytical problems.

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Long-term usage of linezolid can result in adverse events such as peripheral neuropathy, anemia and thrombocytopenia. Therapeutic drug monitoring data from 75 drug-resistant tuberculosis patients treated with linezolid were analyzed using a time-to-event (TTE) approach for peripheral neuropathy and anemia and indirect response modelling for thrombocytopenia. Different time-varying linezolid pharmacokinetic exposure indices (AUC0-24h,ss, Cav, Cmax and Cmin) and patient characteristics were investigated as risk factors. A treatment duration shorter than 3 months was considered dropout and was modelled using a TTE approach. An exposure-response relationship between linezolid Cmin and both peripheral neuropathy and anemia was found. The exposure index which best described the development of thrombocytopenia was AUC0-24h. The final TTE dropout model indicated an association between linezolid Cmin and dropout. New safety targets for each adverse event were proposed which can be used for individualized linezolid dosing. According to the model predictions at 6 months of treatment, a Cmin of 0.11 mg/L and 1.4 mg/L should not be exceeded to keep the cumulative probability to develop anemia and peripheral neuropathy below 20%. The AUC0-24h should be below 111 h·mg/L or 270 h·mg/L to prevent thrombocytopenia and severe thrombocytopenia, respectively. A clinical utility assessment showed that the currently recommended dose of 600 mg once daily is safer compared to a 300 mg BID dosing strategy considering all four safety endpoints.

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The aim of this study was to evaluate the difference in drug exposure of rifampicin in native versus non-native Paraguayan populations using dried blood spots (DBS) samples collected utilizing a limited sampling strategy. This was a prospective pharmacokinetic study that enrolled hospitalized tuberculosis (TB) patients from both native and non-native populations receiving oral rifampicin 10 mg/kg once-daily dosing. Steady-state DBS samples were collected at 2, 4, and 6 h after intake of rifampicin. The area under the time concentration curve 0-24 h (AUC0-24) was calculated using a Bayesian population PK model. Rifampicin AUC0-24 < 38.7 mg*h/L was considered as low. The probability of target attainment (PTA) was calculated using AUC0-24/MIC > 271 as a target and estimated MIC values of 0.125 and 0.25 mg/L. In total, 50 patients were included. Native patients (n = 30) showed comparable drug exposure to the non-natives (n = 20), median AUC0-24 24.7 (17.1-29.5 IQR) and 21.6 (15.0-35.4 IQR) mg*h/L (p = 0.66), respectively. Among total patients, only 16% (n = 8) had a rifampicin AUC0-24 > 38.7 mg*h/L. Furthermore, PTA analysis showed that only 12 (24%) of the patients met a target AUC0-24 /MIC ≥ 271, assuming an MIC of 0.125 mg/L, which plummeted to 0% at a wild-type MIC of 0.25 mg/L. We successfully used DBS and limited sampling for the AUC0-24 estimation of rifampicin. Currently, our group, the EUSAT-RCS consortium, is preparing a prospective multinational, multicenter phase IIb clinical trial evaluating the safety and efficacy of high-dose rifampicin (35 mg/kg) in adult subjects using the DBS technique for AUC0-24 estimation.

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ABSTRACT: Therapeutic drug monitoring (TDM) results for ganciclovir in 12 different treatment episodes showed large intraindividual and interindividual variabilities in the trough concentration and area under the 24-hour concentration-time curve (AUC24). Despite adequate valganciclovir dosing, subtherapeutic concentrations were found in 30% of the treatment episodes. A decrease in viral load was observed regardless of subtherapeutic exposure. These findings show the need for target concentration evaluation and assessment of the applicability of ganciclovir TDM in children.

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BACKGROUND: Voriconazole is an antifungal drug used for the treatment of invasive fungal infections. Due to highly variable drug exposure, therapeutic drug monitoring (TDM) has been recommended. TDM may be helpful to predict exposure accurately, but covariates, such as severe inflammation, that influence the metabolism of voriconazole have not been included in the population pharmacokinetic (popPK) models suitable for routine TDM. OBJECTIVES: To investigate whether the effect of inflammation, reflected by C-reactive protein (CRP), could improve a popPK model that can be applied in clinical care. PATIENTS AND METHODS: Data from two previous studies were included in the popPK modelling. PopPK modelling was performed using Edsim++. Different popPK models were compared using Akaike Information Criterion and goodness-of-fit plots. RESULTS: In total, 1060 voriconazole serum concentrations from 54 patients were included in this study. The final model was a one-compartment model with non-linear elimination. Only CRP was a significant covariate, and was included in the final model and found to affect the maximum rate of enzyme activity (Vmax). For the final popPK model, the mean volume of distribution was 145 L [coefficient of variation percentage (CV%)=61%], mean Michaelis-Menten constant was 5.7 mg/L (CV%=119%), mean Vmax was 86.4 mg/h (CV%=99%) and mean bioavailability was 0.83 (CV%=143%). Internal validation using bootstrapping resulted in median values close to the population parameter estimates. CONCLUSIONS: This one-compartment model with non-linear elimination and CRP as a covariate described the pharmacokinetics of voriconazole adequately.

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Gastrointestinal mucositis could potentially compromise drug absorption due to functional loss of mucosa and other pathophysiological changes in the gastrointestinal microenvironment. Little is known about this effect on commonly used anti-infectives. This study aimed to explore the association between different stages of gastrointestinal mucositis, drug exposure, and gut microbiota. A prospective, observational pilot study was performed in HSCT patients aged ≥ 18 years receiving anti-infectives orally. Left-over blood samples and fecal swabs were collected from routine clinical care until 14 days after HSCT to analyze drug and citrulline concentrations and to determine the composition of the gut microbiota. 21 patients with a median age of 58 (interquartile range 54-64) years were included with 252 citrulline, 155 ciprofloxacin, 139 fluconazole, and 76 acyclovir concentrations and 48 fecal swabs obtained. Severe gastrointestinal mucositis was observed in all patients. Due to limited data correlation analysis was not done for valacyclovir and fluconazole, however we did observe a weak correlation between ciprofloxacin and citrulline concentrations. This could suggest that underexposure of ciprofloxacin can occur during severe mucositis. A follow-up study using frequent sampling rather than the use of left-over would be required to investigate the relationship between gastrointestinal mucositis, drug exposure, and gut microbiome.

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BACKGROUND: Suboptimal exposure to antituberculosis (anti-TB) drugs has been associated with unfavourable treatment outcomes. We aimed to investigate estimates and determinants of first-line anti-TB drug pharmacokinetics in children and adolescents at a global level. METHODS: We systematically searched MEDLINE, Embase and Web of Science (1990-2021) for pharmacokinetic studies of first-line anti-TB drugs in children and adolescents. Individual patient data were obtained from authors of eligible studies. Summary estimates of total/extrapolated area under the plasma concentration-time curve from 0 to 24 h post-dose (AUC0-24) and peak plasma concentration (C max) were assessed with random-effects models, normalised with current World Health Organization-recommended paediatric doses. Determinants of AUC0-24 and C max were assessed with linear mixed-effects models. RESULTS: Of 55 eligible studies, individual patient data were available for 39 (71%), including 1628 participants from 12 countries. Geometric means of steady-state AUC0-24 were summarised for isoniazid (18.7 (95% CI 15.5-22.6) h·mg·L-1), rifampicin (34.4 (95% CI 29.4-40.3) h·mg·L-1), pyrazinamide (375.0 (95% CI 339.9-413.7) h·mg·L-1) and ethambutol (8.0 (95% CI 6.4-10.0) h·mg·L-1). Our multivariate models indicated that younger age (especially <2 years) and HIV-positive status were associated with lower AUC0-24 for all first-line anti-TB drugs, while severe malnutrition was associated with lower AUC0-24 for isoniazid and pyrazinamide. N-acetyltransferase 2 rapid acetylators had lower isoniazid AUC0-24 and slow acetylators had higher isoniazid AUC0-24 than intermediate acetylators. Determinants of C max were generally similar to those for AUC0-24. CONCLUSIONS: This study provides the most comprehensive estimates of plasma exposures to first-line anti-TB drugs in children and adolescents. Key determinants of drug exposures were identified. These may be relevant for population-specific dose adjustment or individualised therapeutic drug monitoring.

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

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Pyrazinamide is one of the first-line antituberculosis drugs. The efficacy of pyrazinamide is associated with the ratio of 24-h area under the concentration-time curve (AUC24) to MIC. The objective of this study was to develop and validate a limited sampling strategy (LSS) based on a population pharmacokinetic (popPK) model to predict AUC24. A popPK model was developed using an iterative two-stage Bayesian procedure and was externally validated. Using data from 20 treatment-naive adult tuberculosis (TB) patients, a one compartment model with transit absorption and first-order elimination best described pyrazinamide pharmacokinetics and fed state was the only significant covariate for absorption rate constant (ka). External validation, using data from 26 TB patients, showed that the popPK model predicted AUC24 with a slight underestimation of 2.1%. LSS were calculated using Monte Carlo simulation (n = 10,000). External validation showed LSS with time points 0 h, 2 h, and 6 h performed best with RMSE of 9.90% and bias of 0.06%. Food slowed absorption of pyrazinamide, but did not affect bioavailability, which may be advantageous in case of nausea or vomiting in which food can be used to diminish these effects. In this study, we successfully developed and validated a popPK model and LSS, using 0 h, 2 h, and 6 h postdose samples, that could be used to perform therapeutic drug monitoring (TDM) of pyrazinamide in TB patients.

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Linezolid is an efficacious medication for the treatment of drug-resistant tuberculosis but has been associated with serious safety issues that can result in treatment interruption. The objectives of this study were thus to build a population pharmacokinetic model and to use the developed model to establish a model-informed precision dosing (MIPD) algorithm enabling safe and efficacious dosing in patients with multidrug- and extensively drug-resistant tuberculosis. Routine hospital therapeutic drug monitoring data, collected from 70 tuberculosis patients receiving linezolid, was used for model development. Efficacy and safety targets for MIPD were the ratio of unbound area under the concentration versus time curve between 0 and 24 h over minimal inhibitory concentration (fAUC0-24h/MIC) above 119 and unbound plasma trough concentration (fCmin) below 1.38 mg/L, respectively. Model building was performed in NONMEM 7.4.3. The final population pharmacokinetic model consisted of a one-compartment model with transit absorption and concentration- and time-dependent auto-inhibition of elimination. A flat dose of 600 mg once daily was appropriate in 67.2% of the simulated patients from an efficacy and safety perspective. Using the here developed MIPD algorithm, the proportion of patients reaching the efficacy and safety target increased to 81.5% and 88.2% using information from two and three pharmacokinetic sampling occasions, respectively. This work proposes an MIPD approach for linezolid and suggests using three sampling occasions to derive an individualized dose that results in adequate efficacy and fewer safety concerns compared to flat dosing.

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BACKGROUND: Cytomegalovirus (CMV) can cause severe disease, including rejection in transplant recipients. Ganciclovir and its oral prodrug valganciclovir have been used as first-line therapy for CMV disease in transplant recipients. The exposure targets of ganciclovir are not exactly known, and toxicity and resistance have interfered with ganciclovir therapy. OBJECTIVES: To evaluate the pharmacokinetics (PK) and pharmacodynamics (PD) of ganciclovir in transplant recipients. METHODS: We used patient data from a previous observational study on ganciclovir therapeutic drug monitoring (TDM) in prophylaxis and therapy. The ganciclovir concentrations and CMV viral loads were determined during routine clinical care. The PK/PD population modelling and simulations were done with non-parametric methodology using the Pmetrics program. RESULTS: Eighty-five patients were included in the PK modelling. The final PK model was a two-compartment model with first-order absorption and elimination. A subset of 17 patients on CMV therapy were included in the PD modelling. A median of 4 (range 2-8) viral loads were obtained per patient. A simulation of 10 000 patients showed that an approximately 1 log10 reduction of CMV viral load will be observed after 12.5 days at the current recommended dose. CONCLUSIONS: The developed linked PK/PD population model and subsequent PD simulations showed slow decline of CMV viral load and it appears that dosing of (val)ganciclovir in this study might have been inadequate to achieve fast reduction of viral load. It is clear that further studies are needed to specify the PD effects of ganciclovir by performing systematic measurements of both ganciclovir concentrations and CMV viral loads.

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BACKGROUND: Ganciclovir is the mainstay of therapy for the prophylaxis and treatment of Cytomegalovirus. However, therapy with this antiviral agent is hindered by side effects such as myelosuppression, which often leads to therapy cessation. Underdosing, as an attempt to prevent side effects, can lead to drug resistance and therapy failure. Therapeutic drug monitoring (TDM) has been used to overcome these problems. The purpose of this narrative review was to give an overview of ganciclovir TDM, available assays, population pharmacokinetic models, and discuss the current knowledge gaps. METHODS: For this narrative review, a nonsystematic literature search was performed on the PubMed database in April 2021. The following search terms were used: ganciclovir, valganciclovir, pharmacokinetics, pharmacodynamics, population pharmacokinetics, therapeutic drug monitoring, bioassay, liquid chromatography coupled with tandem mass spectrometry, liquid chromatography, chromatography, spectrophotometry, and toxicity. In addition, the reference lists of the included articles were screened. RESULTS: The most common bioanalysis method identified was liquid chromatography coupled with tandem mass spectrometry. There are different models presenting ganciclovir IC50; however, establishing a pharmacokinetic/pharmacodynamic target for ganciclovir based on preclinical data is difficult because there are no studies combining dynamic drug exposure in relation to inhibition of viral replication. The data on ganciclovir TDM show large interindividual variability, indicating that TDM may play a role in modifying the dose to reduce toxicity and prevent treatment failure related to low concentrations. The main hurdle for implementing TDM is the lack of robust data to define a therapeutic window. CONCLUSIONS: Although the pharmacokinetics (PK) involved is relatively well-described, both the pharmacodynamics (PD) and pharmacokinetic/pharmacodynamic relationship are not. This is because the studies conducted to date have mainly focused on estimating ganciclovir exposure, and owing to the limited therapeutic options for CMV infections, future studies on ganciclovir are warranted.

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Previous clinical trials for drug-susceptible tuberculosis (DS-TB) have shown that first-line treatment with doses of rifampicin up to 40 mg/kg are safe and increase the early treatment response for young adults with pulmonary tuberculosis. This may lead to a shorter treatment duration for those persons with TB and a good baseline prognosis, or increased treatment success for vulnerable subgroups (age > 60, diabetes, malnutrition, HIV, hepatitis B or hepatitis C coinfection, TB meningitis, stable chronic liver diseases). Here, we describe the design of a phase 2b/c clinical study under the hypothesis that rifampicin at 35 mg/kg is as safe for these vulnerable groups as for the participants included in previous clinical trials. RIAlta is an interventional, open-label, multicenter, prospective clinical study with matched historical controls comparing the standard DS-TB treatment (isoniazid, pyrazinamide, and ethambutol) with rifampicin at 35 mg/kg (HR35ZE group) vs. rifampicin at 10 mg/kg (historical HR10ZE group). The primary outcome is the incidence of grade ≥ 3 Adverse Events or Severe Adverse Events. A total of 134 participants will be prospectively included, and compared with historical matched controls with at least a 1:1 proportion. This will provide a power of 80% to detect non-inferiority with a margin of 8%. This study will provide important information for subgroups of patients that are more vulnerable to TB bad outcomes and/or treatment toxicity. Despite limitations such as non-randomized design and the use of historical controls, the results of this trial may inform the design of future more inclusive clinical trials, and improve the management of tuberculosis in subgroups of patients for whom scientific evidence is still scarce. Trial registration: EudraCT 2020-003146-36, NCT04768231.

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Moxifloxacin is an attractive drug for the treatment of isoniazid-resistant rifampicin-susceptible tuberculosis (TB) or drug-susceptible TB complicated by isoniazid intolerance. However, co-administration with rifampicin decreases moxifloxacin exposure. It remains unclear whether this drug-drug interaction has clinical implications. This retrospective study in a Dutch TB center investigated how rifampicin affected moxifloxacin exposure in patients with isoniazid-resistant or -intolerant TB. Moxifloxacin exposures were measured between 2015 and 2020 in 31 patients with isoniazid-resistant or -intolerant TB receiving rifampicin, and 20 TB patients receiving moxifloxacin without rifampicin. Moxifloxacin exposure, i.e., area under the concentration-time curve (AUC0-24h), and attainment of AUC0-24h/MIC > 100 were investigated for 400 mg moxifloxacin and 600 mg rifampicin, and increased doses of moxifloxacin (600 mg) or rifampicin (900 mg). Moxifloxacin AUC0-24h and peak concentration with a 400 mg dose were decreased when rifampicin was co-administered compared to moxifloxacin alone (ratio of geometric means 0.61 (90% CI (0.53, 0.70) and 0.81 (90% CI (0.70, 0.94), respectively). Among patients receiving rifampicin, 65% attained an AUC0-24h/MIC > 100 for moxifloxacin compared to 78% of patients receiving moxifloxacin alone; this difference was not significant. Seven out of eight patients receiving an increased dose of 600 mg moxifloxacin reached the target AUC0-24h/MIC > 100. This study showed a clinically significant 39% decrease in moxifloxacin exposure when rifampicin was co-administered. Moxifloxacin dose adjustment may compensate for this drug-drug interaction. Further exploring the impact of higher doses of these drugs in patients with isoniazid resistance or intolerance is paramount.

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BACKGROUND: Therapeutic drug monitoring (TDM) supports personalized treatment. For successful implementation, TDM must have a turnaround time suited to the clinical needs of patients and their health care settings. Here, the authors share their views of how a TDM strategy can be tailored to specific settings and patient groups. METHODS: The authors selected distinct scenarios for TDM: high-risk, complex, and/or critically ill patient population; outpatients; and settings with limited laboratory resources. In addition to the TDM scenario approach, they explored potential issues with the legal framework governing dose escalation. RESULTS: The most important issues identified in the different scenarios are that critically ill patients require rapid turnaround time, outpatients require an easy sampling procedure for the sample matrix and sample collection times, settings with limited laboratory resources necessitate setting-specific analytic techniques, and all scenarios warrant a legal framework to capture the use of escalated dosages, ideally with the use of trackable dosing software. CONCLUSIONS: To benefit patients, TDM strategies need to be tailored to the intended population. Strategies can be adapted for rapid turnaround time for critically ill patients, convenient sampling for outpatients, and feasibility for those in settings with limited laboratory resources.

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BACKGROUND: The use of (val)ganciclovir is complicated by toxicity, slow response to treatment and acquired resistance. OBJECTIVES: To evaluate a routine therapeutic drug monitoring (TDM) programme for ganciclovir in a transplant patient population. METHODS: An observational study was performed in transplant recipients from June 2018 to February 2020. Dose adjustments were advised by the TDM pharmacist as part of clinical care. For prophylaxis, a trough concentration (Cmin) of 1-2 mg/L and an AUC24h of >50 mg·h/L were aimed for. For treatment, a Cmin of 2-4 mg/L and an AUC24h of 80-120 mg·h/L were aimed for. RESULTS: Ninety-five solid organ and stem cell transplant patients were enrolled. Overall, 450 serum concentrations were measured; with a median of 3 (IQR = 2-6) per patient. The median Cmin and AUC24h in the treatment and prophylaxis groups were 2.0 mg/L and 90 mg·h/L and 0.9 mg/L and 67 mg·h/L, respectively. Significant intra- and inter-patient patient variability was observed. The majority of patients with an estimated glomerular filtration rate of more than 120 mL/min/1.73 m2 and patients on continuous veno-venous haemofiltration showed underexposure. The highest Cmin and AUC24h values were associated with the increase in liver function markers and decline in WBC count as compared with baseline. CONCLUSIONS: This study revealed that a standard weight and kidney function-based dosing regimen resulted in highly variable ganciclovir Cmin and under- and over-exposure were observed in patients on dialysis and in patients with increased renal function. Clearly there is a need to explore the impact of concentration-guided dose adjustments in a prospective study.

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Nontuberculous mycobacteria can cause minimally symptomatic self-limiting infections to progressive and life-threatening disease of multiple organs. Several factors such as increased testing and prevalence have made this an emerging infectious disease. Multiple guidelines have been published to guide therapy, which remains difficult owing to the complexity of therapy, the potential for acquired resistance, the toxicity of treatment, and a high treatment failure rate. Given the long duration of therapy, complex multi-drug treatment regimens, and the risk of drug toxicity, therapeutic drug monitoring is an excellent method to optimize treatment. However, currently, there is little available guidance on therapeutic drug monitoring for this condition. The aim of this review is to provide information on the pharmacokinetic/pharmacodynamic targets for individual drugs used in the treatment of nontuberculous mycobacteria disease. Lacking data from randomized controlled trials, in vitro, in vivo, and clinical data were aggregated to facilitate recommendations for therapeutic drug monitoring to improve efficacy and reduce toxicity.

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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.

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OBJECTIVES: Malnutrition is associated with a twofold higher risk of dying in patients with tuberculosis (TB) and considered an important potentially reversible risk factor for failure of TB treatment. The construct of malnutrition has three domains: intake or uptake of nutrition; body composition and physical and cognitive function. The objectives of this systematic review are to identify malnutrition assessment methods, and to quantify how malnutrition assessment methods capture the international consensus definition for malnutrition, in patients with TB. DESIGN: Different assessment methods were identified. We determined the extent of capturing of the three domains of malnutrition, that is, intake or uptake of nutrition, body composition and physical and cognitive function. RESULTS: Seventeen malnutrition assessment methods were identified in 69 included studies. In 53/69 (77%) of studies, body mass index was used as the only malnutrition assessment method. Three out of 69 studies (4%) used a method that captured all three domains of malnutrition. CONCLUSIONS: Our study focused on published articles. Implementation of new criteria takes time, which may take longer than the period covered by this review. Most patients with TB are assessed for only one aspect of the conceptual definition of malnutrition. The use of international consensus criteria is recommended to establish uniform diagnostics and treatment of malnutrition. PROSPERO REGISTRATION NUMBER: CRD42019122832.

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