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Item does not contain fulltext, 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 (AUC(0-24)) and peak plasma concentration (C (max)) were assessed with random-effects models, normalised with current World Health Organization-recommended paediatric doses. Determinants of AUC(0-24) 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 AUC(0-24) 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 AUC(0-24) for all first-line anti-TB drugs, while severe malnutrition was associated with lower AUC(0-24) for isoniazid and pyrazinamide. N-acetyltransferase 2 rapid acetylators had lower isoniazid AUC(0-24) and slow acetylators had higher isoniazid AUC(0-24) than intermediate acetylators. Determinants of C (max) were generally similar to those for AUC(0-24). 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-specif

Item does not contain fulltext, BACKGROUND: Adverse effects (AE) to TB treatment cause morbidity, mortality and treatment interruption. The aim of these clinical standards is to encourage best practise for the diagnosis and management of AE.METHODS: 65/81 invited experts participated in a Delphi process using a 5-point Likert scale to score draft standards.RESULTS: We identified eight clinical standards. Each person commencing treatment for TB should: Standard 1, be counselled regarding AE before and during treatment; Standard 2, be evaluated for factors that might increase AE risk with regular review to actively identify and manage these; Standard 3, when AE occur, carefully assessed and possible allergic or hypersensitivity reactions considered; Standard 4, receive appropriate care to minimise morbidity and mortality associated with AE; Standard 5, be restarted on TB drugs after a serious AE according to a standardised protocol that includes active drug safety monitoring. In addition: Standard 6, healthcare workers should be trained on AE including how to counsel people undertaking TB treatment, as well as active AE monitoring and management; Standard 7, there should be active AE monitoring and reporting for all new TB drugs and regimens; and Standard 8, knowledge gaps identified from active AE monitoring should be systematically addressed through clinical research.CONCLUSION: These standards provide a person-centred, consensus-based approach to minimise the impact of AE during TB treatment.

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Contains fulltext : 299618.pdf (Publisher’s version ) (Open Access), The treatment of drug-resistant Mycobacterium tuberculosis relies on complex antibiotic therapy. Inadequate antibiotic exposure can lead to treatment failure, acquired drug resistance, and an increased risk of adverse events. Therapeutic drug monitoring (TDM) can be used to optimize the antibiotic exposure. Therefore, we aimed to develop a single-run multiplex assay using high-performance liquid chromatography-mass spectrometry (HPLC-MS) for TDM of patients with multidrug-resistant, pre-extensively drug-resistant and extensively drug-resistant tuberculosis. A target profile for sufficient performance, based on the intended clinical application, was established and the assay was developed accordingly. Antibiotics were analyzed on a zwitterionic hydrophilic interaction liquid chromatography column and a triple quadrupole mass spectrometer using stable isotope-labeled internal standards. The assay was sufficiently sensitive to monitor drug concentrations over five half-lives for rifampicin, rifabutin, levofloxacin, moxifloxacin, bedaquiline, linezolid, clofazimine, terizidone/cycloserine, ethambutol, delamanid, pyrazinamide, meropenem, prothionamide, and para-amino salicylic acid (PAS). Accuracy and precision were sufficient to support clinical decision making (≤±15% in clinical samples and ±20-25% in spiked samples, with 80% of future measured concentrations predicted to fall within ±40% of nominal concentrations). The method was applied in the TDM of two patients with complex drug-resistant tuberculosis. All relevant antibiotics from their regimens could be quantified and high-dose therapy was initiated, followed by microbiological conversion. In conclusion, we developed a multiplex assay that enables TDM of the relevant first- and second-line anti-tuberculosis medicines in a single run and was able to show its applicability in TDM of two drug-resistant tuberculosis patients.

Item does not contain fulltext, BACKGROUND: Optimal drug dosing is important to ensure adequate response to treatment, prevent development of drug resistance and reduce drug toxicity. The aim of these clinical standards is to provide guidance on 'best practice´ for dosing and management of TB drugs.METHODS: A panel of 57 global experts in the fields of microbiology, pharmacology and TB care were identified; 51 participated in a Delphi process. A 5-point Likert scale was used to score draft standards. The final document represents the broad consensus and was approved by all participants.RESULTS: Six clinical standards were defined: Standard 1, defining the most appropriate initial dose for TB treatment; Standard 2, identifying patients who may be at risk of sub-optimal drug exposure; Standard 3, identifying patients at risk of developing drug-related toxicity and how best to manage this risk; Standard 4, identifying patients who can benefit from therapeutic drug monitoring (TDM); Standard 5, highlighting education and counselling that should be provided to people initiating TB treatment; and Standard 6, providing essential education for healthcare professionals. In addition, consensus research priorities were identified.CONCLUSION: This is the first consensus-based Clinical Standards for the dosing and management of TB drugs to guide clinicians and programme managers in planning and implementation of locally appropriate measures for optimal person-centred treatment to improve patient care.

Contains fulltext : 235795.pdf (Publisher’s version ) (Open Access), 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.

Contains fulltext : 238450.pdf (Publisher’s version ) (Closed access)

Item does not contain fulltext, OBJECTIVES: Extensive but fragmented data from existing studies were used to describe the drug-drug interaction between rifabutin and HIV PIs and predict doses achieving recommended therapeutic exposure for rifabutin in patients with HIV-associated TB, with concurrently administered PIs. METHODS: Individual-level data from 13 published studies were pooled and a population analysis approach was used to develop a pharmacokinetic model for rifabutin, its main active metabolite 25-O-desacetyl rifabutin (des-rifabutin) and drug-drug interaction with PIs in healthy volunteers and patients who had HIV and TB (TB/HIV). RESULTS: Key parameters of rifabutin affected by drug-drug interaction in TB/HIV were clearance to routes other than des-rifabutin (reduced by 76%-100%), formation of the metabolite (increased by 224% in patients), volume of distribution (increased by 606%) and distribution to the peripheral compartment (reduced by 47%). For des-rifabutin, clearance was reduced by 35%-76% and volume of distribution increased by 67%-240% in TB/HIV. These changes resulted in overall increased exposure to rifabutin in TB/HIV patients by 210% because of the effects of PIs and 280% with ritonavir-boosted PIs. CONCLUSIONS: Given together with non-boosted or ritonavir-boosted PIs, rifabutin at 150 mg once daily results in similar or higher exposure compared with rifabutin at 300 mg once daily without concomitant PIs and may achieve peak concentrations within an acceptable therapeutic range. Although 300 mg of rifabutin every 3 days with boosted PI achieves an average equivalent exposure, intermittent doses of rifamycins are not supported by current guidelines.

Item does not contain fulltext, Rationale: Currently recommended multidrug treatment regimens for Mycobacterium avium complex (MAC) lung disease yield limited cure rates. This results, in part, from incomplete understanding of the pharmacokinetics and pharmacodynamics of the drugs. Objectives: To study pharmacokinetics, pharmacodynamics, and drug interactions of multidrug treatment regimens in a large cohort of patients with MAC lung disease. Methods: We retrospectively collected pharmacokinetic data of all patients treated for MAC lung disease in the Adult Care Unit at National Jewish Health, Denver, Colorado, in the January 2006 to January 2010 period; we retrospectively calculated areas under the time-concentration curve (AUC). Minimum inhibitory concentrations (MIC) of their MAC isolates were retrieved for pharmacodynamic calculations. Measurements and Main Results: We included 531 pharmacokinetic analyses, performed for 481 patients (84% females; mean age, 63 yr; mean body mass index, 21.6). Peak serum concentrations (C(max)) below target range were frequent for ethambutol (48% of patients); clarithromycin (56%); and azithromycin (35%). Concurrent administration of rifampicin led to 68%, 23%, and 10% decreases in C(max) of clarithromycin, azithromycin, and moxifloxacin. C(max)/MIC or AUC/MIC ratios associated with bactericidal activity were seldom met; 57% of patients achieved target ratios for ethambutol, versus 42% for clarithromycin, 19% for amikacin, 18% for rifampicin, and 11% for moxifloxacin. Conclusions: Currently recommended regimens for MAC lung disease yield important pharmacologic interactions and low concentrations of key drugs including macrolides. Pharmacodynamic indices for rifampicin, clarithromycin, amikacin, and moxifloxacin are seldom met. This may partly explain the poor outcomes of currently recommended treatment regimens. Trials of new drugs and new dosing strategies are needed.