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

Clinical considerations and pharmacokinetic interactions between HIV and tuberculosis therapeutics

INTRODUCTION

Tuberculosis(TB) is a leading infectious diseases cause of mortality worldwide,especially for people living with human immunodeficiency virus(PLWH). Treating TB in PLWH can be challenging due to numerous druginteractions.

AREASCOVERED

Thisreview discusses drug interactions between antitubercular andantiretroviral drugs. Due to its clinical importance, initiation ofantiretroviral therapy in patients requiring TB treatment isdiscussed. Special focus is placed on the rifamycin class, as itaccounts for the majority of interactions. Clinically relevantguidance is provided on how to manage these interactions. Anadditional section on utilizing therapeutic drug monitoring (TDM) tooptimize drug exposure and minimize toxicities is included.

EXPERTOPINION

Antitubercularand antiretroviral coadministration can be successfully managed. TDMcan be used to optimize drug exposure and minimize toxicity risk. Asnew TB and HIV drugs are discovered, additional research will beneeded to assess for clinically relevant drug interactions.

Protein binding investigation of first-line and second-line antituberculosis drugs

Data on protein binding are incomplete for first-line antituberculosis drugs, and lacking for second-line antituberculosis drugs that are used extensively for multi-drug-resistant tuberculosis (levofloxacin, linezolid and moxifloxacin). Thus, the main purposes of this study were to investigate: (i) the relationship between carrier protein concentration and drug binding; and (ii) the feasibility of predicting free drug concentration using in-vitro and in-vivo results. In-vitro experiments were performed on spiked plasma mimicking real-case samples (drug combinations from clinical practice). Median in-vivo protein binding was 1.5% for ethambutol, 9.7% for isoniazid, 0.7% for pyrazinamide and 88.2% for rifampicin; and median in-vitro protein binding was 26.2% for levofloxacin, 12.8% for linezolid and 46.3% for moxifloxacin. Albumin concentration (<30 g/L) had a moderate impact on moxifloxacin binding and a strong impact on levofloxacin, linezolid and rifampicin binding. Determination of the free drug concentration seems to be of little value for ethambutol, isoniazid, moxifloxacin and pyrazinamide; limited value for linezolid because of its low binding; and major value for rifampicin in hypoalbuminaemic patients with tuberculosis, and levofloxacin because total concentration was an inaccurate reflection of free concentration. The free concentration predicted by the mathematical model was suitable for levofloxacin and linezolid, whereas the real free concentration should be measured for rifampicin. Further investigations should be carried out to investigate the benefit of using free concentration for levofloxacin, linezolid and rifampicin, particularly in the critical period of active tuberculosis associated with hypoalbuminaemia.

Limited sampling strategies for therapeutic drug monitoring of anti-tuberculosis medications: A systematic review of their feasibility and clinical utility

Therapeutic drug monitoring (TDM) is recommended for medications with high inter-individual variability, narrow therapeutic index drugs, possible drug-drug interactions, drug toxicity, and subtherapeutic concentrations, as well as to assess noncompliance. The area under the plasma concentration-time curve (AUC) is a significant pharmacokinetic parameter since it calculates the drug's total systematic exposure in the body. However, multiple blood samples from the patient are required to calculate the area under the curve, which is inconvenient for both the patient and the healthcare professional. To alleviate the issue, the limited sampling strategy (LSS) was devised, in which sampling is minimized while obtaining complete and precise findings to anticipate the area under the curve. One can reduce costs, labor, and discomfort for patients and healthcare workers by applying this limited sampling strategy. This article examines a systematic evaluation of all the limited sampling done in anti-tuberculosis (anti-TB) medications resulting from the literature search of several research papers. This article also briefly describes the two methodologies: Multiple regression analysis (MRA) and the Bayesian approach used to develop a limited sampling strategy model. Anti-TB medications have been found to have considerable inter-individual variability, and isoniazid has a narrow therapeutic index, both of which are criteria for therapeutic drug monitoring. To avoid multi-drug resistance and therapy failure, it is proposed that limited sampling strategy-based therapeutic drug monitoring of anti-TB medications be undertaken to generate an individualized dose regimen, particularly for individuals at high risk of treatment failure or delayed response.

Population pharmacokinetics and limited sampling strategies of polymyxin B in critically ill patients

OBJECTIVES

To characterize the pharmacokinetics (PK) of polymyxin B in Chinese critically ill patients. The factors significantly affecting PK parameters are identified, and a limited sampling strategy for therapeutic drug monitoring of polymyxin B is explored.

METHODS

Thirty patients (212 samples) were included in a population PK analysis. A limited sampling strategy was developed using Bayesian estimation, multiple linear regression and modified integral equations. Non-linear mixed-effects models were developed using Phoenix NLME software.

RESULTS

A two-compartment population PK model was used to describe polymyxin B PK. Population estimates of the volumes of central compartment distribution (V) and peripheral compartment distribution (V2), central compartment clearance (CL) and intercompartmental clearance (Q) were 7.857 L, 12.668 L, 1.672 L/h and 7.009 L/h. Continuous renal replacement therapy (CRRT) significantly affected CL, and body weight significantly affected CL and Q. The AUC0-12h of polymyxin B in patients with CRRT was significantly lower than in patients without CRRT. CL and Q increased with increasing body weight. A limited sampling strategy was suggested using a two-sample scheme with plasma at 0.5h and 8h after the end of infusion (C0.5 and C8) for therapeutic drug monitoring in the clinic.

CONCLUSIONS

A dosing regimen should be based on body weight and the application of CRRT. A two-sample strategy for therapeutic drug monitoring could facilitate individualized treatment with polymyxin B in critically ill patients.

Tuberkulose im Erwachsenenalter

Die Tuberkulose ist in Deutschland eine seltene, überwiegend gut behandelbare Erkrankung. Weltweit ist sie eine der häufigsten Infektionserkrankungen mit ca. 10 Millionen Neuerkrankungen/Jahr. Auch bei einer niedrigen Inzidenz in Deutschland bleibt Tuberkulose insbesondere aufgrund der internationalen Entwicklungen und Migrationsbewegungen eine wichtige Differenzialdiagnose. In Deutschland besteht, aufgrund der niedrigen Prävalenz der Erkrankung und der damit verbundenen abnehmenden klinischen Erfahrung, ein Informationsbedarf zu allen Aspekten der Tuberkulose und ihrer Kontrolle. Diese Leitlinie umfasst die mikrobiologische Diagnostik, die Grundprinzipien der Standardtherapie, die Behandlung verschiedener Organmanifestationen, den Umgang mit typischen unerwünschten Arzneimittelwirkungen, die Besonderheiten in der Diagnostik und Therapie resistenter Tuberkulose sowie die Behandlung bei TB-HIV-Koinfektion. Sie geht darüber hinaus auf Versorgungsaspekte und gesetzliche Regelungen wie auch auf die Diagnosestellung und präventive Therapie einer latenten tuberkulösen Infektion ein. Es wird ausgeführt, wann es der Behandlung durch spezialisierte Zentren bedarf.

Die Aktualisierung der S2k-Leitlinie „Tuberkulose im Erwachsenenalter“ soll allen in der Tuberkuloseversorgung Tätigen als Richtschnur für die Prävention, die Diagnose und die Therapie der Tuberkulose dienen und helfen, den heutigen Herausforderungen im Umgang mit Tuberkulose in Deutschland gewachsen zu sein.

Key Factors in Effective Patient-Tailored Dosing of Fluoroquinolones in Urological Infections: Interindividual Pharmacokinetic and Pharmacodynamic Variability

Fluoroquinolones (FQs) are a critical group of antimicrobials prescribed in urological infections as they have a broad antimicrobial spectrum of activity and a favorable tissue penetration at the site of infection. However, their clinical practice is not problem-free of treatment failure, risk of emergence of resistance, and rare but important adverse effects. Due to their critical role in clinical improvement, understanding the dose-response relation is necessary to optimize the effectiveness of FQs therapy, as it is essential to select the right antibiotic at the right dose for the right duration in urological infections. The aim of this study was to review the published literature about inter-individual variability in pharmacological processes that can be responsible for the clinical response after empiric dose for the most commonly prescribed urological FQs: ciprofloxacin, levofloxacin, and moxifloxacin. Interindividual pharmacokinetic (PK) variability, particularly in elimination, may contribute to treatment failure. Clearance related to creatinine clearance should be specifically considered for ciprofloxacin and levofloxacin. Likewise, today, undesired interregional variability in FQs antimicrobial activity against certain microorganisms exists. FQs pharmacology, patient-specific characteristics, and the identity of the local infecting organism are key factors in determining clinical outcomes in FQs use.

Rationale and design of the CORE (COrticosteroids REvised) study: protocol

INTRODUCTION

Corticosteroids are an important pillar in many anti-inflammatory and immunosuppressive treatment regimens and are available in natural and synthetic forms, which are considered equipotent if clinical bioequivalence data are used. Current clinical bioequivalence data are however based on animal studies or studies with subjective endpoints. Furthermore, advancement in steroid physiology with regard to metabolism, intracellular handling and receptor activation have not yet been incorporated. Therefore, this study aims to re-examine the clinical bioequivalence and dose effects of the most widely used synthetic corticosteroids, prednisolone and dexamethasone.

METHODS AND ANALYSIS

In this double-blind, randomised cross-over clinical trial, 24 healthy male and female volunteers aged 18-75 years, will be included. All volunteers will randomly receive either first a daily dose of 7.5 mg prednisolone for 1 week, immediately followed by a daily dose of 30 mg prednisolone for 1 week, or first a presumed clinical bioequivalent dose of 1.125 mg dexamethasone per day, immediately followed by 4.5 mg of dexamethasone per day for 1 week. After a wash-out period of 4-8 weeks, the other treatment will be applied. The primary study endpoint is the difference in free cortisol excretion in 24 hours urine. Secondary endpoints will include differences in immunological parameters, blood pressure and metabolic measurements.

ETHICS AND DISSEMINATION

This study has been approved by the Medical Ethics Committee of the University Medical Center Groningen (METC 2020.398). The results of this study will be submitted for publication in peer-reviewed journals.

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov (Identifier: NCT04733144), and in the Dutch trial registry (NL9138).

Therapeutic Drug Monitoring of Antibiotics: Defining the Therapeutic Range

PURPOSE

In the present narrative review, the authors aimed to discuss the relationship between the pharmacokinetic/pharmacodynamic (PK/PD) of antibiotics and clinical response (including efficacy and toxicity). In addition, this review describes how this relationship can be applied to define the therapeutic range of a particular antibiotic (or antibiotic class) for therapeutic drug monitoring (TDM).

METHODS

Relevant clinical studies that examined the relationship between PK/PD of antibiotics and clinical response (efficacy and response) were reviewed. The review (performed for studies published in English up to September 2021) assessed only commonly used antibiotics (or antibiotic classes), including aminoglycosides, beta-lactam antibiotics, daptomycin, fluoroquinolones, glycopeptides (teicoplanin and vancomycin), and linezolid. The best currently available evidence was used to define the therapeutic range for these antibiotics.

RESULTS

The therapeutic range associated with maximal clinical efficacy and minimal toxicity is available for commonly used antibiotics, and these values can be implemented when TDM for antibiotics is performed. Additional data are needed to clarify the relationship between PK/PD indices and the development of antibiotic resistance.

CONCLUSIONS

TDM should only be regarded as a means to achieve the main goal of providing safe and effective antibiotic therapy for all patients. The next critical step is to define exposures that can prevent the development of antibiotic resistance and include these exposures as therapeutic drug monitoring targets.

Therapeutic Drug Monitoring of Anti-infective Drugs: Implementation Strategies for 3 Different Scenarios

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.

Population pharmacokinetic model and limited sampling strategy for clozapine using plasma and dried blood spot samples

BACKGROUND

To improve efficacy, therapeutic drug monitoring is often used in clozapine therapy. Trough level monitoring is regular, but trough levels provide limited information about the pharmacokinetics of clozapine and exposure in time. The area under the concentration time curve (AUC) is generally valued as better marker of drug exposure in time but calculating AUC needs multiple sampling. An alternative approach is a limited sampling scheme in combination with a population pharmacokinetic model meant for Bayesian forecasting. Furthermore, multiple venepunctions can be a burden for the patient, whereas collecting samples by means of dried blood spot (DBS) sampling can facilitate AUC-monitoring, making it more patient friendly.

OBJECTIVE

Development of a population pharmacokinetic model and limited sampling strategy for estimating AUC_0-12h (a twice-daily dosage regimen) and AUC_0-24h (a once-daily dosage regimen) of clozapine, using a combination of results from venepunctions and DBS sampling.

METHOD

From 15 schizophrenia patients, plasma and DBS samples were obtained before administration and 2, 4, 6, and 8 h after clozapine intake. MwPharm^® pharmacokinetic software was used to parameterize a population pharmacokinetic model and calculate limited sampling schemes.

RESULTS

A three-point sampling strategy with samples at 2, 6, and 8 h after clozapine intake gave the best estimation of the clozapine AUC_0-12h and at 4, 10, and 11 h for the AUC_0-24h. For clinical practice, however, a two-point sampling strategy with sampling points at 2 and 6 h was sufficient to estimate AUC_0-12h and at 4 and 11 h for AUC_0-24h.

CONCLUSION

A pharmacokinetic model with a two-time point limited sampling strategy meant for Bayesian forecasting using DBS sampling gives a better prediction of the clozapine exposure in time, expressed as AUC, compared to trough level monitoring. This limited sampling strategy might therefore provide a more accurate prediction of effectiveness and occurrence of side effects compared to trough level monitoring. The use of DBS samples also makes the collection of clozapine samples easier and wider applicable.

Development of a dosing-adjustment tool for fluoroquinolones in osteoarticular infections: The Fluo-pop study

Fluoroquinolones efficacy depend on both the drug exposure and the level of drug resistance of the bacteria responsible for the infection. Specifically for the Staphylococcus species, which is the microorganism mainly involved in osteoarticular infections (OAI), in-vitro data reported that an AUC/MIC ratio above 115 h maximizes drug efficacy. However, data on OAI patients are lacking and a simple approach to access AUCs is still a clinical issue. We conducted a prospective, single-center study in 30 OAI patients hospitalized in the Rennes University Hospital to model ofloxacin pharmacokinetics and to define a limited sampling strategy (LSS) suitable for ofloxacin and levofloxacin treatments. Modeling was conducted with the Monolix software. The final model was externally validated using levofloxacin data. Monte-Carlo simulations were used to evaluate the probability of target attainment (PTA) of different dosing regimens. Two hundred and ninety-seven (297) ofloxacin concentrations were available for the pharmacokinetic modeling. Ofloxacin pharmacokinetics was best described using a bicompartmental model with a first order elimination, and a transit compartment model absorption. CKD-EPI and sex explained half of ofloxacin pharmacokinetic variability. For LSS, the 0, 1 h and 3 h sampling scheme resulted in the best approach both for BID and TID dosages (R² adjusted = 91.1% and 95.0%, outliers = 4.8% and 5.0%, respectively). PTA allows choosing the best drug and dosage according to various hypotheses. A simple 3-sample protocol (pre-dose, 1 h after intake and 3 h after intake) to estimate ofloxacin and levofloxacin AUC allows optimal drug dosage for the treatment of osteoarticular infections.

Levofloxacin pharmacokinetics in saliva as measured by a mobile microvolume UV spectrophotometer among people treated for rifampicin-resistant TB in Tanzania

Background

Early detection and correction of low fluoroquinolone exposure may improve treatment of MDR-TB.

Objectives

To explore a recently developed portable, battery-powered, UV spectrophotometer for measuring levofloxacin in saliva of people treated for MDR-TB.

Methods

Patients treated with levofloxacin as part of a regimen for MDR-TB in Northern Tanzania had serum and saliva collected concurrently at 1 and 4 h after 2 weeks of observed levofloxacin administration. Saliva levofloxacin concentrations were quantified in the field via spectrophotometry, while serum was analysed at a regional laboratory using HPLC. A Bayesian population pharmacokinetics model was used to estimate the area under the concentration–time curve (AUC_0–24). Subtarget exposures of levofloxacin were defined by serum AUC_0–24 <80 mg·h/L. The study was registered at Clinicaltrials.gov with clinical trial identifier NCT04124055.

Results

Among 45 patients, 11 (25.6%) were women and 16 (37.2%) were living with HIV. Median AUC_0–24 in serum was 140 (IQR = 102.4–179.09) mg·h/L and median AUC_0–24 in saliva was 97.10 (IQR = 74.80–121.10) mg·h/L. A positive linear correlation was observed with serum and saliva AUC_0–24, and a receiver operating characteristic curve constructed to detect serum AUC_0–24 below 80 mg·h/L demonstrated excellent prediction [AUC 0.80 (95% CI = 0.62–0.94)]. Utilizing a saliva AUC_0–24 cut-off of 91.6 mg·h/L, the assay was 88.9% sensitive and 69.4% specific in detecting subtarget serum AUC_0–24 values, including identifying eight of nine patients below target.

Conclusions

Portable UV spectrophotometry as a point-of-care screen for subtarget levofloxacin exposure was feasible. Use for triage to other investigation or personalized dosing strategy should be tested in a randomized study.

Effect of serum isoniazid level on treatment outcomes among tuberculosis patients with slow response - A retrospective cohort study

BACKGROUND

In this study, we investigate the effects of low serum TB drug level on treatment outcome among TB patients with slow response in South Korea, where the prevalence of rapid acetylator is relatively high.

METHODS

Among the pulmonary TB patients whose treatment outcomes were reported between 2014 and 2018 at Incheon St. Mary hospital, those who underwent TDM because of delayed culture conversion or reversion were included. Primary outcome was microbiological failure defined as (1) positive sputum culture after 120 days of treatment, or (2) culture-confirmed relapse within one year after treatment completion. Patients with culture conversion within 120 days and no relapse were classified as the final conversion group. Clinical characteristics and serum drug concentration at 2 h after administration (C_2hr) were compared between those two groups.

RESULTS

A total of 55 pulmonary TB patients were included. Prevalence of subtherapeutic range of C_2hr for isoniazid and rifampin was 78.2% and 21.8%, respectively. With one year of follow-up, 21 cases were classified as the microbiological failure group, and 34 cases as the final conversion group. In a multivariable logistic regression model for predicting microbiological failure, C_2hr of isoniazid was the most significant predictor after adjusting for the effects of age and sex (adjusted odds ratio, 0.29; p = 0.009). In a tree-based classification model, C_2hr of isoniazid with cutoff level 2.5 μg/ml was the most important variable for predicting microbiological failure.

CONCLUSIONS

Low serum isoniazid level was related to poor treatment outcomes among the TB patients with slow response.

A mobile microvolume UV/visible light spectrophotometer for the measurement of levofloxacin in saliva

INTRODUCTION

Therapeutic drug monitoring (TDM) for personalized dosing of fluoroquinolones has been recommended to optimize efficacy and reduce acquired drug resistance in the treatment of MDR TB. Therefore, the aim of this study was to develop a simple, low-cost, robust assay for TDM using mobile UV/visible light (UV/VIS) spectrophotometry to quantify levofloxacin in human saliva at the point of care for TB endemic settings.

METHODS

All experiments were performed on a mobile UV/VIS spectrophotometer. The levofloxacin concentration was quantified by using the amplitude of the second-order spectrum between 300 and 400 nm of seven calibrators. The concentration of spiked samples was calculated from the spectrum amplitude using linear regression. The method was validated for selectivity, specificity, linearity, accuracy and precision. Drugs frequently co-administered were tested for interference.

RESULTS

The calibration curve was linear over a range of 2.5-50.0 mg/L for levofloxacin, with a correlation coefficient of 0.997. Calculated accuracy ranged from -5.2% to 2.4%. Overall precision ranged from 2.1% to 16.1%. Application of the Savitsky-Golay method reduced the effect of interferents on the quantitation of levofloxacin. Although rifampicin and pyrazinamide showed analytical interference at the lower limit of quantitation of levofloxacin concentrations, this interference had no implication on decisions regarding the levofloxacin dose.

CONCLUSIONS

A simple UV/VIS spectrophotometric method to quantify levofloxacin in saliva using a mobile nanophotometer has been validated. This method can be evaluated in programmatic settings to identify patients with low levofloxacin drug exposure to trigger personalized dose adjustment.

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.

Population Pharmacokinetic Models of Antituberculosis Drugs in Patients: A Systematic Critical Review

BACKGROUND

Tuberculosis (TB) remains one of the most important infectious diseases. Population pharmacokinetic (pop-PK) models are widely used to individualize dosing regimens of several antibiotics, but their application in anti-TB drug studies is scant. The aim of this study was to provide an insight regarding the status of pop-PK for these drugs and to compare results obtained through both parametric and nonparametric approaches to design precise dosage regimens.

METHODS

First, a systematic approach was implemented, searching in PubMed and Google Scholar. Articles that did not include human patients, that lacked an explicit structural model, that analyzed drugs inactive against M. tuberculosis, or were without full-text access, were excluded. Second, the PK parameters were summarized and categorized as parametric versus nonparametric results. Third, a Monte Carlo simulation was performed in Pmetrics using the results of both groups, and an error term was built to describe the imprecision of each PK modeling approach.

RESULTS

Thirty-three articles reporting at least 1 pop-PK model of 19 anti-TB drug were found; 46 different models including PK parameter estimates and their relevant covariates were also reported. Only 9 models were based on nonparametric approaches. Rifampin was the drug most studied, but only using parametric approaches. The simulations showed that nonparametric approaches improve the error term compared with parametric approaches.

CONCLUSIONS

More and better models, ideally using nonparametric approaches linked with clear pharmacodynamic goals, are required to optimize anti-TB drug dosing, as recommended in the WHO End TB strategy.

Therapeutic drug monitoring in patients with tuberculosis and concurrent medical problems

INTRODUCTION

Therapeutic drug monitoring (TDM) has been recommended for treatment optimization in tuberculosis (TB) but is only is used in certain countries e.g. USA, Germany, the Netherlands, Sweden and Tanzania. Recently, new drugs have emerged and PK studies in TB are continuing, which contributes further evidence for TDM in TB. The aim of this review is to provide an update on drugs used in TB, treatment strategies for these drugs, and TDM to support broader implementation.

AREAS COVERED

This review describes the different drug classes used for TB, multidrug-resistant TB (MDR-TB) and extensively drug-resistant TB (XDR-TB), along with their pharmacokinetics, dosing strategies, TDM and sampling strategies. Moreover, the review discusses TDM for patient TB and renal or liver impairment, patients co-infected with HIV or hepatitis, and special patient populations - children and pregnant women.

EXPERT OPINION

TB treatment has a long history of using 'one size fits all.' This has contributed to treatment failures, treatment relapses, and the selection of drug-resistant isolates. While challenging in resource-limited circumstances, TDM offers the clinician the opportunity to individualize and optimize treatment early in treatment. This approach may help to refine treatment and thereby reduce adverse effects and poor treatment outcomes. Funding, training, and randomized controlled trials are needed to advance the use of TDM for patients with TB.

Influence of Renal Function and Age on the Pharmacokinetics of Levofloxacin in Patients with Bone and Joint Infections

Despite its efficacy and toxicity being exposure-related, levofloxacin pharmacokinetics in patients with bone and joint infections has been poorly described to date, so the possible need for a dose adjustment is unknown in this population. A prospective population pharmacokinetic study was conducted in 59 patients to answer this question. The final model consisted of a one-compartment model with first-order absorption and elimination. Mean parameter estimates (% interindividual variability) were 0.895 h^-1 for the absorption rate constant (Ka), 6.10 L/h (40%) for the apparent clearance (CL/F), 90.6 L (25%) for the apparent distribution volume (V/F). Age and glomerular filtration rate (GFR), estimated by the modification of diet in renal disease formula, were related to CL/F by power models, and CL/F was found to increase for increasing GFR and decreasing age. For a similar GFR, the simulated area under the curve (AUC) was 55% higher in 70 years-old patients compared to 30 year-old patients. Based on this model, a 750 mg dose should provide an optimal exposure (AUC/ minimum inhibitory concentration (MIC) ≥100), with the possible exception of patients older than 60 years and with GFR <70 mL/min/m² who may necessitate a dose reduction, and patients with infections caused by bacteria with MIC close to 1 mg/L who may need an increase in the dose.

Prospective evaluation of improving fluoroquinolone exposure using centralised therapeutic drug monitoring (TDM) in patients with tuberculosis (PERFECT): a study protocol of a prospective multicentre cohort study

INTRODUCTION

Global multidrug-resistant tuberculosis (MDR-TB) treatment success rates remain suboptimal. Highly active WHO group A drugs moxifloxacin and levofloxacin show intraindividual and interindividual pharmacokinetic variability which can cause low drug exposure. Therefore, therapeutic drug monitoring (TDM) of fluoroquinolones is recommended to personalise the drug dosage, aiming to prevent the development of drug resistance and optimise treatment. However, TDM is considered laborious and expensive, and the clinical benefit in MDR-TB has not been extensively studied. This observational multicentre study aims to determine the feasibility of centralised TDM and to investigate the impact of fluoroquinolone TDM on sputum conversion rates in patients with MDR-TB compared with historical controls.

METHODS AND ANALYSIS

Patients aged 18 years or older with sputum smear and culture-positive pulmonary MDR-TB will be eligible for inclusion. Patients receiving TDM using a limited sampling strategy (t=0 and t=5 hours) will be matched to historical controls without TDM in a 1:2 ratio. Sample analysis and dosing advice will be performed in a centralised laboratory. Centralised TDM will be considered feasible if >80% of the dosing recommendations are returned within 7 days after sampling and 100% within 14 days. The number of patients who are sputum smear and culture-negative after 2 months of treatment will be determined in the prospective TDM group and will be compared with the control group without TDM to determine the impact of TDM.

ETHICS AND DISSEMINATION

Ethical clearance was obtained by the ethical review committees of the 10 participating hospitals according to local procedures or is pending (online supplementary file 1). Patients will be included after obtaining written informed consent. We aim to publish the study results in a peer-reviewed journal.

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov Registry (NCT03409315).

Population Pharmacokinetics and Limited Sampling Strategy for Therapeutic Drug Monitoring of Polymyxin B in Chinese Patients With Multidrug-Resistant Gram-Negative Bacterial Infections

Polymyxin B is used as a last therapeutic option for the treatment of multidrug-resistant Gram-negative bacterial infections. This study aimed to develop a population pharmacokinetic model and limited sampling strategy, a method to estimate the area under the concentration curve (AUC) by using a limited number of samples, to assist therapeutic drug monitoring of polymyxin B in Chinese patients. Population pharmacokinetic analysis was performed using Phoenix^® NLME with data obtained from 46 adult patients at steady state. Various demographic variables were investigated as potential covariates for population pharmacokinetic modeling. The limited sampling strategies based on the Bayesian approach and multiple linear regression were validated using the intraclass correlation coefficient and Bland-Altman analysis. As a result, the data was described by a two-compartment population pharmacokinetic model. Through the modeling, creatinine clearance was found to be a statistically significant covariate influencing polymyxin B clearance. The limited sampling strategies showed the two-point model (C_0h and C_2h) could predict polymyxin B exposure with good linear relativity (r² > 0.98), and the four-point model (C_1h, C1_.5h, C_4h, and C_8h) performed best in predicting polymyxin B AUC (r² > 0.99). In conclusion, this study successfully developed a population pharmacokinetic model and limited sampling strategies that could be applied in clinical practice to assist in therapeutic drug monitoring of polymyxin B in Chinese patients.

Precision and personalized medicine and anti-TB treatment: Is TDM feasible for programmatic use?

Therapeutic Drug Monitoring (TDM) is increasingly recommended to ensure the correct drug dose thereby minimizing adverse events and maximizing regimen efficacy. To facilitate implementation in TB programs, a framework for TDM is urgently needed. TDM is only useful for dose optimization if a patient is on an appropriate regimen guided by drug susceptibility testing. TDM using a targeted approach selecting patients with risk factors for suboptimal drug exposure (e.g. diabetes) or not responding to treatment for drugs with a clear concentration-response relationship may provide the best value for money. Semiquantitative point-of-care tests for detection of low or high drug concentration should be implemented at community level while quantitative assays can be performed at regional or central level. Expanding PK/PD research followed by clinical trials including both clinical outcome as well as cost-effectiveness will increase the level of evidence supporting TDM.

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.