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

Pharmacokinetics of Imatinib Mesylate and Development of Limited Sampling Strategies for Estimating the Area under the Concentration-Time Curve of Imatinib Mesylate in Palestinian Patients with Chronic Myeloid Leukemia

BACKGROUND AND OBJECTIVE

Imatinib is a tyrosine kinase inhibitor used in the treatment of chronic myeloid leukemia (CML). The area under the concentration-time curve (AUC) is a pharmacokinetic parameter that symbolizes overall exposure to a drug, which is correlated with complete cytogenetic and treatment responses to imatinib, as well as its side effects in patients with CML. The limited sampling strategy (LSS) is considered a sufficiently precise and practical method that can be used to estimate pharmacokinetic parameters such as AUC, without the need for frequent, costly, and inconvenient blood sampling. This study aims to investigate the pharmacokinetic parameters of imatinib, develop and validate a reliable and practical LSS for estimating imatinib AUC0-24, and determine the optimum sampling points for predicting the imatinib AUC after the administration of once-daily imatinib in Palestinian patients with CML.

METHOD

Pharmacokinetic profiles, involving six blood samples collected during a 24-h dosing interval, were obtained from 25 Palestinian patients diagnosed with CML who had been receiving imatinib for at least 7 days and had reached a steady-state level. Imatinib AUC0-24 was calculated using the trapezoidal rule, and linear regression analysis was performed to assess the relationship between measured AUC0-24 and concentrations at each sampling time. All developed models were analyzed to determine their effectiveness in predicting AUC0-24 and to identify the optimal sampling time. To evaluate predictive performance, two error indices were employed: the percentage of root mean squared error (% RMSE) and the mean predictive error (% MPE). Bland and Altman plots, along with mountain plots, were utilized to assess the agreement between measured and predicted AUC.

RESULTS

Among the one-timepoint estimations, predicted AUC0-24 based on concentration of imatinib at the eighth hour after administration (C8-predicted AUC0-24) demonstrated the highest correlation with the measured AUC (r2 = 0.97, % RMSE = 6.3). In two-timepoint estimations, the model consisting of C0 and C8 yielded the highest correlation between predicted and measured imatinib AUC (r2 = 0.993 and % RMSE = 3.0). In three-timepoint estimations, the combination of C0, C1, and C8 provided the most robust multilinear regression for predicting imatinib AUC0-24 (r2 = 0.996, % RMSE = 2.2). This combination also outperformed all other models in predicting AUC. The use of a two-timepoint limited sampling strategy (LSS) for predicting AUC was found to be reliable and practical. While C0/C8 exhibited the highest correlation, the use of C0/C4 could be a more practical and equally accurate choice. Therapeutic drug monitoring of imatinib based on C0 can also be employed in routine clinical practice owing to its reliability and practicality.

CONCLUSION

The LSS using one timepoint, especially C0, can effectively predict imatinib AUC. This approach offers practical benefits in optimizing dose regimens and improving adherence. However, for more precise estimation of imatinib AUC, utilizing two- or three-timepoint concentrations is recommended over relying on a single point.

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.

A Method for Evaluating Robustness of Limited Sampling Strategies—Exemplified by Serum Iohexol Clearance for Determination of Measured Glomerular Filtration Rate

In combination with Bayesian estimates based on a population pharmacokinetic model, limited sampling strategies (LSS) may reduce the number of samples required for individual pharmacokinetic parameter estimations. Such strategies reduce the burden when assessing the area under the concentration versus time curves (AUC) in therapeutic drug monitoring. However, it is not uncommon for the actual sample time to deviate from the optimal one. In this work, we evaluate the robustness of parameter estimations to such deviations in an LSS. A previously developed 4-point LSS for estimation of serum iohexol clearance (i.e., dose/AUC) was used to exemplify the effect of sample time deviations. Two parallel strategies were used: (a) shifting the exact sampling time by an empirical amount of time for each of the four individual sample points, and (b) introducing a random error across all sample points. The investigated iohexol LSS appeared robust to deviations from optimal sample times, both across individual and multiple sample points. The proportion of individuals with a relative error greater than 15% (P15) was 5.3% in the reference run with optimally timed sampling, which increased to a maximum of 8.3% following the introduction of random error in sample time across all four time points. We propose to apply the present method for the validation of LSS developed for clinical use.

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.

Has the Time Come for Systematic Therapeutic Drug Monitoring of First-Line and WHO Group A Antituberculosis Drugs?

ABSTRACT

Tuberculosis (TB) is a major global health issue, with approximately 10 million people being infected each year, and is the leading cause of mortality from infectious disease, with 1.5 million deaths a year. Optimal TB treatment requires a combination of drugs for an adequate treatment duration owing to persistent organisms, hardly accessible infection sites, and a high risk of resistance selection. Long-term therapy increases the risk of patients' loss of adherence, adverse drug reactions, and drug-drug interactions, potentially leading to treatment failure. The high interpatient variability of TB drug exposure is another point eliciting interest in therapeutic drug monitoring (TDM) to optimize treatment. Studies reporting clinically relevant exposure thresholds, which might be proposed as targets toward treatment personalization, are discussed. Practical TDM strategies have also been reported to circumvent issues related to delayed drug absorption and the need for multiple samples when evaluating the area under the curve of drug concentrations. The need for treatment individualization is further emphasized because of the development of multidrug-resistant TB or extensively drug-resistant TB. Finally, the willingness to shorten the treatment duration while maintaining success is also a driver for ensuring adequate exposure to TB drugs with TDM. The aim of the present review was to underline the role of TDM in drug-susceptible TB and World Health Organization group A TB drugs.

Clinical relevance of rifampicin-moxifloxacin interaction in isoniazid resistant/intolerant tuberculosis patients

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 centre 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 (AUC_0-24h), and attainment of AUC_0-24h/minimal inhibitory concentration (MIC) > 100 were investigated for 400 mg moxifloxacin and 600 mg rifampicin, and increased doses of moxifloxacin (600 mg) or rifampicin (900 mg). Moxifloxacin AUC_0-24h 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 AUC_0-24h/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 AUC_0-24h/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.

A Systematic Review of Multiple Linear Regression-Based Limited Sampling Strategies for Mycophenolic Acid Area Under the Concentration-Time Curve Estimation

Background and Objective

One approach of therapeutic drug monitoring in the case of mycophenolic acid (MPA) is a limited sampling strategy (LSS), which allows the evaluation of the area under the concentration–time curve (AUC) based on few concentrations. The aim of this systematic review was to review the MPA LSSs and define the most frequent time points for MPA determination in patients with different indications for mycophenolate mofetil (MMF) administration.

Methods

The literature was comprehensively searched in July 2021 using PubMed, Scopus, and Medline databases. Original articles determining multiple linear regression (MLR)-based LSSs for MPA and its free form (fMPA) were included. Studies on enteric-coated mycophenolic sodium, previously established LSS, Bayesian estimator, and different than twice a day dosing were excluded. Data were analyzed separately for (1) adult renal transplant recipients, (2) adults with other than renal transplantation indication, and (3) for pediatric patients.

Results

A total of 27, 17, and 11 studies were found for groups 1, 2, and 3, respectively, and 126 MLR-based LSS formulae (n = 120 for MPA, n = 6 for fMPA) were included in the review. Three time-point equations were the most frequent. Four MPA LSSs: 2.8401 + 5.7435 × C0 + 0.2655 × C0.5 + 1.1546 × C1 + 2.8971 × C4 for adult renal transplant recipients, 1.783 + 1.248 × C1 + 0.888 × C2 + 8.027 × C4 for adults after islet transplantation, 0.10 + 11.15 × C0 + 0.42 × C1 + 2.80 × C2 for adults after heart transplantation, and 8.217 + 3.163 × C0 + 0.994 × C1 + 1.334 × C2 + 4.183 × C4 for pediatric renal transplant recipients, plus one fMPA LSS, 34.2 + 1.12 × C1 + 1.29 × C2 + 2.28 × C4 + 3.95 × C6 for adult liver transplant recipients, seemed to be the most promising and should be validated in independent patient groups before introduction into clinical practice. The LSSs for pediatric patients were few and not fully characterized. There were only a few fMPA LSSs although fMPA is a pharmacologically active form of the drug.

Conclusions

The review includes updated MPA LSSs, e.g., for different MPA formulations (suspension, dispersible tablets), generic form, and intravenous administration for adult and pediatric patients, and emphasizes the need of individual therapeutic approaches according to MMF indication. Five MLR-based MPA LSSs might be implemented into clinical practice after evaluation in independent groups of patients. Further studies are required, e.g., to establish fMPA LSS in pediatric patients.

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 (AUC0-24). Subtarget exposures of levofloxacin were defined by serum AUC0-24 <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 AUC0-24 in serum was 140 (IQR = 102.4-179.09) mg·h/L and median AUC0-24 in saliva was 97.10 (IQR = 74.80-121.10) mg·h/L. A positive linear correlation was observed with serum and saliva AUC0-24, and a receiver operating characteristic curve constructed to detect serum AUC0-24 below 80 mg·h/L demonstrated excellent prediction [AUC 0.80 (95% CI = 0.62-0.94)]. Utilizing a saliva AUC0-24 cut-off of 91.6 mg·h/L, the assay was 88.9% sensitive and 69.4% specific in detecting subtarget serum AUC0-24 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.

Therapeutic Drug Monitoring in Non-Tuberculosis Mycobacteria Infections

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.

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.

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).

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.