Intermediate Susceptibility Dose-Dependent Breakpoints For High-Dose Rifampin, Isoniazid, and Pyrazinamide Treatment in Multidrug-Resistant Tuberculosis Programs

Population Pharmacokinetics and Significant Under-Dosing of Anti-Tuberculosis Medications in People with HIV and Critical Illness

Critical illness from tuberculosis (TB) bloodstream infection results in a high case fatality rate for people living with human immunodeficiency virus (HIV). Critical illness can lead to altered pharmacokinetics and suboptimal drug exposures. We enrolled adults living with HIV and hospitalized with sepsis, with and without meningitis, in Mbarara, Uganda that were starting first-line anti-TB therapy. Serum was collected two weeks after enrollment at 1-, 2-, 4-, and 6-h post-dose and drug concentrations quantified by validated LC-MS/MS methods. Non-compartmental analyses were used to determine total drug exposure, and population pharmacokinetic modeling and simulations were performed to determine optimal dosages. Eighty-one participants were enrolled. Forty-nine completed pharmacokinetic testing: 18 (22%) died prior to testing, 13 (16%) were lost to follow-up and one had incomplete testing. Isoniazid had the lowest serum attainment, with only 4.1% achieving a target exposure over 24 h (AUC_0–24) of 52 mg·h/L despite appropriate weight-based dosing. Simulations to reach target AUC_0–24 found necessary doses of rifampin of 1800 mg, pyrazinamide of 2500–3000 mg, and for isoniazid 900 mg or higher. Given the high case fatality ratio of TB-related critical illness in this population, an early higher dose anti-TB therapy should be trialed.

The Role of PK/PD Analysis in the Development and Evaluation of Antimicrobials

Pharmacokinetic/pharmacodynamic (PK/PD) analysis has proved to be very useful to establish rational dosage regimens of antimicrobial agents in human and veterinary medicine. Actually, PK/PD studies are included in the European Medicines Agency (EMA) guidelines for the evaluation of medicinal products. The PK/PD approach implies the use of in vitro, ex vivo, and in vivo models, as well as mathematical models to describe the relationship between the kinetics and the dynamic to determine the optimal dosing regimens of antimicrobials, but also to establish susceptibility breakpoints, and prevention of resistance. The final goal is to optimize therapy in order to maximize efficacy and minimize side effects and emergence of resistance. In this review, we revise the PK/PD principles and the models to investigate the relationship between the PK and the PD of antibiotics. Additionally, we highlight the outstanding role of the PK/PD analysis at different levels, from the development and evaluation of new antibiotics to the optimization of the dosage regimens of currently available drugs, both for human and animal use.

Comparison of Rifamycins for Efficacy Against Mycobacterium avium Complex and Resistance Emergence in the Hollow Fiber Model System

Rifamycins are integral part of the combination regimen for treatment of pulmonary Mycobacterium avium-complex [MAC] infection, but different practitioners prefer different rifamycins. The objective of the study was to compare microbial kill and resistance emergence of rifamycins using principles of pharmacokinetics/pharmacodynamics. First, we identified rifamycin MICs in 20 MAC isolates from patients followed by concentration-response studies in test-tubes. Next, we examined efficacy and resistance suppression of three doses of each rifamycin in the hollow fiber system model of pulmonary MAC [HFS-MAC], mimicking human like concentration-time profile of the drugs. HFS-MAC units were repetitively sampled for total and drug-resistant MAC burden and for drug concentration measurements. Inhibitory sigmoid E max model, linear regression, and analysis of variance was used for data analysis. For rifabutin 90% of isolates had MIC ≤ 0.125 mg/L while for both rifampin and rifapentine this was ≤2.0 mg/L. There was no statistically significant difference (p > 0.05) in maximal kill and effective concentration mediating 50% of the bacterial kill among three rifamycins in the static concentration experiment. In the HFS-MAC, the bactericidal kill (day 0-4) for rifampin was 0.89 (95% Confidence Interval (CI): 0.43-1.35), for rifapentine was 1.05 (95% CI: 0.08-1.23), and for rifabutin was 0.92 (95% CI: 0.61-1.24) log10 CFU/ml, respectively. Rifamycins monotherapy failed after just 4-days of treatment and entire MAC population was drug resistant on day 26 of the study. There was no dose dependent difference in MAC kill or resistance suppression among the three rifamycins tested in the HFS-MAC. Therefore, replacing one rifamycin, due to emergence of drug-resistance, with other may not be beneficial in clinical setting.

A Model-Informed Method for the Purpose of Precision Dosing of Isoniazid in Pulmonary Tuberculosis

Background and Objective

This study aimed to develop and evaluate a population pharmacokinetic model and limited sampling strategy for isoniazid to be used in model-based therapeutic drug monitoring.

Methods

A population pharmacokinetic model was developed based on isoniazid and acetyl-isoniazid pharmacokinetic data from seven studies with in total 466 patients from three continents. Three limited sampling strategies were tested based on the available sampling times in the dataset and practical considerations. The tested limited sampling strategies sampled at 2, 4, and 6 h, 2 and 4 h, and 2 h after dosing. The model-predicted area under the concentration–time curve from 0 to 24 h (AUC₂₄) and the peak concentration from the limited sampling strategies were compared to predictions using the full pharmacokinetic curve. Bias and precision were assessed using the mean error (ME) and the root mean square error (RMSE), both expressed as a percentage of the mean model-predicted AUC₂₄ or peak concentration on the full pharmacokinetic curve.

Results

Performance of the developed model was acceptable and the uncertainty in parameter estimations was generally low (the highest relative standard error was 39% coefficient of variation). The limited sampling strategy with sampling at 2 and 4 h was determined as most suitable with an ME of 1.1% and RMSE of 23.4% for AUC₂₄ prediction, and ME of 2.7% and RMSE of 23.8% for peak concentration prediction. For the performance of this strategy, it is important that data on both isoniazid and acetyl-isoniazid are used. If only data on isoniazid are available, a limited sampling strategy using 2, 4, and 6 h can be employed with an ME of 1.7% and RMSE of 20.9% for AUC₂₄ prediction, and ME of 1.2% and RMSE of 23.8% for peak concentration prediction.

Conclusions

A model-based therapeutic drug monitoring strategy for personalized dosing of isoniazid using sampling at 2 and 4 h after dosing was successfully developed. Prospective evaluation of this strategy will show how it performs in a clinical therapeutic drug monitoring setting.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40262-020-00971-2.

Improved Outcomes With High-dose Isoniazid in Multidrug-resistant Tuberculosis Treatment in Haiti

We report outcomes for a cohort of patients with multidrug-resistant tuberculosis who received high-dose isoniazid in Haiti. Patients who received high-dose isoniazid had a faster time to culture conversion and higher odds of successful outcome, despite high-level isoniazid resistance. This suggests high-dose isoniazid may have effectiveness even with phenotypic resistance.

Association Between the Phenotype and Genotype of Isoniazid Resistance Among Mycobacterium tuberculosis Isolates in Thailand

Purpose

The emergence of isoniazid-resistant tuberculosis (HR-TB) is a global public health problem, causing treatment failure and high mortality rates. This study aimed to determine the minimal inhibitory concentration (MIC) of isoniazid and detect the gene mutation in HR-TB and any association between the level of isoniazid resistance and gene mutation.

Methods

We collected 74 clinical HR-TB isolates from two tertiary-care centers in Thailand. MICs were established using broth macrodilution. A line probe assay (LPA) was used to detect gene mutations that confer resistance to isoniazid, rifampicin, aminoglycosides, and fluoroquinolones.

Results

Sixty-one (82.4%) isolates were monoresistant to isoniazid and 44 (72.1%) were highly resistant to isoniazid. From the clinical isolates, the range of isoniazid MICs was 0.4–16 μg/mL. The katG S315T gene mutation was the prominent mutation in both isoniazid-monoresistant TB (70.5%) and multidrug-resistant TB (72.7%) isolates. The positive predictive value (PPV) of katG was 100% in detecting high levels of isoniazid resistance. The PPV of the inhA mutation was 93.8% in detecting low levels of isoniazid resistance. Five isolates (6.8%) exhibited low-level phenotypic resistance, whereas an LPA failed to detect an isoniazid gene mutation. Our study found one HR-TB isolate with a gyrA fluoroquinolone-resistant gene mutation.

Conclusion

Most HR-TB isolates had high isoniazid-resistance levels associated with the katG gene mutation. High-dose isoniazid should be used with caution in patients with HR-TB. Early detection of drug resistance by genotypic assay can help determine an appropriate regimen.

Gatifloxacin Pharmacokinetics/Pharmacodynamics-based Optimal Dosing for Pulmonary and Meningeal Multidrug-resistant Tuberculosis

Background

Gatifloxacin is used for the treatment of multidrug-resistant tuberculosis (MDR-TB). The optimal dose is unknown.

Methods

We performed a 28-day gatifloxacin hollow-fiber system model of tuberculosis (HFS-TB) study in order to identify the target exposures associated with optimal kill rates and resistance suppression. Monte Carlo experiments (MCE) were used to identify the dose that would achieve the target exposure in 10000 adult patients with meningeal or pulmonary MDR-TB. The optimal doses identified were validated using probit analyses of clinical data from 2 prospective clinical trials of patients with pulmonary and meningeal tuberculosis. Classification and regression-tree (CART) analyses were used to identify the gatifloxacin minimum inhibitory concentration (MIC) below which patients failed or relapsed on combination therapy.

Results

The target exposure associated with optimal microbial kill rates and resistance suppression in the HFS-TB was a 0-24 hour area under the concentration-time curve-to-MIC of 184. MCE identified an optimal gatifloxacin dose of 800 mg/day for pulmonary and 1200 mg/day for meningeal MDR-TB, and a clinical susceptibility breakpoint of MIC ≤ 0.5 mg/L. In clinical trials, CART identified that 79% patients failed therapy if MIC was >2 mg/L, but 98% were cured if MIC was ≤0.5 mg/L. Probit analysis of clinical data demonstrated a >90% probability of a cure in patients if treated with 800 mg/day for pulmonary tuberculosis and 1200 mg/day for meningeal tuberculosis. Doses ≤400 mg/day were suboptimal.

Conclusions

Gatifloxacin doses of 800 mg/day and 1200 mg/day are recommended for pulmonary and meningeal MDR-TB treatment, respectively. Gatifloxacin has a susceptible dose-dependent zone at MICs 0.5-2 mg/L.

Current research toward optimizing dosing of first-line antituberculosis treatment

Introduction: Drug concentrations in tuberculosis patients on standard regimens vary widely with clinically important consequences.

Areas covered: We review the available literature identifying factors correlated with pharmacokinetic variability of antituberculosis drugs. Based on population pharmacokinetic models and the weight, height, and sex distributions in a large data base of African tuberculosis patients, we propose simplified weight-based doses of the available fixed dose combination(FDC) for adults with drug susceptible tuberculosis. Emerging studies will support optimized weight-based dosing for children. Other sources of important pharmacokinetic variability include genetic variants, drug-drug interactions, formulation quality, and methods of preparation and administration.

Expert commentary: Optimized weight band-based dosing will result in more equitable distribution of drug exposures by weight. The use of high doses of isoniazid in patients with drug-resistant tuberculosis would be safer and more effective if a feasible test was developed to allow stratified dosing according to acetylator type. There is an urgent need for more suitable formulations of many second-line drugs for children. The adoption of new technologies and efficient FDC design may allow further advances for patients and treatment programs. Lastly, current efforts to ensure adequate quality of antituberculosis drug products are not preventing the use of substandard products to treat patients with tuberculosis.

Levofloxacin Pharmacokinetics/Pharmacodynamics, Dosing, Susceptibility Breakpoints, and Artificial Intelligence in the Treatment of Multidrug-resistant Tuberculosis

Background

Levofloxacin is used for the treatment of multidrug-resistant tuberculosis; however the optimal dose is unknown.

Methods

We used the hollow fiber system model of tuberculosis (HFS-TB) to identify 0-24 hour area under the concentration-time curve (AUC0-24) to minimum inhibitory concentration (MIC) ratios associated with maximal microbial kill and suppression of acquired drug resistance (ADR) of Mycobacterium tuberculosis (Mtb). Levofloxacin-resistant isolates underwent whole-genome sequencing. Ten thousands patient Monte Carlo experiments (MCEs) were used to identify doses best able to achieve the HFS-TB-derived target exposures in cavitary tuberculosis and tuberculous meningitis. Next, we used an ensemble of artificial intelligence (AI) algorithms to identify the most important predictors of sputum conversion, ADR, and death in Tanzanian patients with pulmonary multidrug-resistant tuberculosis treated with a levofloxacin-containing regimen. We also performed probit regression to identify optimal levofloxacin doses in Vietnamese tuberculous meningitis patients.

Results

In the HFS-TB, the AUC0-24/MIC associated with maximal Mtb kill was 146, while that associated with suppression of resistance was 360. The most common gyrA mutations in resistant Mtb were Asp94Gly, Asp94Asn, and Asp94Tyr. The minimum dose to achieve target exposures in MCEs was 1500 mg/day. AI algorithms identified an AUC0-24/MIC of 160 as predictive of microbiologic cure, followed by levofloxacin 2-hour peak concentration and body weight. Probit regression identified an optimal dose of 25 mg/kg as associated with >90% favorable response in adults with pulmonary tuberculosis.

Conclusions

The levofloxacin dose of 25 mg/kg or 1500 mg/day was adequate for replacement of high-dose moxifloxacin in treatment of multidrug-resistant tuberculosis.

Drug resistance mechanisms and drug susceptibility testing for tuberculosis

Tuberculosis (TB) caused by Mycobacterium tuberculosis (MTB) is the deadliest infectious disease and the associated global threat has worsened with the emergence of drug resistance, in particular multidrug-resistant TB (MDR-TB) and extensively drug-resistant TB (XDR-TB). Although the World Health Organization (WHO) End-TB Strategy advocates for universal access to antimicrobial susceptibility testing, this is not widely available and/or it is still underused. The majority of drug resistance in clinical MTB strains is attributed to chromosomal mutations. Resistance-related mutations could also exert certain fitness cost to the drug-resistant MTB strains and growth fitness could be restored by the presence of compensatory mutations. Understanding these underlying mechanisms could provide an important insight into TB pathogenesis and predict the future trend of MDR-TB global pandemic. This review covers the mechanisms of resistance in MTB and provides a comprehensive overview of current phenotypic and molecular approaches for drug susceptibility testing, with particular attention to the methods endorsed and recommended by the WHO.