Transformation Morphisms and Time-to-Extinction Analysis That Map Therapy Duration From Preclinical Models to Patients With Tuberculosis: Translating From Apples to Oranges

Ceftriaxone Efficacy for Mycobacterium avium Complex Lung Disease in the Hollow Fiber and Translation to Sustained Sputum Culture Conversion in Patients

BACKGROUND

Only 35.6%-50.8% of patients with Mycobacterium avium complex (MAC) pulmonary disease achieve sustained sputum culture conversion (SSCC) on treatment with the azithromycin-ethambutol-rifabutin standard of care (SOC). We tested the efficacy of ceftriaxone, a β-lactam with a lung-to-serum penetration ratio of 12.18-fold.

METHODS

We mimicked lung concentration-time profiles of 7 ceftriaxone once-daily doses for 28 days in the hollow fiber system model of intracellular MAC (HFS-MAC). Monte Carlo experiments were used for dose selection. We also compared once-daily ceftriaxone monotherapy to 3-drug SOC against 5 MAC clinical isolates in HFS-MAC using γ (kill) slopes, and translated to SSCC rates.

RESULTS

Ceftriaxone killed 1.02-3.82 log10 colony-forming units (CFU)/mL, at optimal dose of 2 g once-daily. Ceftriaxone killed all 5 strains below day 0 versus 2 of 5 for SOC. The median γ (95% confidence interval [CI]) was 0.49 (.47-.52) log10 CFU/mL/day for ceftriaxone and 0.38 (.34-.43) log10 CFU/mL/day for SOC. In patients, the SOC was predicted to achieve SSCC rates (CI) of 39.3% (36%-42%) at 6 months. The SOC SSCC was 50% at 8.18 (3.64-27.66) months versus 3.58 (2.20-7.23) months for ceftriaxone, shortening time to SSCC 2.35-fold.

CONCLUSIONS

Ceftriaxone is a promising agent for creation of short-course chemotherapy.

Application of the Hollow-Fiber Infection Model to Personalized Precision Dosing of Isoniazid in a Clinical Setting

BACKGROUND

The hollow-fiber infection model (HFIM) is a valuable tool for evaluating pharmacokinetics/pharmacodynamics relationships and determining the optimal antibiotic dose in monotherapy or combination therapy, but the application for personalized precision medicine in tuberculosis treatment remains limited. This study aimed to evaluate the efficacy of adjusted antibiotic doses for a tuberculosis patient using HFIM.

METHODS

Model-based Bayesian forecasting was utilized to assess the proposed reduction of the isoniazid dose from 300 mg daily to 150 mg daily in a patient with an ultra-slow-acetylation phenotype. The efficacy of the adjusted 150-mg dose was evaluated in a time-to-kill assay performed using the bacterial isolate Mycobacterium tuberculosis (Mtb) H37Ra in a HFIM that mimicked the individual pharmacokinetic profile of the patient.

RESULTS

The isoniazid concentration observed in the HFIM adequately reflected the target drug exposures simulated by the model. After 7 days of repeated dose administration, isoniazid killed 4 log10 Mtb CFU/mL in the treatment arm, while the control arm without isoniazid increased 1.6 log10 CFU/mL.

CONCLUSION

Our results provide an example of the utility of the HFIM for predicting the efficacy of specific recommended doses of anti-tuberculosis drugs in real clinical setting.

Mathematical models of drug-resistant tuberculosis lack bacterial heterogeneity: A systematic review

Drug-resistant tuberculosis (DR-TB) threatens progress in the control of TB. Mathematical models are increasingly being used to guide public health decisions on managing both antimicrobial resistance (AMR) and TB. It is important to consider bacterial heterogeneity in models as it can have consequences for predictions of resistance prevalence, which may affect decision-making. We conducted a systematic review of published mathematical models to determine the modelling landscape and to explore methods for including bacterial heterogeneity. Our first objective was to identify and analyse the general characteristics of mathematical models of DR-mycobacteria, including M. tuberculosis. The second objective was to analyse methods of including bacterial heterogeneity in these models. We had different definitions of heterogeneity depending on the model level. For between-host models of mycobacterium, heterogeneity was defined as any model where bacteria of the same resistance level were further differentiated. For bacterial population models, heterogeneity was defined as having multiple distinct resistant populations. The search was conducted following PRISMA guidelines in five databases, with studies included if they were mechanistic or simulation models of DR-mycobacteria. We identified 195 studies modelling DR-mycobacteria, with most being dynamic transmission models of non-treatment intervention impact in M. tuberculosis (n = 58). Studies were set in a limited number of specific countries, and 44% of models (n = 85) included only a single level of "multidrug-resistance (MDR)". Only 23 models (8 between-host) included any bacterial heterogeneity. Most of these also captured multiple antibiotic-resistant classes (n = 17), but six models included heterogeneity in bacterial populations resistant to a single antibiotic. Heterogeneity was usually represented by different fitness values for bacteria resistant to the same antibiotic (61%, n = 14). A large and growing body of mathematical models of DR-mycobacterium is being used to explore intervention impact to support policy as well as theoretical explorations of resistance dynamics. However, the majority lack bacterial heterogeneity, suggesting that important evolutionary effects may be missed.

Nouveau short-course therapy and morphism mapping for clinical pulmonary Mycobacterium kansasii

Standard therapy [isoniazid, rifampin, ethambutol], with or without a macrolide, for pulmonary Mycobacterium kansasii lasts more than a year. Therefore, shorter treatment duration regimens are required. We used data from 32 Taiwanese patients treated with standard therapy who were followed using repetitive sampling-based sputum Mkn time-to-positivity in liquid cultures to calculate kill slopes [γ] based on ordinary differential equations and time-to-extinction of each patient's bacterial burden. The γ was 0.18 [95% Confidence Interval (CI): 0.16-0.20] log10 CFU/mL/day on standard therapy. Next, we identified Mkn time-to-extinction in the hollow fiber system model of pulmonary M. kansasii disease [HFS-Mkn] treated with standard therapy, which was a γ of 0.60 [95% CI: 0.45-0.69) log10 CFU/mL/day. The γs and time-to-extinctions between the two datasets formed structure-preserving maps based on category theory: thus, we could map them from one to the other using morphisms. This mapping identified a multistep non-linear transformation-factor for time-to-extinction from HFS-Mkn to patients. Next, a head-to-head study in the HFS-Mkn identified median time-to-extinction for standard therapy of 38.7 [95% CI: 29.1-53.2) days, isoniazid-rifampin-ethambutol-moxifloxacin of 21.7 [95% CI: 19.1-25) days, isoniazid-rifampin-moxifloxacin of 22 [96% CI: 20.1-24.5) days, and rifampin-moxifloxacin-tedizolid of 20.7 [95% CI:18.5-29) days. Our transformation-factor based translation predicted the proportion of patients of 90.7 [88.74-92.35)% achieving cure with standard therapy at 12 months, and 6-months cure rates of 99.8 [95% CI: 99.27-99.95)% for isoniazid-rifampin-ethambutol-moxifloxacin, 92.2 [90.37-93.71)% for isoniazid-rifampin-moxifloxacin, and 99.9 [99.44-99.99)% for rifampin-moxifloxacin-tedizolid. Thus, rifampin-moxifloxacin-tedizolid and isoniazid-rifampin-ethambutol-moxifloxacin are predicted to be short-course chemotherapy regimens for pulmonary M. kansasii disease.

Determining the Delamanid Pharmacokinetics/Pharmacodynamics Susceptibility Breakpoint Using Monte Carlo Experiments

Antimicrobial susceptibility testing, based on clinical breakpoints that incorporate pharmacokinetics/pharmacodynamics (PK/PD) and clinical outcomes, is becoming a new standard in guiding individual patient therapy as well as for drug resistance surveillance. However, for most antituberculosis drugs, breakpoints are instead defined by the epidemiological cutoff values of the MIC of phenotypically wild-type strains irrespective of PK/PD or dose. In this study, we determined the PK/PD breakpoint for delamanid by estimating the probability of target attainment for the approved dose administered at 100 mg twice daily using Monte Carlo experiments. We used the PK/PD targets (0- to 24-h area under the concentration-time curve to MIC) identified in a murine chronic tuberculosis model, hollow fiber system model of tuberculosis, early bactericidal activity studies of patients with drug-susceptible tuberculosis, and population pharmacokinetics in patients with tuberculosis. At the MIC of 0.016 mg/L, determined using Middlebrook 7H11 agar, the probability of target attainment was 100% in the 10,000 simulated subjects. The probability of target attainment fell to 25%, 40%, and 68% for PK/PD targets derived from the mouse model, the hollow fiber system model of tuberculosis, and patients, respectively, at the MIC of 0.031 mg/L. This indicates that an MIC of 0.016 mg/L is the delamanid PK/PD breakpoint for delamanid at 100 mg twice daily. Our study demonstrated that it is feasible to use PK/PD approaches to define a breakpoint for an antituberculosis drug.

High rifampicin peak plasma concentrations accelerate the slow phase of bacterial decline in tuberculosis patients: Evidence for heteroresistance

BACKGROUND

Antibiotic treatments are often associated with a late slowdown in bacterial killing. This separates the killing of bacteria into at least two distinct phases: a quick phase followed by a slower phase, the latter of which is linked to treatment success. Current mechanistic explanations for the in vitro slowdown are either antibiotic persistence or heteroresistance. Persistence is defined as the switching back and forth between susceptible and non-susceptible states, while heteroresistance is defined as the coexistence of bacteria with heterogeneous susceptibilities. Both are also thought to cause a slowdown in the decline of bacterial populations in patients and therefore complicate and prolong antibiotic treatments. Reduced bacterial death rates over time are also observed within tuberculosis patients, yet the mechanistic reasons for this are unknown and therefore the strategies to mitigate them are also unknown.

METHODS AND FINDINGS

We analyse a dose ranging trial for rifampicin in tuberculosis patients and show that there is a slowdown in the decline of bacteria. We show that the late phase of bacterial killing depends more on the peak drug concentrations than the total drug exposure. We compare these to pharmacokinetic-pharmacodynamic models of rifampicin heteroresistance and persistence. We find that the observation on the slow phase's dependence on pharmacokinetic measures, specifically peak concentrations are only compatible with models of heteroresistance and incompatible with models of persistence. The quantitative agreement between heteroresistance models and observations is very good ([Formula: see text]). To corroborate the importance of the slowdown, we validate our results by estimating the time to sputum culture conversion and compare the results to a different dose ranging trial.

CONCLUSIONS

Our findings indicate that higher doses, specifically higher peak concentrations may be used to optimize rifampicin treatments by accelerating bacterial killing in the slow phase. It adds to the growing body of literature supporting higher rifampicin doses for shortening tuberculosis treatments.

Minocycline intra-bacterial pharmacokinetic hysteresis as a basis for pharmacologic memory and a backbone for once-a-week pan-tuberculosis therapy

Background: There is need for shorter duration regimens for the treatment of tuberculosis, that can treat patients regardless of multidrug resistance status (pan-tuberculosis).

Methods: We combined minocycline with tedizolid, moxifloxacin, and rifampin, in the hollow fiber system model of tuberculosis and mimicked each drugs’ intrapulmonary pharmacokinetics for 28 days. Minocycline-tedizolid was administered either as a once-a-week or a daily regimen. In order to explore a possible explanation for effectiveness of the once-a-week regimen, we measured systemic and intra-bacterial minocycline pharmacokinetics. Standard daily therapy (rifampin, isoniazid, pyrazinamide) was the comparator. We then calculated γ_f or kill slopes for each regimen and ranked the regimens by time-to-extinction predicted in patients.

Results: The steepest γ_f and shortest time-to-extinction of entire bacterial population was with daily minocycline-rifampin combination. There was no difference in γ_f between the minocycline-tedizolid once-a-week versus the daily therapy (p = 0.85). Standard therapy was predicted to cure 88% of patients, while minocycline-rifampin would cure 98% of patients. Minocycline concentrations fell below minimum inhibitory concentration after 2 days of once-weekly dosing schedule. The shape of minocycline intra-bacterial concentration-time curve differed from the extracellular pharmacokinetic system and lagged by several days, consistent with system hysteresis. Hysteresis explained the persistent microbial killing after hollow fiber system model of tuberculosis concentrations dropped below the minimum inhibitory concentration.

Conclusion: Minocycline could form a backbone of a shorter duration once-a-week pan-tuberculosis regimen. We propose a new concept of post-antibiotic microbial killing, distinct from post-antibiotic effect. We propose system hysteresis as the basis for the novel concept of pharmacologic memory, which allows intermittent dosing.

OUP accepted manuscript

Objectives

The standard of care (SOC) for the treatment of pulmonary Mycobacterium avium complex (MAC) disease (clarithromycin, rifabutin, and ethambutol) achieves sustained sputum conversion rates of only 54%. Thus, new treatments should be prioritized.

Methods

We identified the omadacycline MIC against one laboratory MAC strain and calculated drug half life in solution, which we compared with measured MAC doubling times. Next, we performed an omadacycline hollow fibre system model of intracellular MAC (HFS-MAC) exposure–effect study, as well as the three-drug SOC, using pharmacokinetics achieved in patient lung lesions. Data was analysed using bacterial kill slopes (γ-slopes) and inhibitory sigmoid E_max bacterial burden versus exposure analyses. Monte Carlo experiments (MCE) were used to identify the optimal omadacycline clinical dose.

Results

Omadacycline concentration declined in solution with a half-life of 27.7 h versus a MAC doubling time of 16.3 h, leading to artefactually high MICs. Exposures mediating 80% of maximal effect changed up to 8-fold depending on sampling day with bacterial burden versus exposure analyses, while γ-slope-based analyses gave a single robust estimate. The highest omadacycline monotherapy γ-slope was −0.114 (95% CI: −0.141 to −0.087) (r^2 =0.98) versus −0.114 (95% CI: −0.133 to −0.094) (r²= 0.99) with the SOC. MCEs demonstrated that 450 mg of omadacycline given orally on the first 2 days followed by 300 mg daily would achieve the AUC_0-24 target of 39.67 mg·h/L.

Conclusions

Omadacycline may be a potential treatment option for pulmonary MAC, possibly as a back-bone treatment for a new MAC regimen and warrants future study in treatment of this disease.

Duration of pretomanid/moxifloxacin/pyrazinamide therapy compared with standard therapy based on time-to-extinction mathematics

Objectives

Animal models have suggested that the combination of pretomanid with pyrazinamide and moxifloxacin (PaMZ) may shorten TB therapy duration to 3–4 months. Here, we tested that in the hollow-fibre system model of TB (HFS-TB).

Methods

A series of HFS-TB experiments were performed to compare the kill rates of the PaMZ regimen with the standard three-drug combination therapy. HFS-TB experiments were performed with bacilli in log-phase growth treated for 28 days, intracellular bacilli treated daily for 28 days and semi-dormant Mycobacterium tuberculosis treated with daily therapy for 56 days for sterilizing effect. Next, time-to-extinction equations were employed, followed by morphism transformation and Latin hypercube sampling, to determine the proportion of patients who achieved a time to extinction of 3, 4 or 6 months with each regimen.

Results

Using linear regression, the HFS-TB sterilizing effect rates of the PaMZ regimen versus the standard-therapy regimen during the 56 days were 0.18 (95% credible interval=0.13–0.23) versus 0.15 (95% credible interval=0.08–0.21) log₁₀ cfu/mL/day, compared with 0.16 (95% credible interval=0.13–0.18) versus 0.11 (95% credible interval=0.09–0.13) log₁₀ cfu/mL/day in the Phase II clinical trial, respectively. Using time-to-extinction and Latin hypercube sampling modelling, the expected percentages of patients in which the PaMZ regimen would achieve sterilization were 40.37% (95% credible interval=39.1–41.34) and 72.30% (95% credible interval=71.41–73.17) at 3 and 4 months duration of therapy, respectively, versus 93.67% (95% credible interval=93.18–94.13) at 6 months for standard therapy.

Conclusions

The kill rates of the PaMZ regimen were predicted to be insufficient to achieve cure in less than 6 months in most patients.

Bacterial load slopes represent biomarkers of tuberculosis therapy success, failure, and relapse

There is an urgent need to discover biomarkers that are predictive of long-term TB treatment outcomes, since treatment is expense and prolonged to document relapse. We used mathematical modeling and machine learning to characterize a predictive biomarker for TB treatment outcomes. We computed bacterial kill rates, γ_f for fast- and γ_s for slow/non-replicating bacteria, using patient sputum data to determine treatment duration by computing time-to-extinction of all bacterial subpopulations. We then derived a γ_s-slope-based rule using first 8 weeks sputum data, that demonstrated a sensitivity of 92% and a specificity of 89% at predicting relapse-free cure for 2, 3, 4, and 6 months TB regimens. In comparison, current methods (two-month sputum culture conversion and the Extended-EBA) methods performed poorly, with sensitivities less than 34%. These biomarkers will accelerate evaluation of novel TB regimens, aid better clinical trial designs and will allow personalization of therapy duration in routine treatment programs.

Optimizing ethambutol dosing among HIV/tuberculosis co-infected patients: a population pharmacokinetic modelling and simulation study

BACKGROUND

Reduced ethambutol serum concentrations are commonly observed among TB patients co-infected with HIV and may lead to treatment failure.

OBJECTIVES

To perform a population pharmacokinetic study of ethambutol in HIV/TB patients, and to evaluate an intensified ethambutol weight-based dosing strategy to support pharmacokinetic target attainment.

METHODS

We conducted a prospective study of ethambutol pharmacokinetics among HIV/TB patients administered first-line TB treatment in Botswana, with study visits before and after initiation of ART. Clinical and disease status markers, including HIV-associated systemic immune activation and gut dysfunction biomarkers, were evaluated as covariates of ethambutol pharmacokinetic parameters in non-linear mixed effects analysis. Monte Carlo simulations were performed to compare pharmacokinetic target attainment under standard and intensified weight-based ethambutol dosing strategies.

RESULTS

We studied 40 HIV/TB patients prior to initiation of ART, of whom 24 returned for a second visit a median of 33 days following ART initiation. Ethambutol serum concentrations were best explained by a two-compartment model with first-order elimination, with a significant improvement in oral bioavailability following ART initiation. In Monte Carlo simulations, a supplementary ethambutol dose of 400 mg daily led to >2-fold improvements in pharmacokinetic target attainment probabilities in lung tissue, both before and after ART initiation.

CONCLUSIONS

Low serum ethambutol concentrations were commonly observed among HIV/TB patients in Botswana, and the oral bioavailability of ethambutol increased following ART initiation. Supplementary ethambutol dosing among HIV/TB patients may provide a strategy to optimize anti-TB treatment regimens in this high-risk population.

Once-a-week tigecycline for the treatment of drug-resistant TB

BACKGROUND

MDR-TB and XDR-TB have poor outcomes.

OBJECTIVES

To examine the efficacy of tigecycline monotherapy in the hollow fibre system model of TB.

METHODS

We performed pharmacokinetic/pharmacodynamic studies using tigecycline human-like concentration-time profiles in the hollow fibre system model of TB in five separate experiments using Mycobacterium tuberculosis in log-phase growth or as semi-dormant or intracellular bacilli, as monotherapy. We also compared efficacy with the isoniazid/rifampicin/pyrazinamide combination (standard therapy). We then applied extinction mathematics, morphisms and Latin hypercube sampling to identify duration of therapy with tigecycline monotherapy.

RESULTS

The median tigecycline MIC for 30 M. tuberculosis clinical and laboratory isolates (67% MDR/XDR) was 2 mg/L. Tigecycline monotherapy was highly effective in killing M. tuberculosis in log-phase-growth and semi-dormant and intracellular M. tuberculosis. Once-a-week dosing had the same efficacy as daily therapy for the same cumulative dose; thus, tigecycline efficacy was linked to the AUC0-24/MIC ratio. Tigecycline replacement by daily minocycline after 4 weeks of therapy was effective in sterilizing bacilli. The AUC0-24/MIC ratio associated with optimal kill was 42.3. Tigecycline monotherapy had a maximum sterilizing effect (day 0 minus day 28) of 3.06 ± 0.20 log10 cfu/mL (r2 = 0.92) compared with 3.92 ± 0.45 log10 cfu/mL (r2 = 0.80) with optimized standard therapy. In our modelling, at a tigecycline monotherapy duration of 12 months, the proportion of patients with XDR-TB who reached bacterial population extinction was 64.51%.

CONCLUSIONS

Tigecycline could cure patients with XDR-TB or MDR-TB who have failed recommended therapy. Once-a-week tigecycline could also replace second-line injectables in MDR-TB regimens.

Model-Informed Drug Discovery and Development Strategy for the Rapid Development of Anti-Tuberculosis Drug Combinations

The increasing emergence of drug-resistant tuberculosis requires new effective and safe drug regimens. However, drug discovery and development are challenging, lengthy and costly. The framework of model-informed drug discovery and development (MID3) is proposed to be applied throughout the preclinical to clinical phases to provide an informative prediction of drug exposure and efficacy in humans in order to select novel anti-tuberculosis drug combinations. The MID3 includes pharmacokinetic-pharmacodynamic and quantitative systems pharmacology models, machine learning and artificial intelligence, which integrates all the available knowledge related to disease and the compounds. A translational in vitro-in vivo link throughout modeling and simulation is crucial to optimize the selection of regimens with the highest probability of receiving approval from regulatory authorities. In vitro-in vivo correlation (IVIVC) and physiologically-based pharmacokinetic modeling provide powerful tools to predict pharmacokinetic drug-drug interactions based on preclinical information. Mechanistic or semi-mechanistic pharmacokinetic-pharmacodynamic models have been successfully applied to predict the clinical exposure-response profile for anti-tuberculosis drugs using preclinical data. Potential pharmacodynamic drug-drug interactions can be predicted from in vitro data through IVIVC and pharmacokinetic-pharmacodynamic modeling accounting for translational factors. It is essential for academic and industrial drug developers to collaborate across disciplines to realize the huge potential of MID3.

Both Pharmacokinetic Variability and Granuloma Heterogeneity Impact the Ability of the First-Line Antibiotics to Sterilize Tuberculosis Granulomas

Tuberculosis (TB) remains as one of the world's deadliest infectious diseases despite the use of standardized antibiotic therapies. Recommended therapy for drug-susceptible TB is up to 6 months of antibiotics. Factors that contribute to lengthy regimens include antibiotic underexposure in lesions due to poor pharmacokinetics (PK) and complex granuloma compositions, but it is difficult to quantify how individual antibiotics are affected by these factors and to what extent these impact treatments. We use our next-generation multi-scale computational model to simulate granuloma formation and function together with antibiotic pharmacokinetics and pharmacodynamics, allowing us to predict conditions leading to granuloma sterilization. In this work, we focus on how PK variability, determined from human PK data, and granuloma heterogeneity each quantitatively impact granuloma sterilization. We focus on treatment with the standard regimen for TB of four first-line antibiotics: isoniazid, rifampin, ethambutol, and pyrazinamide. We find that low levels of antibiotic concentration due to naturally occurring PK variability and complex granulomas leads to longer granuloma sterilization times. Additionally, the ability of antibiotics to distribute in granulomas and kill different subpopulations of bacteria contributes to their specialization in the more efficacious combination therapy. These results can inform strategies to improve antibiotic therapy for TB.

Dynamic imaging in patients with tuberculosis reveals heterogeneous drug exposures in pulmonary lesions

Tuberculosis (TB) is the leading cause of death from a single infectious agent, requiring at least 6 months of multidrug treatment to achieve cure¹. However, the lack of reliable data on antimicrobial pharmacokinetics (PK) at infection sites hinders efforts to optimize antimicrobial dosing and shorten TB treatments². In this study, we applied a new tool to perform unbiased, noninvasive and multicompartment measurements of antimicrobial concentration-time profiles in humans³. Newly identified patients with rifampin-susceptible pulmonary TB were enrolled in a first-in-human study⁴ using dynamic [¹¹C]rifampin (administered as a microdose) positron emission tomography (PET) and computed tomography (CT). [¹¹C]rifampin PET-CT was safe and demonstrated spatially compartmentalized rifampin exposures in pathologically distinct TB lesions within the same patients, with low cavity wall rifampin exposures. Repeat PET-CT measurements demonstrated independent temporal evolution of rifampin exposure trajectories in different lesions within the same patients. Similar findings were recapitulated by PET-CT in experimentally infected rabbits with cavitary TB and confirmed using postmortem mass spectrometry. Integrated modeling of the PET-captured concentration-time profiles in hollow-fiber bacterial kill curve experiments provided estimates on the rifampin dosing required to achieve cure in 4 months. These data, capturing the spatial and temporal heterogeneity of intralesional drug PK, have major implications for antimicrobial drug development.

Modeling and Simulation of Pretomanid Pharmacodynamics in Pulmonary Tuberculosis Patients

Pretomanid (PA-824) is a nitroimidazole in clinical testing for the treatment of tuberculosis. A population pharmacodynamic model for pretomanid was developed using a Bayesian analysis of efficacy data from two early bactericidal activity (EBA) studies, PA-824-CL-007 and PA-824-CL-010, conducted in Cape Town, South Africa. The two studies included 122 adult male and female participants with newly diagnosed pulmonary tuberculosis who received once daily oral pretomanid doses of either 50, 100, 150, 200, 600, 1,000, or 1,200 mg for 14 days. The structural model described capacity-limited growth and saturable drug-induced bacterial killing with separate rate equations for sputum solid culture colony forming unit (CFU) counts and liquid culture time to positivity (TTP) that were linked through a time constant. The posterior population geometric means and interindividual variability percent coefficients of variation were, respectively; 0.152±0.013 log₁₀ CFU/mL sputum/day and 54%±6% for the maximum kill rate constant, 20.4±1.0 h and 20.8%±0.1% for the time constant of proportionality between the CFU and TTP rate equations, and 770±140 ng/mL and 48%±17% for the pretomanid half-maximum effect plasma concentration. Model simulations showed once daily pretomanid at 100 mg, 200 mg, and 300 mg, attained 58%, 73%, and 80%, respectively, of an expected maximum 14-day EBA of 0.136 log₁₀CFU/mL sputum/day. These results establish a pretomanid exposure-efficacy relationship with dual outcomes for CFU counts and TTP, and with potential applications to dose optimization of pretomanid-containing regimens.

Quantitative assessment of the activity of antituberculosis drugs and regimens

Introduction: Identification of optimal drug doses and drug combinations is crucial for optimized treatment of tuberculosis. Areas covered: An unprecedented level of research activity involving multiple approaches is seeking to improve tuberculosis treatment. This report is a review of the quantitative methods currently used on clinical data sets to identify drug exposure targets and optimal drug combinations for tuberculosis treatment. A high-level summary of the methods, including the strengths and weaknesses of each method and potential methodological improvements is presented. Methods incorporating data generated from multiple sources such as in vitro and clinical studies, and their potential to provide better estimates of pharmacokinetic/pharmacodynamic (PK/PD) targets, are discussed. PK/PD relationships identified are compared between different studies and data analysis methods. Expert opinion: The relationships between drug exposures and tuberculosis treatment outcomes are complex and require analytical methods capable of handling the multidimensional nature of the relationships. The choice of a method is guided by its complexity, interpretability of results, and type of data available.

Pharmacokinetic/Pharmacodynamic Background and Methods and Scientific Evidence Base for Dosing of Second-line Tuberculosis Drugs

A World Health Organization workshop systematically examined the evidence base for dosing second-line tuberculosis drugs, identifying knowledge gaps. To fill these in, pharmacokinetics/pharmacodynamics, Monte Carlo experiments, and artificial intelligence algorithms were used in hollow-fiber model studies and clinical data analyses.

Clofazimine for the Treatment of Mycobacterium kansasii

Mycobacterium kansasii pulmonary infection is a global problem. Standard combination therapy consists of isoniazid at 300 mg/day, rifampin at 600 mg/day, and ethambutol at 15 mg/kg of body weight/day for 18 months. Coincubation of M. kansasii with different clofazimine concentrations over 7 days in test tubes resulted in a maximal kill (maximum effect [E_max]) of 2.03 log₁₀ CFU/ml below the day 0 bacterial burden. The concentration associated with E_max was 110 times the MIC. Next, the effects of human-like concentration-time profiles of clofazimine human-equivalent doses ranging from 0 to 200 mg daily for 21 days were examined in the hollow-fiber model of intracellular M. kansasii (HFS-Mkn). On day 14, when the clofazimine microbial effect was maximal, the E_max was 2.57 log₁₀ CFU/ml, while the dose associated with E_max was 100 mg/day. However, no dose killed M. kansasii to levels below the day 0 bacterial burden. Thus, the antimicrobial effect of clofazimine monotherapy in the HFS-Mkn was modest. Human-equivalent concentration-time profiles of standard combination therapy and doses were used as comparators in the HFS-Mkn On day 14, standard therapy killed to a level 2.32 log₁₀ CFU/ml below the day 0 bacterial burden. The effect of standard therapy was consistent with a biexponential decline, with kill rate constants of 1.85 per day (half-life = 0.37 days) and 0.06 per day (half-life = 12.76 days) (r² > 0.99). This means that standard therapy would take 9.3 to 12 months to completely eliminate M. kansasii in the model, which is consistent with clinical observations. This observation for standard therapy means that the modest to poor effect of clofazimine on M. kansasii identified here is likely to be the same in the clinic.