Drug Effect of Clofazimine on Persisters Explains an Unexpected Increase in Bacterial Load in Patients

Clofazimine pharmacokinetics in HIV-infected adults with diarrhea: Implications of diarrheal disease on absorption of orally administered therapeutics

Oral drug absorption kinetics are usually established in populations with a properly functioning gastrointestinal tract. However, many diseases and therapeutics can alter gastrointestinal physiology and cause diarrhea. The extent of diarrhea-associated impact on drug pharmacokinetics has not been quantitatively described. To address this knowledge gap, we used a population pharmacokinetic modeling approach with data collected in a phase IIa study of matched human immunodeficiency virus (HIV)-infected adults with/without cryptosporidiosis and diarrhea to examine diarrhea-associated impact on oral clofazimine pharmacokinetics. A population pharmacokinetic model was developed with 428 plasma samples from 23 HIV-infected adults with/without Cryptosporidium infection using nonlinear mixed-effects modeling. Covariates describing cryptosporidiosis-associated diarrhea severity (e.g., number of diarrhea episodes, diarrhea grade) or HIV infection (e.g., viral load, CD4+ T cell count) were evaluated. A two-compartment model with lag time and first-order absorption and elimination best fit the data. Maximum diarrhea grade over the study duration was found to be associated with a more than sixfold reduction in clofazimine bioavailability. Apparent clofazimine clearance, intercompartmental clearance, central volume of distribution, and peripheral volume of distribution were 3.71 L/h, 18.2 L/h (interindividual variability [IIV] 45.0%), 473 L (IIV 3.46%), and 3434 L, respectively. The absorption rate constant was 0.625 h-1 (IIV 149%) and absorption lag time was 1.83 h. In conclusion, the maximum diarrhea grade observed for the duration of oral clofazimine administration was associated with a significant reduction in clofazimine bioavailability. Our results highlight the importance of studying disease impacts on oral therapeutic pharmacokinetics to inform dose optimization and maximize the chance of treatment success.

Solans B, Hesseling AC, Winckler J, Schaaf HS, Draper HR, van der Laan L, Hughes J, Fourie B, Nielsen J, Wiesner L, Garcia-Prats AJ, Savic RM. Pharmacokinetics and cardiac safety of clofazimine in children with rifampicin-resistant tuberculosis

Clofazimine is recommended for the treatment of rifampicin-resistant tuberculosis (RR-TB), but there is currently no verified dosing guideline for its use in children. There is only limited safety and no pharmacokinetic (PK) data available for children. We aimed to characterize clofazimine PK and its relationship with QT-interval prolongation in children. An observational cohort study of South African children <18 years old routinely treated for RR-TB with a clofazimine-containing regimen was analyzed. Clofazimine 100 mg gelatin capsules were given orally once daily (≥20 kg body weight), every second day (10 to <20 kg), or thrice weekly (<10 kg). PK sampling and electrocardiograms were completed pre-dose and at 1, 4, and 10 hours post-dose, and the population PK and Fridericia-corrected QT (QTcF) interval prolongation were characterized. Fifty-four children contributed both PK and QTcF data, with a median age (2.5th-97.5th centiles) of 3.3 (0.5-15.6) years; five children were living with HIV. Weekly area under the time-concentration curve at steady state was 79.1 (15.0-271) mg.h/L compared to an adult target of 60.9 (56.0-66.6) mg.h/L. Children living with HIV had four times higher clearance compared to those without. No child had a QTcF ≥500 ms. A linear concentration-QTcF relationship was found, with a drug effect of 0.05 (0.027, 0.075) ms/µg/L. In some of the first PK data in children, we found clofazimine exposure using an off-label dosing strategy was higher in children versus adults. Clofazimine concentrations were associated with an increase in QTcF, but severe prolongation was not observed. More data are required to inform dosing strategies in children.

Combined quantitative tuberculosis biomarker model for time-to-positivity and colony forming unit to support tuberculosis drug development

Biomarkers are quantifiable characteristics of biological processes. In Mycobacterium tuberculosis, common biomarkers used in clinical drug development are colony forming unit (CFU) and time-to-positivity (TTP) from sputum samples. This analysis aimed to develop a combined quantitative tuberculosis biomarker model for CFU and TTP biomarkers for assessing drug efficacy in early bactericidal activity studies. Daily CFU and TTP observations in 83 previously patients with uncomplicated pulmonary tuberculosis after 7 days of different rifampicin monotherapy treatments (10–40 mg/kg) from the HIGHRIF1 study were included in this analysis. The combined quantitative tuberculosis biomarker model employed the Multistate Tuberculosis Pharmacometric model linked to a rifampicin pharmacokinetic model in order to determine drug exposure-response relationships on three bacterial sub-states using both the CFU and TTP data simultaneously. CFU was predicted from the MTP model and TTP was predicted through a time-to-event approach from the TTP model, which was linked to the MTP model through the transfer of all bacterial sub-states in the MTP model to a one bacterial TTP model. The non-linear CFU-TTP relationship over time was well predicted by the final model. The combined quantitative tuberculosis biomarker model provides an efficient approach for assessing drug efficacy informed by both CFU and TTP data in early bactericidal activity studies and to describe the relationship between CFU and TTP over time.

New and Repurposed Drugs for the Treatment of Active Tuberculosis: An Update for Clinicians

Although tuberculosis (TB) is preventable and curable, the lengthy treatment (generally 6 months), poor patient adherence, high inter-individual variability in pharmacokinetics (PK), emergence of drug resistance, presence of comorbidities, and adverse drug reactions complicate TB therapy and drive the need for new drugs and/or regimens. Hence, new compounds are being developed, available drugs are repurposed, and the dosing of existing drugs is optimized, resulting in the largest drug development portfolio in TB history. This review highlights a selection of clinically available drug candidates that could be part of future TB regimens, including bedaquiline, delamanid, pretomanid, linezolid, clofazimine, optimized (high dose) rifampicin, rifapentine, and para-aminosalicylic acid. The review covers drug development history, preclinical data, PK, and current clinical development.

Standards for model-based early bactericidal activity analysis and sample size determination in tuberculosis drug development

Background: A critical step in tuberculosis (TB) drug development is the Phase 2a early bactericidal activity (EBA) study which informs if a new drug or treatment has short-term activity in humans. The aim of this work was to present a standardized pharmacometric model-based early bactericidal activity analysis workflow and determine sample sizes needed to detect early bactericidal activity or a difference between treatment arms. Methods: Seven different steps were identified and developed for a standardized pharmacometric model-based early bactericidal activity analysis approach. Non-linear mixed effects modeling was applied and different scenarios were explored for the sample size calculations. The sample sizes needed to detect early bactericidal activity given different TTP slopes and associated variability was assessed. In addition, the sample sizes needed to detect effect differences between two treatments given the impact of different TTP slopes, variability in TTP slope and effect differences were evaluated. Results: The presented early bactericidal activity analysis approach incorporates estimate of early bactericidal activity with uncertainty through the model-based estimate of TTP slope, variability in TTP slope, impact of covariates and pharmacokinetics on drug efficacy. Further it allows for treatment comparison or dose optimization in Phase 2a. To detect early bactericidal activity with 80% power and at a 5% significance level, 13 and 8 participants/arm were required for a treatment with a TTP-EBA_0-14 as low as 11 h when accounting for variability in pharmacokinetics and when variability in TTP slope was 104% [coefficient of variation (CV)] and 22%, respectively. Higher sample sizes are required for smaller early bactericidal activity and when pharmacokinetics is not accounted for. Based on sample size determinations to detect a difference between two groups, TTP slope, variability in TTP slope and effect difference between two treatment arms needs to be considered. Conclusion: In conclusion, a robust standardized pharmacometric model-based EBA analysis approach was established in close collaboration between microbiologists, clinicians and pharmacometricians. The work illustrates the importance of accounting for covariates and drug exposure in EBA analysis in order to increase the power of detecting early bactericidal activity for a single treatment arm as well as differences in EBA between treatments arms in Phase 2a trials of TB drug development.

Pharmacokinetics and pharmacodynamics of anti-tuberculosis drugs: An evaluation of in vitro, in vivo methodologies and human studies

There has been an increased interest in pharmacokinetics and pharmacodynamics (PKPD) of anti-tuberculosis drugs. A better understanding of the relationship between drug exposure, antimicrobial kill and acquired drug resistance is essential not only to optimize current treatment regimens but also to design appropriately dosed regimens with new anti-tuberculosis drugs. Although the interest in PKPD has resulted in an increased number of studies, the actual bench-to-bedside translation is somewhat limited. One of the reasons could be differences in methodologies and outcome assessments that makes it difficult to compare the studies. In this paper we summarize most relevant in vitro, in vivo, in silico and human PKPD studies performed to optimize the drug dose and regimens for treatment of tuberculosis. The in vitro assessment focuses on MIC determination, static time-kill kinetics, and dynamic hollow fibre infection models to investigate acquisition of resistance and killing of Mycobacterium tuberculosis populations in various metabolic states. The in vivo assessment focuses on the various animal models, routes of infection, PK at the site of infection, PD read-outs, biomarkers and differences in treatment outcome evaluation (relapse and death). For human PKPD we focus on early bactericidal activity studies and inclusion of PK and therapeutic drug monitoring in clinical trials. Modelling and simulation approaches that are used to evaluate and link the different data types will be discussed. We also describe the concept of different studies, study design, importance of uniform reporting including microbiological and clinical outcome assessments, and modelling approaches. We aim to encourage researchers to consider methods of assessing and reporting PKPD of anti-tuberculosis drugs when designing studies. This will improve appropriate comparison between studies and accelerate the progress in the field.

Need for a Standardized Translational Drug Development Platform: Lessons Learned from the Repurposing of Drugs for COVID-19

In the absence of drugs to treat or prevent COVID-19, drug repurposing can be a valuable strategy. Despite a substantial number of clinical trials, drug repurposing did not deliver on its promise. While success was observed with some repurposed drugs (e.g., remdesivir, dexamethasone, tocilizumab, baricitinib), others failed to show clinical efficacy. One reason is the lack of clear translational processes based on adequate preclinical profiling before clinical evaluation. Combined with limitations of existing in vitro and in vivo models, there is a need for a systematic approach to urgent antiviral drug development in the context of a global pandemic. We implemented a methodology to test repurposed and experimental drugs to generate robust preclinical evidence for further clinical development. This translational drug development platform comprises in vitro, ex vivo, and in vivo models of SARS-CoV-2, along with pharmacokinetic modeling and simulation approaches to evaluate exposure levels in plasma and target organs. Here, we provide examples of identified repurposed antiviral drugs tested within our multidisciplinary collaboration to highlight lessons learned in urgent antiviral drug development during the COVID-19 pandemic. Our data confirm the importance of assessing in vitro and in vivo potency in multiple assays to boost the translatability of pre-clinical data. The value of pharmacokinetic modeling and simulations for compound prioritization is also discussed. We advocate the need for a standardized translational drug development platform for mild-to-moderate COVID-19 to generate preclinical evidence in support of clinical trials. We propose clear prerequisites for progression of drug candidates for repurposing into clinical trials. Further research is needed to gain a deeper understanding of the scope and limitations of the presented translational drug development platform.

Assessment of the efficacy of clofazimine alone and in combination with primary agents against Mycobacterium tuberculosis in vitro

OBJECTIVES

The chemotherapeutic regimens of drug-susceptible (DS)-tuberculosis (TB) patients comprise four primary anti-TB drugs; rifampicin (RMP), isoniazid (INH), ethambutol (EMB) and pyrazinamide (PZA), administered for six-to-nine months. These drug regimens target the various microbial populations that include actively-replicating (AR), slow-replicating (SR) and non-replicating (NR) organisms. Clofazimine (CFZ) has showed benefit in shortening DS-TB treatment in vivo from six to four months when used in combination with this regimen in murine models of experimental infection. However, its antimicrobial efficacy when used in combination with the primary drugs against the various microbial populations of Mycobacterium tuberculosis has not been demonstrated.

METHODS

In the current in vitro study, the inhibitory and bactericidal activities of CFZ in combination with the primary anti-TB drugs, RMP, INH and EMB against the AR and SR organisms in planktonic and biofilm-forming cultures, respectively, were evaluated by fractional inhibitory concentration index (FICI) and fractional bactericidal concentration index (FBCI) determinations, using the Loewe Additivity Model.

RESULTS

In planktonic cultures, CFZ demonstrated synergistic growth inhibitory activity in combination with RMP and INH individually and collectively. With respect to bactericidal activity, CFZ exhibited synergistic activity only in a two-drug combination with RMP. However, in biofilm-forming cultures, all CFZ-containing anti-TB drug combinations exhibited synergistic inhibitory and bactericidal effects, particularly in combination with RIF and INH.

CONCLUSION

Clofazimine exhibited synergistic effects in combination with primary anti-TB drugs against both planktonic and biofilm-forming cultures, showing potential benefit in augmenting treatment outcome when used during standard TB chemotherapy.

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.

An optimized method for the detection and spatial distribution of aminoglycoside and vancomycin antibiotics in tissue sections by mass spectrometry imaging

Suboptimal antibiotic dosing has been identified as one of the key drivers in the development of multidrug-resistant (MDR) bacteria that have become a global health concern. Aminoglycosides and vancomycin are broad-spectrum antibiotics used to treat critically ill patients infected by a variety of MDR bacterial species. Resistance to these antibiotics is becoming more prevalent. In order to design proper antibiotic regimens that maximize efficacy and minimize the development of resistance, it is pivotal to obtain the in situ pharmacokinetic-pharmacodynamic profiles at the sites of infection. Mass spectrometry imaging (MSI) is the ideal technique to achieve this. Aminoglycosides, due to their structure, suffer from poor ionization efficiency. Additionally, ion suppression effects by endogenous molecules greatly inhibit the detection of aminoglycosides and vancomycin at therapeutic levels. In the current study, an optimized method was developed that enabled the detection of these antibiotics by MSI. Tissue spotting experiments demonstrated a 5-, 15-, 35-, and 54-fold increase in detection sensitivity in the washed samples for kanamycin, amikacin, streptomycin, and vancomycin, respectively. Tissue mimetic models were utilized to optimize the washing time and matrix additive concentration. These studies determined the improved limit of detection was 40 to 5 μg/g of tissue for vancomycin and streptomycin, and 40 to 10 μg/g of tissue for kanamycin and amikacin. The optimized protocol was applied to lung sections from mice dosed with therapeutic levels of kanamycin and vancomycin. The washing protocol enabled the first drug distribution investigations of aminoglycosides and vancomycin by MSI, paving the way for site-of-disease antibiotic penetration studies.

Difference in persistent tuberculosis bacteria between in vitro and sputum from patients: implications for translational predictions

This study aimed to investigate the number of persistent bacteria in sputum from tuberculosis patients compared to in vitro and to suggest a model-based approach for accounting for the potential difference. Sputum smear positive patients (n = 25) provided sputum samples prior to onset of chemotherapy. The number of cells detected by conventional agar colony forming unit (CFU) and most probable number (MPN) with Rpf supplementation were quantified. Persistent bacteria was assumed to be the difference between MPN_rpf and CFU. The difference in persistent bacteria between in vitro and human sputum prior to chemotherapy was quantified using different model-based approaches. The persistent bacteria in sputum was 17% of the in vitro levels, suggesting a difference in phenotypic resistance, whereas no difference was found for multiplying bacterial subpopulations. Clinical trial simulations showed that the predicted time to 2 log fall in MPN_rpf in a Phase 2a setting using in vitro pre-clinical efficacy information, would be almost 3 days longer if drug response was predicted ignoring the difference in phenotypic resistance. The discovered phenotypic differences between in vitro and humans prior to chemotherapy could have implications on translational efforts but can be accounted for using a model-based approach for translating in vitro to human drug response.

A model-based analysis identifies differences in phenotypic resistance between in vitro and in vivo: implications for translational medicine within tuberculosis

Proper characterization of drug effects on Mycobacterium tuberculosis relies on the characterization of phenotypically resistant bacteria to correctly establish exposure–response relationships. The aim of this work was to evaluate the potential difference in phenotypic resistance in in vitro compared to murine in vivo models using CFU data alone or CFU together with most probable number (MPN) data following resuscitation with culture supernatant. Predictions of in vitro and in vivo phenotypic resistance i.e. persisters, using the Multistate Tuberculosis Pharmacometric (MTP) model framework was evaluated based on bacterial cultures grown with and without drug exposure using CFU alone or CFU plus MPN data. Phenotypic resistance and total bacterial number in in vitro natural growth observations, i.e. without drug, was well predicted by the MTP model using only CFU data. Capturing the murine in vivo total bacterial number and persisters during natural growth did however require re-estimation of model parameter using both the CFU and MPN observations implying that the ratio of persisters to total bacterial burden is different in vitro compared to murine in vivo. The evaluation of the in vitro rifampicin drug effect revealed that higher resolution in the persister drug effect was seen using CFU and MPN compared to CFU alone although drug effects on the other bacterial populations were well predicted using only CFU data. The ratio of persistent bacteria to total bacteria was predicted to be different between in vitro and murine in vivo. This difference could have implications for subsequent translational efforts in tuberculosis drug development.

Quantification of Natural Growth of Two Strains of Mycobacterium Marinum for Translational Antituberculosis Drug Development

The zebrafish infected with Mycobacterium marinum (M. marinum) is an attractive tuberculosis disease model, showing similar pathogenesis to Mycobacterium tuberculosis (M. tuberculosis) infections in humans. To translate pharmacological findings from this disease model to higher vertebrates, a quantitative understanding of the natural growth of M. marinum in comparison to the natural growth of M. tuberculosis is essential. Here, the natural growth of two strains of M. marinum, E11 and M^USA, is studied over an extended period using an established model‐based approach, the multistate tuberculosis pharmacometric (MTP) model, for comparison to that of M. tuberculosis. Poikilotherm‐derived strain E11 and human‐derived strain M^USA were grown undisturbed up to 221 days and viability of cultures (colony forming unit (CFU)/mL) was determined by plating at different time points. Nonlinear mixed effects modeling using the MTP model quantified the bacterial growth, the transfer among fast, slow, and non‐multiplying states, and the inoculi. Both strains showed initial logistic growth, reaching a maximum after 20–25 days for E11 and M^USA, respectively, followed by a decrease to a new plateau. Natural growth of both E11 and M^USA was best described with Gompertz growth functions. For E11, the inoculum was best described in the slow‐multiplying state, for M^USA in the fast‐multiplying state. Natural growth of E11 was most similar to that of M. tuberculosis, whereas M^USA showed more aggressive growth behavior. Characterization of natural growth of M. marinum and quantitative comparison with M. tuberculosis brings the zebrafish tuberculosis disease model closer to the quantitative translational pipeline of antituberculosis drug development.