Development of New Tuberculosis Drugs: Translation to Regimen Composition for Drug-Sensitive and Multidrug-Resistant Tuberculosis

Dynamic microfluidic single-cell screening identifies pheno-tuning compounds to potentiate tuberculosis therapy

Drug-recalcitrant infections are a leading global-health concern. Bacterial cells benefit from phenotypic variation, which can suggest effective antimicrobial strategies. However, probing phenotypic variation entails spatiotemporal analysis of individual cells that is technically challenging, and hard to integrate into drug discovery. In this work, we develop a multi-condition microfluidic platform suitable for imaging two-dimensional growth of bacterial cells during transitions between separate environmental conditions. With this platform, we implement a dynamic single-cell screening for pheno-tuning compounds, which induce a phenotypic change and decrease cell-to-cell variation, aiming to undermine the entire bacterial population and make it more vulnerable to other drugs. We apply this strategy to mycobacteria, as tuberculosis poses a major public-health threat. Our lead compound impairs Mycobacterium tuberculosis via a peculiar mode of action and enhances other anti-tubercular drugs. This work proves that harnessing phenotypic variation represents a successful approach to tackle pathogens that are increasingly difficult to treat.

Use of multiple pharmacodynamic measures to deconstruct the Nix-TB regimen in a short-course murine model of tuberculosis

A major challenge for tuberculosis (TB) drug development is to prioritize promising combination regimens from a large and growing number of possibilities. This includes demonstrating individual drug contributions to the activity of higher-order combinations. A BALB/c mouse TB infection model was used to evaluate the contributions of each drug and pairwise combination in the clinically relevant Nix-TB regimen [bedaquiline-pretomanid-linezolid (BPaL)] during the first 3 weeks of treatment at human equivalent doses. The rRNA synthesis (RS) ratio, an exploratory pharmacodynamic (PD) marker of ongoing Mycobacterium tuberculosis rRNA synthesis, together with solid culture CFU counts and liquid culture time to positivity (TTP) were used as PD markers of treatment response in lung tissue; and their time-course profiles were mathematically modeled using rate equations with pharmacologically interpretable parameters. Antimicrobial interactions were quantified using Bliss independence and Isserlis formulas. Subadditive (or antagonistic) and additive effects on bacillary load, assessed by CFU and TTP, were found for bedaquiline-pretomanid and linezolid-containing pairs, respectively. In contrast, subadditive and additive effects on rRNA synthesis were found for pretomanid-linezolid and bedaquiline-containing pairs, respectively. Additionally, accurate predictions of the response to BPaL for all three PD markers were made using only the single-drug and pairwise effects together with an assumption of negligible three-way drug interactions. The results represent an experimental and PD modeling approach aimed at reducing combinatorial complexity and improving the cost-effectiveness of in vivo systems for preclinical TB regimen development.

Therapeutic developments for tuberculosis and nontuberculous mycobacterial lung disease

Tuberculosis (TB) drug discovery and development has undergone nothing short of a revolution over the past 20 years. Successful public-private partnerships and sustained funding have delivered a much-improved understanding of mycobacterial disease biology and pharmacology and a healthy pipeline that can tolerate inevitable attrition. Preclinical and clinical development has evolved from decade-old concepts to adaptive designs that permit rapid evaluation of regimens that might greatly shorten treatment duration over the next decade. But the past 20 years also saw the rise of a fatal and difficult-to-cure lung disease caused by nontuberculous mycobacteria (NTM), for which the drug development pipeline is nearly empty. Here, we discuss the similarities and differences between TB and NTM lung diseases, compare the preclinical and clinical advances, and identify major knowledge gaps and areas of cross-fertilization. We argue that applying paradigms and networks that have proved successful for TB, from basic research to clinical trials, will help to populate the pipeline and accelerate curative regimen development for NTM disease.

Use of Multiple Pharmacodynamic Measures to Deconstruct the Nix-TB Regimen in a Short-Course Murine Model of Tuberculosis

A major challenge for tuberculosis (TB) drug development is to prioritize promising combination regimens from a large and growing number of possibilities. This includes demonstrating individual drug contributions to the activity of higher-order combinations. A BALB/c mouse TB infection model was used to evaluate the contributions of each drug and pairwise combination in the clinically relevant Nix-TB regimen (bedaquiline-pretomanid-linezolid [BPaL]) during the first three weeks of treatment at human equivalent doses. RS ratio, an exploratory pharmacodynamic (PD) marker of ongoing Mycobacterium tuberculosis rRNA synthesis, to-gether with solid culture CFU and liquid culture time to positivity (TTP) were used as PD markers of treatment response in lung tissue; and their time course profiles were mathematically modeled using rate equations with pharmacologically interpretable parameters. Antimicrobial interactions were quantified using Bliss independence and Isserlis formulas. Subadditive (or antagonistic) and additive effects on bacillary load, assessed by CFU and TTP, were found for bedaquiline-pretomanid and linezolid-containing pairs, respectively. In contrast, subadditive and additive effects on rRNA synthesis were found for pretomanid-linezolid and bedaquiline-containing pairs, respectively. Additionally, accurate predictions of the response to BPaL for all three PD markers were made using only the single-drug and pairwise effects together with an assumption of negligible three-way drug interactions. The results represent an experimental and PD modeling approach aimed at reducing combinatorial complexity and improving the cost-effectiveness of in vivo systems for preclinical TB regimen development.

Translational predictions of phase 2a first-in-patient efficacy studies for antituberculosis drugs

BACKGROUND

Phase 2a trials in tuberculosis typically use early bactericidal activity (EBA), the decline in sputum CFU over 14 days, as the primary end-point for testing the efficacy of drugs as monotherapy. However, the cost of phase 2a trials can range from USD 7 million to USD 19.6 million on average, while >30% of drugs fail to progress to phase 3. Better utilising pre-clinical data to predict and prioritise the most likely drugs to succeed will thus help to accelerate drug development and reduce costs. We aim to predict clinical EBA using pre-clinical in vivo pharmacokinetic (PK)-pharmacodynamic (PD) data and a model-based translational pharmacology approach.

METHODS AND FINDINGS

First, mouse PK, PD and clinical PK models were compiled. Second, mouse PK-PD models were built to derive an exposure-response relationship. Third, translational prediction of clinical EBA studies was performed using mouse PK-PD relationships and informed by clinical PK models and species-specific protein binding. Presence or absence of clinical efficacy was accurately predicted from the mouse model. Predicted daily decreases of CFU in the first 2 days of treatment and between day 2 and day 14 were consistent with clinical observations.

CONCLUSION

This platform provides an innovative solution to inform or even replace phase 2a EBA trials, to bridge the gap between mouse efficacy studies and phase 2b and phase 3 trials, and to substantially accelerate drug development.

Predictions of Bedaquiline and Pretomanid Target Attainment in Lung Lesions of Tuberculosis Patients using Translational Minimal Physiologically Based Pharmacokinetic Modeling

BACKGROUND

Site-of-action concentrations for bedaquiline and pretomanid from tuberculosis patients are unavailable. The objective of this work was to predict bedaquiline and pretomanid site-of-action exposures using a translational minimal physiologically based pharmacokinetic (mPBPK) approach to understand the probability of target attainment (PTA).

METHODS

A general translational mPBPK framework for the prediction of lung and lung lesion exposure was developed and validated using pyrazinamide site-of-action data from mice and humans. We then implemented the framework for bedaquiline and pretomanid. Simulations were conducted to predict site-of-action exposures following standard bedaquiline and pretomanid, and bedaquiline once-daily dosing. Probabilities of average concentrations within lesions and lungs greater than the minimum bactericidal concentration for non-replicating (MBCNR) and replicating (MBCR) bacteria were calculated. Effects of patient-specific differences on target attainment were evaluated.

RESULTS

The translational modeling approach was successful in predicting pyrazinamide lung concentrations from mice to patients. We predicted that 94% and 53% of patients would attain bedaquiline average daily PK exposure within lesions (Cavg-lesion) > MBCNR during the extensive phase of bedaquiline standard (2 weeks) and once-daily (8 weeks) dosing, respectively. Less than 5% of patients were predicted to achieve Cavg-lesion > MBCNR during the continuation phase of bedaquiline or pretomanid treatment, and more than 80% of patients were predicted to achieve Cavg-lung >MBCR for all simulated dosing regimens of bedaquiline and pretomanid.

CONCLUSIONS

The translational mPBPK model predicted that the standard bedaquiline continuation phase and standard pretomanid dosing may not achieve optimal exposures to eradicate non-replicating bacteria in most patients.

Translational predictions of phase 2a first-in-patient efficacy studies for antituberculosis drugs

Background

Phase 2a trials in tuberculosis typically use early bactericidal activity (EBA), the decline in sputum colony forming units (CFU) over 14 days, as the primary outcome for testing the efficacy of drugs as monotherapy. However, the cost of phase 2a trials can range from 7 to 19.6 million dollars on average, while more than 30% of drugs fail to progress to phase 3. Better utilizing preclinical data to predict and prioritize the most likely drugs to succeed will thus help accelerate drug development and reduce costs. We aim to predict clinical EBA using preclinical in vivo pharmacokinetic-pharmacodynamic (PKPD) data and a model-based translational pharmacology approach.

Methods and Findings

First, mouse PK, PD and clinical PK models were compiled. Second, mouse PKPD models were built to derive an exposure response relationship. Third, translational prediction of clinical EBA studies was performed using mouse PKPD relationships and informed by clinical PK models and species-specific protein binding. Presence or absence of clinical efficacy was accurately predicted from the mouse model. Predicted daily decreases of CFU in the first 2 days of treatment and between day 2 and day 14 were consistent with clinical observations.

Conclusion

This platform provides an innovative solution to inform or even replace phase 2a EBA trials, to bridge the gap between mouse efficacy studies and phase 2b and phase 3 trials, and to substantially accelerate drug development.

Tools to develop antibiotic combinations that target drug tolerance in Mycobacterium tuberculosis

Combination therapy is necessary to treat tuberculosis to decrease the rate of disease relapse and prevent the acquisition of drug resistance, and shorter regimens are urgently needed. The adaptation of Mycobacterium tuberculosis to various lesion microenvironments in infection induces various states of slow replication and non-replication and subsequent antibiotic tolerance. This non-heritable tolerance to treatment necessitates lengthy combination therapy. Therefore, it is critical to develop combination therapies that specifically target the different types of drug-tolerant cells in infection. As new tools to study drug combinations earlier in the drug development pipeline are being actively developed, we must consider how to best model the drug-tolerant cells to use these tools to design the best antibiotic combinations that target those cells and shorten tuberculosis therapy. In this review, we discuss the factors underlying types of drug tolerance, how combination therapy targets these populations of bacteria, and how drug tolerance is currently modeled for the development of tuberculosis multidrug therapy. We highlight areas for future studies to develop new tools that better model drug tolerance in tuberculosis infection specifically for combination therapy testing to bring the best drug regimens forward to the clinic.

A Credibility Assessment Plan for an In Silico Model that Predicts the Dose-Response Relationship of New Tuberculosis Treatments

Tuberculosis is one of the leading causes of death in several developing countries and a public health emergency of international concern. In Silico Trials can be used to support innovation in the context of drug development reducing the duration and the cost of the clinical experimentations, a particularly desirable goal for diseases such as tuberculosis. The agent-based Universal Immune System Simulator was used to develop an In Silico Trials environment that can predict the dose-response of new therapeutic vaccines against pulmonary tuberculosis, supporting the optimal design of clinical trials. But before such in silico methodology can be used in the evaluation of new treatments, it is mandatory to assess the credibility of this predictive model. This study presents a risk-informed credibility assessment plan inspired by the ASME V&V 40-2018 technical standard. Based on the selected context of use and regulatory impact of the technology, a detailed risk analysis is described together with the definition of all the verification and validation activities and related acceptability criteria. The work provides an example of the first steps required for the regulatory evaluation of an agent-based model used in the context of drug development.

Potential Impact of Long-Acting Products on the Control of Tuberculosis: Preclinical Advancements and Translational Tools in Preventive Treatment

A key component of global tuberculosis (TB) control is the treatment of latent TB infection. The use of long-acting technologies to administer TB preventive treatment has the potential to significantly improve the delivery and impact of this important public health intervention. For example, an ideal long-acting treatment could consist of a single dose that could be administered in the clinic (ie, a "1-shot cure" for latent TB). Interest in long-acting formulations for TB preventive therapy has gained considerable traction in recent years. This article presents an overview of the specific considerations and current preclinical advancements relevant for the development of long-acting technologies of TB drugs for treatment of latent infection, including attributes of target product profiles, suitability of drugs for long-acting formulations, ongoing research efforts, and translation to clinical studies.

Microfluidic dose-response platform to track the dynamics of drug response in single mycobacterial cells

Preclinical analysis of drug efficacy is critical for drug development. However, conventional bulk-cell assays statically assess the mean population behavior, lacking resolution on drug-escaping cells. Inaccurate estimation of efficacy can lead to overestimation of compounds, whose efficacy will not be confirmed in the clinic, or lead to rejection of valuable candidates. Time-lapse microfluidic microscopy is a powerful approach to characterize drugs at high spatiotemporal resolution, but hard to apply on a large scale. Here we report the development of a microfluidic platform based on a pneumatic operating principle, which is scalable and compatible with long-term live-cell imaging and with simultaneous analysis of different drug concentrations. We tested the platform with mycobacterial cells, including the tubercular pathogen, providing the first proof of concept of a single-cell dose-response assay. This dynamic in-vitro model will prove useful to probe the fate of drug-stressed cells, providing improved predictions of drug efficacy in the clinic.

Anti-tuberculosis treatment strategies and drug development: challenges and priorities

Despite two decades of intensified research to understand and cure tuberculosis disease, biological uncertainties remain and hamper progress. However, owing to collaborative initiatives including academia, the pharmaceutical industry and non-for-profit organizations, the drug candidate pipeline is promising. This exceptional success comes with the inherent challenge of prioritizing multidrug regimens for clinical trials and revamping trial designs to accelerate regimen development and capitalize on drug discovery breakthroughs. Most wanted are markers of progression from latent infection to active pulmonary disease, markers of drug response and predictors of relapse, in vitro tools to uncover synergies that translate clinically and animal models to reliably assess the treatment shortening potential of new regimens. In this Review, we highlight the benefits and challenges of 'one-size-fits-all' regimens and treatment duration versus individualized therapy based on disease severity and host and pathogen characteristics, considering scientific and operational perspectives.

A bacterial phospholipid phosphatase inhibits host pyroptosis by hijacking ubiquitin

The inflammasome-mediated cleavage of gasdermin D (GSDMD) causes pyroptosis and inflammatory cytokine release to control pathogen infection, but how pathogens evade this immune response remains largely unexplored. Here we identify the known protein phosphatase PtpB from Mycobacterium tuberculosis as a phospholipid phosphatase inhibiting the host inflammasome-pyroptosis pathway. Mechanistically, PtpB dephosphorylated phosphatidylinositol-4-monophosphate and phosphatidylinositol-(4,5)-bisphosphate in host cell membrane, thus disrupting the membrane localization of the cleaved GSDMD to inhibit cytokine release and pyroptosis of macrophages. Notably, this phosphatase activity requires PtpB binding to ubiquitin. Disrupting phospholipid phosphatase activity or the ubiquitin-interacting motif of PtpB enhanced host GSDMD-dependent immune responses and reduced intracellular pathogen survival. Thus, pathogens inhibit pyroptosis and counteract host immunity by altering host membrane composition.

Comparing timelines and evidence available to support new TB, HIV, and HCV drug approvals: The same, only different

Background

Tuberculosis (TB), human immunodeficiency virus (HIV), and hepatitis C virus (HCV) share a global presence and propensity to disproportionately affect marginalized populations. However, over recent decades, many fewer drugs have been brought to market for TB than for the others. Although three new anti-TB drugs have been approved in the US or Europe in the last 10 years, uptake of these drugs has been limited. Using case examples of drugs developed recently for TB, HIV, and HCV, we explore possible reasons. We examine the use and effect of regulatory pathways intended to address weak economic incentives in the face of urgent, unmet needs; evaluate the extent of data underpinning authorizations for these indications; document development timelines and evidence available at the time of each approval; consider explanations for observed differences; and discuss the implications for clinical guidelines and use.

Methods and findings

For each indication, we selected two drugs: one recently approved and one approved between 2012 and 2014, when the first new anti-TB drug from a novel class in more than 40 years received marketing authorization. We calculated time from first published peer-reviewed evidence of activity to date of approval; the number of phase 1, 2, and 3 trials; the number of trial participants randomized to treatment arms containing the drug; and the total number of participants in each trial from the individual drug approval packages. We found that the two TB drugs took longer to gain approval (8.0 and 19.2 years for bedaquiline and pretomanid, respectively) despite availing of special regulatory pathways meant to expedite approval, when compared to the HIV (2.6 years for dolutegravir and 4.7 years for doravirine) and HCV drugs (3.2 and 1.6 years for sofosbuvir and glecaprevir/pibrentasvir, respectively). Moreover, fewer participants were studied prior to TB drug approvals (380 and 879) than prior to approvals for HIV (1598 and 979) and for HCV (2291 and 2448) drugs.

Conclusions

The dramatic disparities observed in TB drug development reaffirm the importance of several actions. Increased investment in TB research and development is necessary to rapidly advance drugs through the pipeline. Development plans and partnerships must provide safety and efficacy evidence on combinations and durations that are relevant to real-world use in heterogeneous populations. Reliable, validated surrogate markers of relapse-free cure are essential to decrease the duration and cost of TB treatment trials and increase the confidence and speed with which new regimens can advance. Lastly, regulators and normative bodies must maintain high evidentiary standards for authorization while ensuring timely and broad approval for TB drugs and regimens.

Pharmacometrics in tuberculosis: progress and opportunities

Tuberculosis remains one of the leading causes of death by a communicable agent, infecting up to one-quarter of the world's population, predominantly in disadvantaged communities. Pharmacometrics employs quantitative mathematical models to describe the relationships between pharmacokinetics and pharmacodynamics, and to predict drug doses, exposures, and responses. Pharmacometric approaches have provided a scientific basis for improved dosing of antituberculosis drugs and concomitantly administered antiretrovirals at the population level. The development of modelling frameworks including physiologically-based pharmacokinetics, quantitative systems pharmacology and machine learning provides an opportunity to extend the role of pharmacometrics to in silico quantification of drug-drug interactions, prediction of doses for special populations, dose optimization and individualization, and understanding the complex exposure-response relationships of multidrug regimens in terms of both efficacy and safety, informing regimen design for future study. In this short clinically-focused review, we explore what has been done, and what opportunities exist for pharmacometrics to impact tuberculosis pharmacotherapy.

Drug development challenges in nontuberculous mycobacterial lung disease: TB to the rescue

Nontuberculous mycobacterial pulmonary disease (NTM-PD) is treated with multiple repurposed drugs. Chemotherapy is long and often toxic, includes parenteral drugs, and suffers from poor cure rates. There is an urgent need for more efficacious, tolerated, and oral antibiotics optimized towards the treatment of NTM-PD, adapted to the spectrum of disease. In contrast to the empty NTM pipeline, drug development for the related tuberculosis lung disease has experienced a renaissance. Here, we argue that applying lessons learned from tuberculosis will facilitate the discovery of curative oral regimens for NTM-PD.

Development of Predictive Classification Models for Whole Cell Antimycobacterial Activity of Benzothiazinones

Nitrobenzothiazinones (BTZs) are a very potent class of antibiotics against Mycobacterium tuberculosis. However, relationships between their structural properties and whole cell activity remain poorly predictable. Herein, we present the synthesis and antimycobacterial evaluation of a diverse set of BTZs. High potency was predominantly achieved by piperidine and piperazine substitutions, whereupon three compounds were identified as promising candidates, showing preferable metabolic stability. Lack of correlation between potency and calculated binding energies suggested that target inhibition is not the only requirement to obtain suitable antimycobacterial agents. In contrast, prediction of whole cell activity class was successfully accomplished by extensively validated machine learning models. The performance of the superior model was further verified by >70% correct class predictions for a large set of reported BTZs. Our generated model is thus a key prerequisite to streamline lead optimization endeavors, particularly regarding the improvement of overall hit rates in whole cell antimycobacterial assays.

Types and functions of heterogeneity in mycobacteria

The remarkable ability of Mycobacterium tuberculosis to survive attacks from the host immune response and drug treatment is due to the resilience of a few bacilli rather than a result of survival of the entire population. Maintenance of mycobacterial subpopulations with distinct phenotypic characteristics is key for survival in the face of dynamic and variable stressors encountered during infection. Mycobacterial populations develop a wide range of phenotypes through an innate asymmetric growth pattern and adaptation to fluctuating microenvironments during infection that point to heterogeneity being a vital survival strategy. In this Review, we describe different types of mycobacterial heterogeneity and discuss how heterogeneity is generated and regulated in response to environmental cues. We discuss how this heterogeneity may have a key role in recording memory of their environment at both the single-cell level and the population level to give mycobacterial populations plasticity to withstand complex stressors.

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.

A rabbit model to study antibiotic penetration at the site of infection for non-tuberculous mycobacterial lung disease: macrolide case study

Nontuberculous mycobacterial pulmonary disease (NTM-PD) is a potentially fatal infectious disease requiring long treatment duration with multiple antibiotics and against which there is no reliable cure. Among the factors that have hampered the development of adequate drug regimens is the lack of an animal model that reproduces the NTM lung pathology required for studying antibiotic penetration and efficacy. Given the documented similarities between tuberculosis and NTM immunopathology in patients, we first determined that the rabbit model of active tuberculosis reproduces key features of human NTM-PD and provides an acceptable surrogate model to study lesion penetration. We focused on clarithromycin, a macrolide and pillar of NTM-PD treatment, and explored the underlying causes of the disconnect between its favorable potency and pharmacokinetics, and inconsistent clinical outcome. To quantify pharmacokinetic-pharmacodynamic target attainment at the site of disease, we developed a translational model describing clarithromycin distribution from plasma to lung lesions, including the spatial quantitation of clarithromycin and azithromycin in mycobacterial lesions of two patients on long-term macrolide therapy. Through clinical simulations, we visualized the coverage of clarithromycin in plasma and four disease compartments, revealing heterogeneous bacteriostatic and bactericidal target attainment depending on the compartment and the corresponding potency against nontuberculous mycobacteria in clinically relevant assays. Overall, clarithromycin's favorable tissue penetration and lack of bactericidal activity indicated that its clinical activity is limited by pharmacodynamic rather than pharmacokinetic factors. Our results pave the way towards the simulation of lesion pharmacokinetic-pharmacodynamic coverage by multi-drug combinations, to enable the prioritization of promising regimens for clinical trials.

A Systematic Review of Economic Evaluations of Active Tuberculosis Treatments

Background: The disease burden of active tuberculosis (TB) is considerable, but systematic reviews of economic evaluations of active TB treatments are scarce. Methods: PubMed, EMBASE, and the Cochrane Library databases were used to search for articles on cost-effectiveness analysis or cost-utility analysis that economically evaluated active TB treatments, which were then systematically reviewed by two independent reviewers. We extracted vital components of the included studies, such as country, population, intervention/comparator, primary outcome, values of outcomes, thresholds, model type, time horizon, and health states included in the model. Results: Seventeen studies were included in this systematic review. Thirteen dealt with interventions of medications, and the remaining four compared care strategies. The Markov model was the most commonly used tool to compare medications, whereas studies on care plans mainly used decision trees. The most commonly used primary outcome was disability-adjusted life years, followed by quality-adjusted life years. For treatment-naïve TB, the 4-month regimen was more cost-effective than the 6-month regimen mainly in low- and middle-income countries. For multidrug-resistant TB, a bedaquiline-based regimen was cost-effective. For multidrug-resistant TB, decentralized care that employed the use of home or mobile devices was more cost-effective than hospital-based centralized care in low- and middle-income countries. Conclusion: New treatment strategies to improve therapeutic outcomes by enhancing treatment adherence, such as regimens with shorter durations (2 or 4 months) and decentralized care, or new anti-TB agents (e.g., bedaquiline) have been suggested as cost-effective interventions for active TB. This review provides information on the economic evaluation of active TB from good-quality studies, thus aiding the future economic evaluation of active TB.

Host-directed therapies for tuberculosis: quantitative systems pharmacology approaches

Host-directed therapies (HDTs) that modulate host-pathogen interactions offer an innovative strategy to combat Mycobacterium tuberculosis (Mtb) infections. When combined with tuberculosis (TB) antibiotics, HDTs could contribute to improving treatment outcomes, reducing treatment duration, and preventing resistance development. Translation of the interplay of host-pathogen interactions leveraged by HDTs towards therapeutic outcomes in patients is challenging. Quantitative understanding of the multifaceted nature of the host-pathogen interactions is vital to rationally design HDT strategies. Here, we (i) provide an overview of key Mtb host-pathogen interactions as basis for HDT strategies; and (ii) discuss the components and utility of quantitative systems pharmacology (QSP) models to inform HDT strategies. QSP models can be used to identify and optimize treatment targets, to facilitate preclinical to human translation, and to design combination treatment strategies.

Interleukin-13 overexpressing mice represent an advanced pre-clinical model for detecting the distribution of anti-mycobacterial drugs within centrally necrotizing granulomas

The Mycobacterium tuberculosis-harboring granuloma with a necrotic center surrounded by a fibrous capsule is the hallmark of tuberculosis (TB). For a successful treatment, antibiotics need to penetrate these complex structures to reach their bacterial targets. Hence, animal models reflecting the pulmonary pathology of TB patients are of particular importance to improve the preclinical validation of novel drug candidates. M. tuberculosis-infected interleukin-13-overexpressing (IL-13^tg) mice develop a TB pathology very similar to patients and, in contrast to other mouse models, also share pathogenetic mechanisms. Accordingly, IL-13^tg animals represent an ideal model for analyzing the penetration of novel anti-TB drugs into various compartments of necrotic granulomas by matrix-assisted laser desorption/ionization–mass spectrometry imaging (MALDI-MS imaging). In the present study, we evaluated the suitability of BALB/c IL-13^tg mice for determining the antibiotic distribution within necrotizing lesions. To this end, we established a workflow based on the inactivation of M. tuberculosis by gamma irradiation while preserving lung tissue integrity and drug distribution, which is essential for correlating drug penetration with lesion pathology. MALDI-MS imaging analysis of clofazimine, pyrazinamide, and rifampicin revealed a drug-specific distribution within different lesion types, including cellular granulomas, developing in BALB/c wild-type mice, and necrotic granulomas in BALB/c IL-13^tg animals, emphasizing the necessity of preclinical models reflecting human pathology. Most importantly, our study demonstrates that BALB/c IL-13^tg mice recapitulate the penetration of antibiotics into human lesions. Therefore, our workflow in combination with the IL-13^tg mouse model provides an improved and accelerated evaluation of novel anti-TB drugs and new regimens in the preclinical stage.

Emerging Therapeutics, Technologies, and Drug Development Strategies to Address Patient Nonadherence and Improve Tuberculosis Treatment

Imperfect medication adherence remains the biggest predictor of treatment failure for patients with tuberculosis. Missed doses during treatment lead to relapse, tuberculosis resistance, and further spread of disease. Understanding individual patient phenotypes, population pharmacokinetics, resistance development, drug distribution to tuberculosis lesions, and pharmacodynamics at the site of infection is necessary to fully measure the impact of adherence on patient outcomes. To decrease the impact of expected variability in drug intake on tuberculosis outcomes, an improvement in patient adherence and new forgiving regimens that protect against missed doses are needed. In this review, we summarize emerging technologies to improve medication adherence in clinical practice and provide suggestions on how digital adherence technologies can be incorporated in clinical trials and practice and the drug development pipeline that will lead to more forgiving regimens and benefit patients suffering from tuberculosis. Expected final online publication date for the Annual Review of Pharmacology and Toxicology, Volume 62 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

The Treatment of Tuberculosis

Tuberculosis (TB) remains a leading cause of infectious death worldwide, and poverty is a major driver. Clinically, TB presents as "latent" TB and active TB disease, and the treatment for each is different. TB drugs can display "early bactericidal activity (EBA)" and / or "sterilizing activity" (clearing persisters). Isoniazid is excellent at the former, and rifampin is excellent at the latter. Pyrazinamide and ethambutol complete the first-line regimen for drug-susceptible TB, each playing a specific role. Drug-resistant TB is an increasing concern, being met, in part, with repurposed drugs (including moxifloxacin, levofloxacin, linezolid, clofazimine, and beta-lactams) and new drugs (including bedaquiline, pretomanid, and delamanid). One challenge is to select drugs without overlapping adverse drug reaction profiles. QTc interval prolongation is one such concern, but to date, it has been manageable. Drug penetration into organism sanctuaries, such as the central nervous system, bone, and pulmonary TB cavities remain important challenges. The pharmacodynamics of most TB drugs can be described by the area under the curve (AUC) divided by the minimal inhibitory concentration (MIC). The hollow fiber infection model (HFIM) and various animal models (especially mouse and macaque) allow for sophisticated pharmacokinetic/pharmacodynamic experiments. These experiments may hasten the selection of the most potent, shortest possible regimens to treat even extremely drug resistant TB. These findings can be translated to humans by optimizing drug exposure in each patient, using therapeutic drug monitoring and dose individualization.

Model-Informed Drug Development for Anti-Infectives: State of the Art and Future

Model-informed drug development (MIDD) has a long and rich history in infectious diseases. This review describes foundational principles of translational anti-infective pharmacology, including choice of appropriate measures of exposure and pharmacodynamic (PD) measures, patient subpopulations, and drug-drug interactions. Examples are presented for state-of-the-art, empiric, mechanistic, interdisciplinary, and real-world evidence MIDD applications in the development of antibacterials (review of minimum inhibitory concentration-based models, mechanism-based pharmacokinetic/PD (PK/PD) models, PK/PD models of resistance, and immune response), antifungals, antivirals, drugs for the treatment of global health infectious diseases, and medical countermeasures. The degree of adoption of MIDD practices across the infectious diseases field is also summarized. The future application of MIDD in infectious diseases will progress along two planes; "depth" and "breadth" of MIDD methods. "MIDD depth" refers to deeper incorporation of the specific pathogen biology and intrinsic and acquired-resistance mechanisms; host factors, such as immunologic response and infection site, to enable deeper interrogation of pharmacological impact on pathogen clearance; clinical outcome and emergence of resistance from a pathogen; and patient and population perspective. In particular, improved early assessment of the emergence of resistance potential will become a greater focus in MIDD, as this is poorly mitigated by current development approaches. "MIDD breadth" refers to greater adoption of model-centered approaches to anti-infective development. Specifically, this means how various MIDD approaches and translational tools can be integrated or connected in a systematic way that supports decision making by key stakeholders (sponsors, regulators, and payers) across the entire development pathway.