A multi-scale approach to designing therapeutics for tuberculosis

Linderman, Jennifer J.; Cilfone, Nicholas A.; Pienaar, Elsje; Gong, Chang; Kirschner, Denise E.

doi:10.1039/c4ib00295d

Cited by 25 publications

(29 citation statements)

References 130 publications

(316 reference statements)

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“…Briefly, this multi-scale, hybrid model incorporates an agent-based model, ordinary differential equations (ODEs) and partial differential equations (PDEs) to describe and simulate granuloma formation and function, and has been developed based on experimental data from in vitro , mouse and non-human primate models. 9,13,30 The agent-based model operates on the molecular and cellular levels and reads out at a tissue scale; individual immune cells (such as T cells and macrophages) are modeled as agents that are recruited and interact with each other according to a set of rules (see http://malthus.micro.med.umich.edu/GranSim/). ODEs and PDEs are used to describe molecular scale events, such as receptor-ligand binding or cytokine and antibiotic diffusion, which are solved through the implementation of efficient numerical solvers.…”

Section: Model and Methodsmentioning

confidence: 99%

“…We simulate the dynamics of granuloma formation and function in the framework of a hybrid, multi-scale agent-based model. 9,13,30 These dynamics are crucial to understanding TB antibiotic efficacy, as the structure of granulomas influences antibiotic exposure to bacterial populations. 26,44,46 Although our model can assist in screening new antibiotic treatments, the computational complexity and number of granuloma simulations required to test all potential treatment regimens (Figure 1) prevents us from testing every possibility in the regimen design space.…”

Section: Introductionmentioning

confidence: 99%

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Applying Optimization Algorithms to Tuberculosis Antibiotic Treatment Regimens

et al. 2017

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Introduction Tuberculosis (TB), one of the most common infectious diseases, requires treatment with multiple antibiotics taken over at least 6 months. This long treatment often results in poor patient-adherence, which can lead to the emergence of multi-drug resistant TB. New antibiotic treatment strategies are sorely needed. New antibiotics are being developed or repurposed to treat TB, but as there are numerous potential antibiotics, dosing sizes and potential schedules, the regimen design space for new treatments is too large to search exhaustively. Here we propose a method that combines an agent-based multi-scale model capturing TB granuloma formation with algorithms for mathematical optimization to identify optimal TB treatment regimens. Methods We define two different single-antibiotic treatments to compare the efficiency and accuracy in predicting optimal treatment regimens of two optimization algorithms: genetic algorithms (GA) and surrogate-assisted optimization through radial basis function (RBF) networks. We also illustrate the use of RBF networks to optimize double-antibiotic treatments. Results We found that while GAs can locate optimal treatment regimens more accurately, RBF networks provide a more practical strategy to TB treatment optimization with fewer simulations, and successfully estimated optimal double-antibiotic treatment regimens. Conclusions Our results indicate surrogate-assisted optimization can locate optimal TB treatment regimens from a larger set of antibiotics, doses and schedules, and could be applied to solve optimization problems in other areas of research using systems biology approaches. Our findings have important implications for the treatment of diseases like TB that have lengthy protocols or for any disease that requires multiple drugs.

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Section: Model and Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Applying Optimization Algorithms to Tuberculosis Antibiotic Treatment Regimens

et al. 2017

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“…There are models that include genomics and systems biological networks, particularly signaling networks, that integrate stochastic simulations and differential equations [43,48,49,125]. Finally, there are hybrid multi-scale hierarchies that are implemented to integrate ordinary or partial differential equations with ABMs [46,95,97]. Currently, no multi-scale model covering the full range of scales has been successfully accomplished, from molecular/atomistic to organ/individual interactions, covering femtoseconds to hours.…”

Section: Computational Immunologymentioning

confidence: 99%

“…They predicted that chemotaxis increased total number of TC-DC contacts but decreased unique contacts between antigen-specific TCs and antigen-presenting DCs, producing less activated T-cells [83]. Subsequent refinements were developed to study T-cell and DC behavior, mediated by multiple cytokine signals and chemoattractants, after infection by Mycobacterium tuberculosis [49,[94][95][96][97]. Using these models, mechanisms that strongly correlate with better host-level outcomes have been identified, including elimination of uncontained lung granulomas by inducing low levels of lung tissue damage and inhibition of bacteria dissemination within the lung [96].…”

Section: Computational Immunologymentioning

confidence: 99%

Computational immuno-biology for organ transplantation and regenerative medicine

Vásquez-Montoya

Danobeitia

Fernández

et al. 2016

Transplantation Reviews

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“…However, computational studies based on rifapentine and isoniazid inhaled formulation have predicted that antibiotic concentrations in granulomas remain more stable over an entire dosing window (2 weeks) with inhaled formulations than with daily oral doses [27]. Furthermore, it is doubtful whether aerosol formulations will achieve sufficient therapeutic levels in the serum; and reducing the clearance rate of the drug from the lung without reducing the free concentration will still need to be achieved, losing the advantage of local delivery.…”

Section: Inhalation Therapy For Tbmentioning

confidence: 99%

Drug Delivery for tuberculosis: is Inhaled Therapy the Key to success?

Traini

Young

2017

Ther. Deliv.

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" The questions on the utility of inhaled TB therapy are still open-ended, but in a world where the risk of untreatable infections is ever-present, the need for continued research into TB, perhaps focusing on 'game changers' such as inhaled therapies, are of utmost importance. " Drug delivery for tuberculosisWorldwide, tuberculosis (TB) has 86% treatment success rate in new cases, leaving more than 1 million new patients without a cure [1]. Thus, the need for both shorter treatment regimens and new antibiotics is great. Current oral or injectable standard anti-TB drug regiments are well established and relatively inexpensive therapies. Still, it is evident from the rise of multidrug resistance TB (MDR-TB) worldwide, that among other factors, these approaches are not preferred among patients and healthcare professionals and, have been proven to have varying degrees of success.In the past few years there has been an enormous interest in developing more effective anti-TB vaccines [2,3], developing new anti-TB drugs that shortens treatment and exploiting the genome to accelerate the diagnosis and treatment of drug-resistant TB [4,5]. Importantly, there has also been a rising interest in developing anti-TB therapies via inhalation [6,7]. This is because, used as primary or adjunct to the current standard therapy for TB, inhaled therapy may hold the key as a potential new delivery mode that has improved health benefits. These are likely to include reduced treatment times and possibly limited insurgence of drug resistance. Specifically, for inhaled TB treatment, drugs should target alveolar macrophages that harbor microorganisms and/or maintain high drug concentration at the infection site in the lung [8]. Inhaled drug delivery offers this prospect and has the potential to achieve high concentrations of pharmacologic agents in the lungs, while producing adequate systemic concentrations through alveolar-capillary absorption to treat extrapulmonary sites of infection. It would seem that a localized delivery method would be intuitively attractive for a disease that is very often restricted, but not limited, to the lung. Inhalation therapy for TBInhalation therapy for TB is not a 'new' approach and began in the late 1940s when streptomycin started showing signs of resistance [9]. Since then, many different formulation approaches have been investigated. Micro [10,11], nanoparticles [12,13], liposomes [14], in situ forming liposomes [15], proliposomes [16,17] and liposphere [18], with single [19,20] and combination drugs [21,22], have all been manufactured with different degrees of success, although mostly limited to data collected in vitro or from preclinical studies where, for the majority, formulations were found effective in reducing bacterial counts. Nevertheless, there is no completed clinical study and it is difficult to identify which system would be the most advantageous to take further.Recent setbacks have also hindered research advances in this field, that is, the suspension of enrolment in STAND (Phase III combi...

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A multi-scale approach to designing therapeutics for tuberculosis

Cited by 25 publications

References 130 publications

Applying Optimization Algorithms to Tuberculosis Antibiotic Treatment Regimens

Applying Optimization Algorithms to Tuberculosis Antibiotic Treatment Regimens

Computational immuno-biology for organ transplantation and regenerative medicine

Drug Delivery for tuberculosis: is Inhaled Therapy the Key to success?

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