In silico evaluation and exploration of antibiotic tuberculosis treatment regimens

Pienaar, Elsje; Dartois, Véronique; Linderman, Jennifer J.; Kirschner, Denise E.

doi:10.1186/s12918-015-0221-8

Title: In silico evaluation and exploration of antibiotic tuberculosis treatment regimens

Journal Article · 14 November 2015 · BMC Systems Biology

DOI: https://doi.org/10.1186/s12918-015-0221-8 · OSTI ID:1241146

Pienaar, Elsje ^[1]; Dartois, Véronique ^[2]; Linderman, Jennifer J. ^[3]; Kirschner, Denise E. ^[4]

Univ. of Michigan, Ann Arbor, MI (United States); Univ. of Michigan Medical School, Ann Arbor, MI (United States)
The State Univ. of New Jersey, New Brunswick, NJ (United States)
Univ. of Michigan, Ann Arbor, MI (United States)
Univ. of Michigan Medical School, Ann Arbor, MI (United States)

Improvement in tuberculosis treatment regimens requires selection of antibiotics and dosing schedules from a large design space of possibilities. Incomplete knowledge of antibiotic and host immune dynamics in tuberculosis granulomas impacts clinical trial design and success, and variations among clinical trials hamper side-by-side comparison of regimens. Our objective is to systematically evaluate the efficacy of isoniazid and rifampin regimens, and identify modifications to these antibiotics that improve treatment outcomes. We pair a spatio-temporal computational model of host immunity with pharmacokinetic and pharmacodynamic data on isoniazid and rifampin. The model is calibrated to plasma pharmacokinetic and granuloma bacterial load data from non-human primate models of tuberculosis and to tissue and granuloma measurements of isoniazid and rifampin in rabbit granulomas. We predict the efficacy of regimens containing different doses and frequencies of isoniazid and rifampin. We predict impacts of pharmacokinetic/pharmacodynamic modifications on antibiotic efficacy. We demonstrate that suboptimal antibiotic concentrations within granulomas lead to poor performance of intermittent regimens compared to daily regimens. Improvements from dose and frequency changes are limited by inherent antibiotic properties, and we propose that changes in intracellular accumulation ratios and antimicrobial activity would lead to the most significant improvements in treatment outcomes. Results suggest that an increased risk of drug resistance in fully intermittent as compared to daily regimens arises from higher bacterial population levels early during treatment. In conclusion, our systems pharmacology approach complements efforts to accelerate tuberculosis therapeutic development.

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Research Organization:: Univ. of California (United States)

Sponsoring Organization:: USDOE Office of Science (SC)

Grant/Contract Number:: AC02-05CH11231

OSTI ID:: 1241146

Journal Information:: BMC Systems Biology, Vol. 9, Issue 1; ISSN 1752-0509

Publisher:: BioMed CentralCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 31 works

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Metronidazole prevents reactivation of latent Mycobacterium tuberculosis infection in macaques Lin, P. L.; Dartois, V.; Johnston, P. J. Proceedings of the National Academy of Sciences, Vol. 109, Issue 35 https://doi.org/10.1073/pnas.1121497109	journal	July 2012
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Design and synthesis of antituberculars: preparation and evaluation against Mycobacterium tuberculosis of an isoniazid Schiff base Hearn, M. J. Journal of Antimicrobial Chemotherapy, Vol. 53, Issue 2 https://doi.org/10.1093/jac/dkh041	journal	January 2004
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American Thoracic Society/Centers for Disease Control and Prevention/Infectious Diseases Society of America Treatment of Tuberculosis American Journal of Respiratory and Critical Care Medicine, Vol. 167, Issue 4, p. 603-662 https://doi.org/10.1164/rccm.167.4.603	journal	February 2003
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Standardized Treatment of Active Tuberculosis in Patients with Previous Treatment and/or with Mono-resistance to Isoniazid: A Systematic Review and Meta-analysis Menzies, Dick; Benedetti, Andrea; Paydar, Anita PLoS Medicine, Vol. 6, Issue 9 https://doi.org/10.1371/journal.pmed.1000150	journal	September 2009
Multi-Scale Modeling Predicts a Balance of Tumor Necrosis Factor-α and Interleukin-10 Controls the Granuloma Environment during Mycobacterium tuberculosis Infection Cilfone, Nicholas A.; Perry, Cory R.; Kirschner, Denise E. PLoS ONE, Vol. 8, Issue 7 https://doi.org/10.1371/journal.pone.0068680	journal	July 2013
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QSAR Based Design of New Antitubercular Compounds: Improved Isoniazid Derivatives Against Multidrug-Resistant TB Martins, Filomena; Ventura, Cristina; Santos, Susana Current Pharmaceutical Design, Vol. 20, Issue 27 https://doi.org/10.2174/1381612819666131118164434	journal	November 2013
DFT Based QSAR/QSPR Models in the Development of Novel Anti-tuberculosis Drugs Targeting Mycobacterium tuberculosis Rajkhowa, Sanchaita; Deka, Ramesh Current Pharmaceutical Design, Vol. 20, Issue 27 https://doi.org/10.2174/1381612819666131118165824	journal	November 2013
Multiscale Computational Modeling Reveals a Critical Role for TNF-α Receptor 1 Dynamics in Tuberculosis Granuloma Formation Fallahi-Sichani, Mohammad; El-Kebir, Mohammed; Marino, Simeone The Journal of Immunology, Vol. 186, Issue 6 https://doi.org/10.4049/jimmunol.1003299	journal	February 2011
Differential Risk of Tuberculosis Reactivation among Anti-TNF Therapies Is Due to Drug Binding Kinetics and Permeability Fallahi-Sichani, Mohammad; Flynn, JoAnne L.; Linderman, Jennifer J. The Journal of Immunology, Vol. 188, Issue 7 https://doi.org/10.4049/jimmunol.1103298	journal	February 2012
Computational Modeling Predicts IL-10 Control of Lesion Sterilization by Balancing Early Host Immunity–Mediated Antimicrobial Responses with Caseation during Mycobacterium tuberculosis Infection Cilfone, Nicholas A.; Ford, Christopher B.; Marino, Simeone The Journal of Immunology, Vol. 194, Issue 2 https://doi.org/10.4049/jimmunol.1400734	journal	December 2014

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Integrating mathematical models with experimental data to investigate the within-host dynamics of bacterial infections Vlazaki, Myrto; Huber, John; Restif, Olivier Pathogens and Disease, Vol. 77, Issue 8 https://doi.org/10.1093/femspd/ftaa001	journal	November 2019
Multifidelity Analysis for Predicting Rare Events in Stochastic Computational Models of Complex Biological Systems Pienaar, Elsje Biomedical Engineering and Computational Biology, Vol. 9 https://doi.org/10.1177/1179597218790253	journal	January 2018
Leukocyte Motility Models Assessed through Simulation and Multi-objective Optimization-Based Model Selection Read, Mark N.; Bailey, Jacqueline; Timmis, Jon PLOS Computational Biology, Vol. 12, Issue 9 https://doi.org/10.1371/journal.pcbi.1005082	journal	September 2016
Using Chemical Reaction Kinetics to Predict Optimal Antibiotic Treatment Strategies Abel zur Wiesch, Pia; Clarelli, Fabrizio; Cohen, Ted PLOS Computational Biology, Vol. 13, Issue 1 https://doi.org/10.1371/journal.pcbi.1005321	journal	January 2017
Comparing efficacies of moxifloxacin, levofloxacin and gatifloxacin in tuberculosis granulomas using a multi-scale systems pharmacology approach Pienaar, Elsje; Sarathy, Jansy; Prideaux, Brendan PLOS Computational Biology, Vol. 13, Issue 8 https://doi.org/10.1371/journal.pcbi.1005650	journal	August 2017
Emergence and selection of isoniazid and rifampin resistance in tuberculosis granulomas Pienaar, Elsje; Linderman, Jennifer J.; Kirschner, Denise E. PLOS ONE, Vol. 13, Issue 5 https://doi.org/10.1371/journal.pone.0196322	journal	May 2018
Quantifying Limits on Replication, Death, and Quiescence of Mycobacterium tuberculosis in Mice McDaniel, Margaret M.; Krishna, Nitin; Handagama, Winode G. Frontiers in Microbiology, Vol. 7 https://doi.org/10.3389/fmicb.2016.00862	journal	June 2016
Both Pharmacokinetic Variability and Granuloma Heterogeneity Impact the Ability of the First-Line Antibiotics to Sterilize Tuberculosis Granulomas Cicchese, Joseph M.; Dartois, Véronique; Kirschner, Denise E. Frontiers in Pharmacology, Vol. 11 https://doi.org/10.3389/fphar.2020.00333	journal	March 2020

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Similar Records

A computational tool integrating host immunity with antibiotic dynamics to study tuberculosis treatment

Journal Article · 2014 · Journal of Theoretical Biology · OSTI ID:1344478

Pienaar, Elsje; Cilfone, Nicholas A.; Lin, Philana Ling; +6 more

Emergence and selection of isoniazid and rifampin resistance in tuberculosis granulomas

Journal Article · 2018 · PLoS ONE · OSTI ID:1544032

Pienaar, Elsje; Linderman, Jennifer J.; Kirschner, Denise E.; +1 more

Comparing efficacies of moxifloxacin, levofloxacin and gatifloxacin in tuberculosis granulomas using a multi-scale systems pharmacology approach

Journal Article · 2017 · PLoS Computational Biology (Online) · OSTI ID:1375507

Pienaar, Elsje; Sarathy, Jansy; Prideaux, Brendan; +5 more

Related Subjects

60 APPLIED LIFE SCIENCES
computational model
pharmacokinetic/pharmacodynamic
isoniazid
Rifampin
tissue distribution

In silico evaluation and exploration of antibiotic tuberculosis treatment regimens [Supplementary Data] Pienaar, Elsje; Dartois, VĂŠronique; Linderman, Jennifer https://doi.org/10.6084/m9.figshare.c.3602969 The current record is supplemented by this dataset	dataset	November 2015
In silico evaluation and exploration of antibiotic tuberculosis treatment regimens [Supplemental Data] Pienaar, Elsje; Dartois, Véronique; Linderman, Jennifer https://doi.org/10.6084/m9.figshare.c.3602969.v1 The current record is supplemented by this dataset	dataset	November 2015
Additional file 1: Figure S1. of In silico evaluation and exploration of antibiotic tuberculosis treatment regimens Pienaar, Elsje; Dartois, VĂŠronique; Linderman, Jennifer https://doi.org/10.6084/m9.figshare.c.3602969_d1 The current record is supplemented by this text	text	January 2015
Additional file 1: Figure S1. of In silico evaluation and exploration of antibiotic tuberculosis treatment regimens Pienaar, Elsje; Dartois, Véronique; Linderman, Jennifer https://doi.org/10.6084/m9.figshare.c.3602969_d1.v1 The current record is supplemented by this figure	figure	November 2015