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Title: Applying Optimization Algorithms to Tuberculosis Antibiotic Treatment Regimens

Abstract

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.

Authors:
 [1];  [2];  [3];  [1]
  1. University of Michigan, Ann Arbor, MI (United States). Department of Chemical Engineering
  2. University of Michigan, Ann Arbor, MI (United States). Department of Chemical Engineering; University of Michigan Medical School, Ann Arbor, MI (United States). Department of Microbiology and Immunology
  3. University of Michigan Medical School, Ann Arbor, MI (United States). Department of Microbiology and Immunology
Publication Date:
Research Org.:
Lawrence Berkeley National Laboratory, Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC).
Sponsoring Org.:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)
OSTI Identifier:
1461962
DOE Contract Number:  
AC02-05CH11231
Resource Type:
Journal Article
Journal Name:
Cellular and Molecular Bioengineering
Additional Journal Information:
Journal Volume: 10; Journal Issue: 6; Journal ID: ISSN 1865-5025
Country of Publication:
United States
Language:
English

Citation Formats

Cicchese, Joseph M., Pienaar, Elsje, Kirschner, Denise E., and Linderman, Jennifer J. Applying Optimization Algorithms to Tuberculosis Antibiotic Treatment Regimens. United States: N. p., 2017. Web. doi:10.1007/s12195-017-0507-6.
Cicchese, Joseph M., Pienaar, Elsje, Kirschner, Denise E., & Linderman, Jennifer J. Applying Optimization Algorithms to Tuberculosis Antibiotic Treatment Regimens. United States. doi:10.1007/s12195-017-0507-6.
Cicchese, Joseph M., Pienaar, Elsje, Kirschner, Denise E., and Linderman, Jennifer J. Wed . "Applying Optimization Algorithms to Tuberculosis Antibiotic Treatment Regimens". United States. doi:10.1007/s12195-017-0507-6.
@article{osti_1461962,
title = {Applying Optimization Algorithms to Tuberculosis Antibiotic Treatment Regimens},
author = {Cicchese, Joseph M. and Pienaar, Elsje and Kirschner, Denise E. and Linderman, Jennifer J.},
abstractNote = {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.},
doi = {10.1007/s12195-017-0507-6},
journal = {Cellular and Molecular Bioengineering},
issn = {1865-5025},
number = 6,
volume = 10,
place = {United States},
year = {2017},
month = {8}
}