Open AccessApplying Optimization Algorithms to Tuberculosis Antibiotic Treatment Regimens
Author(s) -
Joseph M. Cicchese,
Elsje Pienaar,
Denise E. Kirschner,
Jennifer J. Linderman
Publication year - 2017
Publication title -
cellular and molecular bioengineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.668
H-Index - 34
eISSN - 1865-5033
pISSN - 1865-5025
DOI - 10.1007/s12195-017-0507-6
Subject(s) - tuberculosis , antibiotics , computer science , medicine , intensive care medicine , algorithm , biology , microbiology and biotechnology , pathology
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.