title: Drug regimens identified and optimized by output-driven platform markedly reduce tuberculosis treatment time.
abstract: The current drug regimens for treating tuberculosis are lengthy and onerous, and hence complicated by poor adherence leading to drug resistance and disease relapse. Previously, using an output-driven optimization platform and an in vitro macrophage model of Mycobacterium tuberculosis infection, we identified several experimental drug regimens among billions of possible drug-dose combinations that outperform the current standard regimen. Here we use this platform to optimize the in vivo drug doses of two of these regimens in a mouse model of pulmonary tuberculosis. The experimental regimens kill M. tuberculosis much more rapidly than the standard regimen and reduce treatment time to relapse-free cure by 75%. Thus, these regimens have the potential to provide a markedly shorter course of treatment for tuberculosis in humans. As these regimens omit isoniazid, rifampicin, fluoroquinolones and injectable aminoglycosides, they would be suitable for treating many cases of multidrug and extensively drug-resistant tuberculosis.
authors.affiliation: Division of Infectious Diseases, Department of Medicine, University of California, Los Angeles, California 90095, USA.
authors.forename: Bai-Yu
authors.initials: BY
authors.lastname: Lee
authors.affiliation: Division of Infectious Diseases, Department of Medicine, University of California, Los Angeles, California 90095, USA.
authors.forename: Daniel L
authors.initials: DL
authors.lastname: Clemens
authors.affiliation: Department of Mechanical and Aerospace Engineering, University of California, Los Angeles, California 90095, USA.
authors.forename: Aleidy
authors.initials: A
authors.lastname: Silva
authors.affiliation: Division of Infectious Diseases, Department of Medicine, University of California, Los Angeles, California 90095, USA.
authors.forename: Barbara Jane
authors.initials: BJ
authors.lastname: Dillon
authors.affiliation: Division of Infectious Diseases, Department of Medicine, University of California, Los Angeles, California 90095, USA.
authors.forename: Saša
authors.initials: S
authors.lastname: Masleša-Galić
authors.affiliation: Division of Infectious Diseases, Department of Medicine, University of California, Los Angeles, California 90095, USA.
authors.forename: Susana
authors.initials: S
authors.lastname: Nava
authors.affiliation: Med-X Research Institute, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, China.
authors.forename: Xianting
authors.initials: X
authors.lastname: Ding
authors.affiliation: Department of Mechanical and Aerospace Engineering, University of California, Los Angeles, California 90095, USA.|Department of Bioengineering, University of California, Los Angeles, California 90095, USA.
authors.forename: Chih-Ming
authors.initials: CM
authors.lastname: Ho
authors.affiliation: Division of Infectious Diseases, Department of Medicine, University of California, Los Angeles, California 90095, USA.
authors.forename: Marcus A
authors.initials: MA
authors.lastname: Horwitz
mesh_terms: D000818:Animals; D000995:Antitubercular Agents / Q000494:pharmacology* / Q000627:therapeutic use; D015169:Colony Count, Microbial; D004195:Disease Models, Animal; D004305:Dose-Response Relationship, Drug; D004347:Drug Interactions; D004359:Drug Therapy, Combination / Q000379:methods; D005260:Female; D006801:Humans; D055118:Medication Adherence; D051379:Mice; D008807:Mice, Inbred BALB C; D009169:Mycobacterium tuberculosis / Q000187:drug effects* / Q000302:isolation & purification; D013047:Specific Pathogen-Free Organisms; D013997:Time Factors; D016896:Treatment Outcome; D018088:Tuberculosis, Multidrug-Resistant / Q000188:drug therapy* / Q000382:microbiology; D014397:Tuberculosis, Pulmonary / Q000188:drug therapy* / Q000382:microbiology
chemical_list: D000995:Antitubercular Agents