title: Systematic Analysis of Hollow Fiber Model of Tuberculosis Experiments.
abstract: BACKGROUND
  The in vitro hollow fiber system model of tuberculosis (HFS-TB), in tandem with Monte Carlo experiments, was introduced more than a decade ago. Since then, it has been used to perform a large number of tuberculosis pharmacokinetics/pharmacodynamics (PK/PD) studies that have not been subjected to systematic analysis.
  
  
  METHODS
  We performed a literature search to identify all HFS-TB experiments published between 1 January 2000 and 31 December 2012. There was no exclusion of articles by language. Bias minimization was according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Steps for reporting systematic reviews were followed.
  
  
  RESULTS
  There were 22 HFS-TB studies published, of which 12 were combination therapy studies and 10 were monotherapy studies. There were 4 stand-alone Monte Carlo experiments that utilized quantitative output from the HFS-TB. All experiments reported drug pharmacokinetics, which recapitulated those encountered in humans. HFS-TB studies included log-phase growth studies under ambient air, semidormant bacteria at pH 5.8, and nonreplicating persisters at low oxygen tension of ≤ 10 parts per billion. The studies identified antibiotic exposures associated with optimal kill of Mycobacterium tuberculosis and suppression of acquired drug resistance (ADR) and informed predictions about optimal clinical doses, expected performance of standard doses and regimens in patients, and expected rates of ADR, as well as a proposal of new susceptibility breakpoints.
  
  
  CONCLUSIONS
  The HFS-TB model offers the ability to perform PK/PD studies including humanlike drug exposures, to identify bactericidal and sterilizing effect rates, and to identify exposures associated with suppression of drug resistance. Because of the ability to perform repetitive sampling from the same unit over time, the HFS-TB vastly improves statistical power and facilitates the execution of time-to-event analyses and repeated event analyses, as well as dynamic system pharmacology mathematical models.
authors.affiliation: Center for Infectious Diseases Research and Experimental Therapeutics, Baylor Research Institute, Baylor University Medical Center, Dallas, Texas.
authors.forename: Jotam G
authors.initials: JG
authors.lastname: Pasipanodya
authors.affiliation: Center for Tuberculosis Research, Division of Infectious Diseases, Johns Hopkins University School of Medicine, Baltimore, Maryland.
authors.forename: Eric
authors.initials: E
authors.lastname: Nuermberger
authors.affiliation: Critical Path Institute, Tucson, Arizona.
authors.forename: Klaus
authors.initials: K
authors.lastname: Romero
authors.affiliation: Critical Path Institute, Tucson, Arizona.
authors.forename: Debra
authors.initials: D
authors.lastname: Hanna
authors.affiliation: Center for Infectious Diseases Research and Experimental Therapeutics, Baylor Research Institute, Baylor University Medical Center, Dallas, Texas Department of Medicine, University of Cape Town, Observatory, South Africa.
authors.forename: Tawanda
authors.initials: T
authors.lastname: Gumbo
mesh_terms: D000995:Antitubercular Agents / Q000494:pharmacology* / Q000627:therapeutic use*; D055808:Drug Discovery / Q000379:methods*; D004353:Drug Evaluation, Preclinical; D004359:Drug Therapy, Combination; D006801:Humans; D066298:In Vitro Techniques; D008954:Models, Biological; D009010:Monte Carlo Method; D009169:Mycobacterium tuberculosis / Q000187:drug effects*; D014376:Tuberculosis / Q000188:drug therapy*
chemical_list: D000995:Antitubercular Agents
keywords: Monte Carlo experiments; PK/PD; hollow fiber system; quantitative drug development tool; tuberculosis