Systematic analysis of hollow fiber model of tuberculosis experiments

Clinical Infectious Diseases

Volumn 61, Issue , 2015, Pages S10-S17

  Pasipanodya, Jotam G ^a   Nuermberger, Eric ^b   Romero, Klaus ^c   Hanna, Debra ^c   Gumbo, Tawanda ^a,d  

^a BAYLOR RESEARCH INSTITUTE   (United States)

^b JOHNS HOPKINS UNIVERSITY SCHOOL OF MEDICINE   (United States)

^c CRITICAL PATH INSTITUTE   (United States)

^d UNIVERSITY OF CAPE TOWN   (South Africa)

Author keywords

Hollow fiber system; ; Monte Carlo experiments; PK PD; ; Quantitative drug development tool; ; Tuberculosis;

Indexed keywords

ANTIBIOTIC AGENT; TUBERCULOSTATIC AGENT;

AMBIENT AIR; ANTIBIOTIC THERAPY; AREA UNDER THE CURVE; ARTICLE; BACTERIAL GROWTH; BACTERICIDAL ACTIVITY; DRUG EXPOSURE; HUMAN; META ANALYSIS; MINIMUM INHIBITORY CONCENTRATION; MONOTHERAPY; MONTE CARLO METHOD; MYCOBACTERIUM TUBERCULOSIS; OXYGEN TENSION; POPULATION; PRIORITY JOURNAL; SYSTEMATIC REVIEW; TREATMENT DURATION; TUBERCULOSIS; BIOLOGICAL MODEL; COMBINATION DRUG THERAPY; DRUG DEVELOPMENT; DRUG EFFECTS; IN VITRO STUDY; PRECLINICAL STUDY; PROCEDURES;

ANTITUBERCULAR AGENTS; DRUG DISCOVERY; DRUG EVALUATION, PRECLINICAL; DRUG THERAPY, COMBINATION; HUMANS; IN VITRO TECHNIQUES; MODELS, BIOLOGICAL; MONTE CARLO METHOD; MYCOBACTERIUM TUBERCULOSIS; TUBERCULOSIS;

EID: 84942084271     PISSN: 10584838     EISSN: 15376591     Source Type: Journal    
DOI: 10.1093/cid/civ425     Document Type: Article

References (47)

1. World Health Organization. Guidelines for the programmatic management of drug-resistant tuberculosis. Geneva, Switzerland: WHO, 2011.
2. Dheda K, Gumbo T, Gandhi NR, et al. Global control of tuberculosis: from extensively drug-resistant to untreatable tuberculosis. Lancet Respir Med 2014; 2:321-38.
3. Gumbo T, Louie A, Deziel MR, Parsons LM, Salfinger M, Drusano GL. Selection of a moxifloxacin dose that suppresses drug resistance in Mycobacterium tuberculosis, by use of an in vitro pharmacodynamic infection model and mathematical modeling. J Infect Dis 2004; 190: 1642-51.
4. Gumbo T, Lenaerts AJ, Hanna D, Romero K, Nuermberger E. Nonclinical models for antituberculosis drug development: a landscape analysis. J Infect Dis 2015; 211(suppl 3):S83-95.
5. Srivastava S, Gumbo T. In vitro and in vivo modeling of tuberculosis drugs and its impact on optimization of doses and regimens. Curr Pharm Des 2011; 17:2881-8.
6. Gumbo T, Angulo-Barturen I, Ferrer-Bazaga S. Pharmacokinetic-pharmacodynamic and dose-response relationships of antituberculosis drugs: recommendations and standards for industry and academia. J Infect Dis 2015; 211(suppl 3):S96-106.
7. Metropolis N, Ulam S. The Monte Carlo method. J Am Stat Assoc 1949; 44:335-41.
8. Metropolis N. The beginning of the Monte Carlo method. Los Alamos Science 1987. Available at: library.lanl.gov/cgi-bin/getfile?00326866.pdf. Accessed 10 June 2015.
9. Pasipanodya J, Gumbo T. An oracle: antituberculosis pharmacokinetics-pharmacodynamics, clinical correlation, and clinical trial simulations to predict the future. Antimicrob Agents Chemother 2011; 55:24-34.
10. Gumbo T, Louie A, Liu W, et al. Isoniazid bactericidal activity and resistance emergence: integrating pharmacodynamics and pharmacogenomics to predict efficacy in different ethnic populations. Antimicrob Agents Chemother 2007; 51:2329-36.
11. Gumbo T, Siyambalapitiyage Dona CS, Meek C, Leff R. Pharmacokinetics-pharmacodynamics of pyrazinamide in a novel in vitro model of tuberculosis for sterilizing effect: a paradigm for faster assessment of new antituberculosis drugs. Antimicrob Agents Chemother 2009; 53:3197-204.
12. Drusano GL, Sgambati N, Eichas A, Brown DL, Kulawy R, Louie A. The combination of rifampin plus moxifloxacin is synergistic for suppression of resistance but antagonistic for cell kill of Mycobacterium tuberculosis as determined in a hollow-fiber infection model. MBio 2010; 1: e00139-10.
13. Gumbo T, Louie A, Deziel MR, Drusano GL. Pharmacodynamic evidence that ciprofloxacin failure against tuberculosis is not due to poor microbial kill but to rapid emergence of resistance. Antimicrob Agents Chemother 2005; 49:3178-81.
14. Gumbo T, Louie A, Deziel MR, et al. Concentration-dependent Mycobacterium tuberculosis killing and prevention of resistance by rifampin. Antimicrob Agents Chemother 2007; 51:3781-8.
15. Gumbo T, Louie A, Liu W, et al. Isoniazid's bactericidal activity ceases because of the emergence of resistance, not depletion of Mycobacterium tuberculosis in the log phase of growth. J Infect Dis 2007; 195:194-201.
16. Musuka S, Srivastava S, Siyambalapitiyage Dona CW, et al. Thioridazine pharmacokinetic-pharmacodynamic parameters "wobble" during treatment of tuberculosis: a theoretical basis for shorter-duration curative monotherapy with congeners. Antimicrob Agents Chemother 2013; 57:5870-7.
17. Gumbo T. New susceptibility breakpoints for first-line antituberculosis drugs based on antimicrobial pharmacokinetic/pharmacodynamic science and population pharmacokinetic variability. Antimicrob Agents Chemother 2010; 54:1484-91.
18. Jeena PM, Bishai WR, Pasipanodya JG, Gumbo T. In silico children and the glass mouse model: clinical trial simulations to identify and individualize optimal isoniazid doses in children with tuberculosis. Antimicrob Agents Chemother 2011; 55:539-45.
19. Srivastava S, Sherman C, Meek C, Leff R, Gumbo T. Pharmacokinetic mismatch does not lead to emergence of isoniazid- or rifampin-resistant Mycobacterium tuberculosis but to better antimicrobial effect: a new paradigm for antituberculosis drug scheduling. Antimicrob Agents Chemother 2011; 55:5085-9.
20. Srivastava S, Sherman C, Meek C, Leff R, Gumbo T. Hollow fiber model to study bactericidal and sterilizing effect of multiple drugs within two months: implications for design of new clinical regimens. In: 52nd Interscience Conference of Antimicrobial Agents and Chemotherapy (ICAAC), San Francisco, CA, 9-12 September 2012.
21. Srivastava S, Musuka S, Sherman C, Meek C, Leff R, Gumbo T. Effluxpump-derived multiple drug resistance to ethambutol monotherapy in Mycobacterium tuberculosis and the pharmacokinetics and pharmacodynamics of ethambutol. J Infect Dis 2010; 201:1225-31.
22. Drusano GL, Sgambati N, Eichas A, Brown D, Kulawy R, Louie A. Effect of administration of moxifloxacin plus rifampin against Mycobacterium tuberculosis for 7 of 7 days versus 5 of 7 days in an in vitro pharmacodynamic system. MBio 2011; 2:e00108-11.
23. Louie A, Brown D, Swift M, Files K, Fikes S, Drusano GL. Clinical doses of PNU-100480 (U, sutezolid) plus rifampin (R) synergistically kills Mycobacterium tuberculosis (Mtb) while linezolid (L) plus R does not. In: 52nd Interscience Conference of Antimicrobial Agents and Chemotherapy (ICAAC), San Francisco, CA, 9-12 September 2012.
24. Okusanya OO, Forrest A, Bulik CC, et al. Analyses for rifampin (RIF) in combination with sutezolid (SUT) or linezolid (LZD) against Mycobacterium tuberculosis (Mtb) in log-phase (LP) using data from a hollow fiber infection model. In: 52nd Interscience Conference of Antimicrobial Agents and Chemotherapy (ICAAC), San Francisco, CA, 9-12 September 2012.
25. Okusanya OO, Forrest A, Bulik CC. PK/PD analyses of the effects of sutezolid (SUT), linezolid (LZD), and rifampin (RIF), alone and in combination, against Mycobacterium tuberculosis (Mtb) in acid-phase (AP) growth using data from a hollow fiber infection model (HFIM). In: 52nd Interscience Conference of Antimicrobial Agents and Chemotherapy (ICAAC), San Francisco, CA, 9-12 September 2012.
26. Goutelle S, Bourguignon L, Maire PH, Van GM, Conte JE Jr, Jelliffe RW. Population modeling and Monte Carlo simulation study of the pharmacokinetics and antituberculosis pharmacodynamics of rifampin in lungs. Antimicrob Agents Chemother 2009; 53:2974-81.
27. Goutelle S, Bourguignon L, Jelliffe RW, Conte JE Jr, Maire P. Mathematical modeling of pulmonary tuberculosis therapy: insights from a prototype model with rifampin. J Theor Biol 2011; 282:80-92.
28. Xue B, Okusanya OO, Zhu T, et al. Pharmacokinetic-pharmacodynamic (PK-PD) analysis evaluating the effects of rifampin (RIF), PNU-100480 (sutezolid, U-480), and its metabolite PNU-101603 (U-603), alone and in combination, against Mycobacterium tuberculosis (Mtb) in the nonreplicating persister (NRP) state using data from a hollow-fiber infection model (HFIM). In: 52nd Interscience Conference of Antimicrobial Agents and Chemotherapy (ICAAC), San Francisco, CA, 9-12 September 2012.
29. Srivastava S, Pasipanodya JG, Meek C, Leff R, Gumbo T. Multidrug-resistant tuberculosis not due to noncompliance but to between-patient pharmacokinetic variability. J Infect Dis 2011; 204:1951-9.
30. Schmalstieg AM, Srivastava S, Belkaya S, et al. The antibiotic resistance arrow of time: efflux pump induction is a general first step in the evolution of mycobacterial drug resistance. Antimicrob Agents Chemother 2012; 56:4806-15.
31. Louie A, Brown D, Swift M, Files K, Fikes S, Drusano GL. Pharmacodynamics Of PNU-100480 (U, sutezolid), a new oxazolidinone, in combination with its active metabolite in the killing of Mycobacterium tuberculosis (Mtb) in an in vitro hollow fiber infection model (HFIM). In: 52nd Interscience Conference of Antimicrobial Agents and Chemotherapy (ICAAC), San Francisco, CA, 9-12 September 2012.
32. Louie A, Brown D, Swift M, Files K, Fikes S, Drusano GL. Activities of PNU 100480 (PNU 480) alone, PNU 480 plus its major metabolite PNU 101603 (PNU 1603), and PNU 480 plus PNU 1603 in combination with rifampin (RIF) against Mycobacterium tuberculosis (Mtb). In: 52nd Interscience Conference of Antimicrobial Agents and Chemotherapy (ICAAC), San Francisco, CA, 9-12 September 2012.
33. Drusano GL, Sgambati N, Eichas A, Brown D, Kulawy R, Louie A. Exposure-response of Mycobacterium tuberculosis (Mtb) in the State of Wayne-Hayes level II anaerobiosis to moxifloxacin (M). In: 52nd Interscience Conference of Antimicrobial Agents and Chemotherapy (ICAAC), San Francisco, CA, 9-12 September 2012.
34. Drusano GL, Sgambati N, Eichas A, Brown D, Kulawy R, Louie A. Prediction of clinical outcome from hollow fiber infection model (HFIM) data for rifampin (RIF) therapy of M. tuberculosis (Mtb) in non-replicative persister (NRP) phase. In: 52nd Interscience Conference of Antimicrobial Agents and Chemotherapy (ICAAC), San Francisco, CA, 9-12 September 2012.
35. Ginsburg AS, Lee J, Woolwine SC, Grosset JH, Hamzeh FM, Bishai WR. Modeling in vivo pharmacokinetics and pharmacodynamics of moxifloxacin therapy for Mycobacterium tuberculosis infection by using a novel cartridge system. Antimicrob Agents Chemother 2005; 49:853-6.
36. Srivastava S, Sherman C, Gumbo T. Bactericidal and sterilizing activities of anti-tuberculosis drugs during the first 28 days: a prequel [abstract A-1569]. In: 52nd Interscience Conference of Antimicrobial Agents and Chemotherapy (ICAAC), San Francisco, CA, 9-12 September 2012.
37. Drusano GL, Louie A, Deziel M, Gumbo T. The crisis of resistance: identifying drug exposures to suppress amplification of resistant mutant subpopulations. Clin Infect Dis 2006; 42:525-32.
38. Stass H, Dalhoff A, Kubitza D, Schühly U. Pharmacokinetics, safety, and tolerability of ascending single doses of moxifloxacin, a new 8-methoxy quinolone, administered to healthy subjects. Antimicrob Agents Chemother 1998; 42:2060-5.
39. Sorger PK, Allerheiligen SRB, Abernethy DR, et al. Quantitative and systems pharmacology in the post-genomic era: new approaches to discovering drugs and understanding therapeutic mechanisms. In: QSP Workshop Group. National Institute of General Medical Sciences, 2011. Available at: http://www.nigms.nih.gov/training/documents/systemspharmawpsorger2011.pdf. Accessed 10 June 2015.
40. National Science Foundation Blue Ribbon Panel on Simulation-Based Engineering. Simulation-based engineering science. Revolutionizing engineering science through simulation. National Science Foundation, 2006. Available at: http://www.nsf.gov/pubs/reports/sbes-final-report.pdf. Accessed 10 June 2015.
41. Pasipanodya JG, Gumbo T. A new evolutionary and pharmacokinetic-pharmacodynamic scenario for rapid emergence of resistance to single and multiple anti-tuberculosis drugs. Curr Opin Pharmacol 2011; 11:457-63.
42. Gumbo T. Biological variability and the emergence of multidrug-resistant tuberculosis. Nat Genet 2013; 45:720-1.
43. Diacon AH, Maritz JS, Venter A, van Helden PD, Dawson R, Donald PR. Time to liquid culture positivity can substitute for colony counting on agar plates in early bactericidal activity studies of antituberculosis agents. Clin Microbiol Infect 2012; 18:711-7.
44. Chigutsa E, Patel K, Denti P, et al. A time-to-event pharmacodynamic model describing treatment response in patients with pulmonary tuberculosis using days to positivity in automated liquid mycobacterial culture. Antimicrob Agents Chemother 2013; 57:789-95.
45. Chigutsa E, Pasipanodya JG, Visser ME, et al. Impact of nonlinear interactions of pharmacokinetics and MICs on sputum bacillary kill rates as a marker of sterilizing effect in tuberculosis. Antimicrob Agents Chemother 2015; 59:38-45.
46. Pasipanodya JG, McIlleron H, Burger A, Wash PA, Smith P, Gumbo T. Serum drug concentrations predictive of pulmonary tuberculosis outcomes. J Infect Dis 2013; 208:1464-73.
47. Gumbo T, Pasipanodya JG, Romero K, Hanna D, Nuermberger E. Forecasting accuracy of the hollow fiber model of tuberculosis for clinical therapeutic outcomes. Clin Infect Dis 2015; 61(suppl 1):S25-31.