Population Modeling and Monte Carlo Simulation Study of the Pharmacokinetics and Antituberculosis Pharmacodynamics of Rifampin in Lungs

被引:88
|
作者
Goutelle, Sylvain [1 ,2 ]
Bourguignon, Laurent [1 ,2 ]
Maire, Pascal H. [1 ,2 ]
Van Guilder, Michael [3 ]
Conte, John E., Jr. [4 ,5 ]
Jelliffe, Roger W. [3 ]
机构
[1] Hop Antoine Charial, Hosp Civils Lyon, Serv Pharmaceut, ADCAPT, F-69340 Franceville, France
[2] Univ Lyon 1, CNRS, UMR 5558, F-69622 Villeurbanne, France
[3] Univ Calif Los Angeles, Sch Med, Lab Appl Pharmacokinet, Los Angeles, CA USA
[4] Univ Calif San Francisco, Infect Dis Res Grp, Dept Epidemiol & Biostat, San Francisco, CA 94143 USA
[5] Amer Hlth Sci, San Francisco, CA USA
关键词
EPITHELIAL LINING FLUID; PULMONARY TUBERCULOSIS PATIENTS; PLASMA-CONCENTRATIONS; TARGET GOALS; DRUGS; AIDS; RIFAPENTINE; REGIMENS; DESCRIBE; THERAPY;
D O I
10.1128/AAC.01520-08
中图分类号
Q93 [微生物学];
学科分类号
071005 ; 100705 ;
摘要
Little information exists on the pulmonary pharmacology of antituberculosis drugs. We used population pharmacokinetic modeling and Monte Carlo simulation to describe and explore the pulmonary pharmacokinetics and pharmacodynamics of rifampin (RIF; rifampicin). A population pharmacokinetic model that adequately described the plasma, epithelial lining fluid (ELF), and alveolar cell (AC) concentrations of RIF in a population of 34 human volunteers was made by use of the nonparametric adaptive grid (NPAG) algorithm. The estimated concentrations correlated well with the measured concentrations, and there was little bias and good precision. The results obtained with the NPAG algorithm were then imported into Matlab software to perform a 10,000-subject Monte Carlo simulation. The ability of RIF to suppress the development of drug resistance and to induce a sufficient bactericidal effect against Mycobacterium tuberculosis was evaluated by calculating the proportion of subjects achieving specific target values for the maximum concentration of drug (C(max))/MIC ratio and the area under the concentration-time curve from time zero to 24 h (AUC(0-24))/MIC ratio, respectively. At the lowest MIC (0.01 mg/liter), after the administration of one 600-mg oral dose, the rates of target attainment for C(max)/MIC (>= 175) were 95% in ACs, 48.8% in plasma, and 35.9% in ELF. Under the same conditions, the target attainment results for the killing effect were 100% in plasma (AUC(0-24)/MIC >= 271) but only 54.5% in ELF (AUC(0-24)/MIC >= 665). The use of a 1,200-mg RIF dose was associated with better results for target attainment. The overall results suggest that the pulmonary concentrations obtained with the standard RIF dose are too low in most subjects. This work supports the need to evaluate higher doses of RIF for the treatment of patients with tuberculosis.
引用
收藏
页码:2974 / 2981
页数:8
相关论文
共 50 条
  • [1] Population Modeling and Simulation Study of the Pharmacokinetics and Antituberculosis Pharmacodynamics of Isoniazid in Lungs
    Lalande, L.
    Bourguignon, L.
    Bihari, S.
    Maire, P.
    Neely, M.
    Jelliffe, R.
    Goutelle, S.
    [J]. ANTIMICROBIAL AGENTS AND CHEMOTHERAPY, 2015, 59 (09) : 5181 - 5189
  • [2] Meropenem pharmacokinetics, pharmacodynamics, and Monte Carlo simulation in the neonate
    Bradley, John S.
    Sauberan, Jason B.
    Ambrose, Paul G.
    Bhavnani, Sitjata M.
    Rasmussen, Maynard R.
    Capparelli, Edmund V.
    [J]. PEDIATRIC INFECTIOUS DISEASE JOURNAL, 2008, 27 (09) : 794 - 799
  • [3] Optimal dose finding of garenoxacin based on population pharmacokinetics/pharmacodynamics and Monte Carlo simulation
    Tanigawara, Yusuke
    Nozawa, Kenji
    Tsuda, Hisatsugu
    [J]. EUROPEAN JOURNAL OF CLINICAL PHARMACOLOGY, 2012, 68 (01) : 39 - 53
  • [4] Optimal dose finding of garenoxacin based on population pharmacokinetics/pharmacodynamics and Monte Carlo simulation
    Yusuke Tanigawara
    Kenji Nozawa
    Hisatsugu Tsuda
    [J]. European Journal of Clinical Pharmacology, 2012, 68 : 39 - 53
  • [5] Pharmacokinetics, Pharmacodynamics, and Monte Carlo Simulation Selecting the Best Antimicrobial Dose to Treat an Infection
    Bradley, John S.
    Garonzik, Samira Merali
    Forrest, Alan
    Bhavnani, Sujata M.
    [J]. PEDIATRIC INFECTIOUS DISEASE JOURNAL, 2010, 29 (11) : 1043 - 1046
  • [6] Predicting efficacy of antiinfectives with pharmacodynamics and Monte Carlo simulation
    Bradley, JS
    Dudley, MN
    Drusano, GL
    [J]. PEDIATRIC INFECTIOUS DISEASE JOURNAL, 2003, 22 (11) : 982 - 992
  • [7] Media mix modeling – A Monte Carlo simulation study
    Liu Y.
    Laguna J.
    Wright M.
    He H.
    [J]. Journal of Marketing Analytics, 2014, 2 (3) : 173 - 186
  • [8] Pharmacokinetics/pharmacodynamics cut-off determination for fosfomycin using Monte Carlo simulation in healthy horses
    Kuroda, Taisuke
    Minamijima, Yohei
    Niwa, Hidekazu
    Mita, Hiroshi
    Tamura, Norihisa
    Fukuda, Kentaro
    Toutain, Pierre-Louis
    Ohta, Minoru
    [J]. JOURNAL OF VETERINARY MEDICAL SCIENCE, 2024, 86 (04): : 413 - 420
  • [9] Pharmacodynamics of ceftazidime and meropenem in cerebrospinal fluid:: results of population pharmacokinetic modelling and Monte Carlo simulation
    Lodise, T. P.
    Nau, R.
    Kinzig, M.
    Drusano, G. L.
    Jones, R. N.
    Soergel, F.
    [J]. JOURNAL OF ANTIMICROBIAL CHEMOTHERAPY, 2007, 60 (05) : 1038 - 1044
  • [10] Bone Penetration of Amoxicillin and Clavulanic Acid Evaluated by Population Pharmacokinetics and Monte Carlo Simulation
    Landersdorfer, Cornelia B.
    Kinzig, Martina
    Bulitta, Juergen B.
    Hennig, Friedrich F.
    Holzgrabe, Ulrike
    Soergel, Fritz
    Gusinde, Johannes
    [J]. ANTIMICROBIAL AGENTS AND CHEMOTHERAPY, 2009, 53 (06) : 2569 - 2578