BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

143 related articles for article (PubMed ID: 15518244)

  • 1. Fuzzy simulation of pharmacokinetic models: case study of whole body physiologically based model of diazepam.
    Gueorguieva II; Nestorov IA; Rowland M
    J Pharmacokinet Pharmacodyn; 2004 Jun; 31(3):185-213. PubMed ID: 15518244
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Incorporating measures of variability and uncertainty into the prediction of in vivo hepatic clearance from in vitro data.
    Nestorov I; Gueorguieva I; Jones HM; Houston B; Rowland M
    Drug Metab Dispos; 2002 Mar; 30(3):276-82. PubMed ID: 11854145
    [TBL] [Abstract][Full Text] [Related]  

  • 3. A fuzzy physiologically based pharmacokinetic modeling framework to predict drug disposition in humans.
    Seng KY; Vicini P; Nestorov IA
    Conf Proc IEEE Eng Med Biol Soc; 2006; 2006():5037-40. PubMed ID: 17947127
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Physiologically based pharmacokinetic modeling of drug disposition in rat and human: a fuzzy arithmetic approach.
    Seng KY; Nestorov I; Vicini P
    Pharm Res; 2008 Aug; 25(8):1771-81. PubMed ID: 18363078
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Diazepam pharamacokinetics from preclinical to phase I using a Bayesian population physiologically based pharmacokinetic model with informative prior distributions in WinBUGS.
    Gueorguieva I; Aarons L; Rowland M
    J Pharmacokinet Pharmacodyn; 2006 Oct; 33(5):571-94. PubMed ID: 16810558
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Simulating pharmacokinetic and pharmacodynamic fuzzy-parameterized models: a comparison of numerical methods.
    Seng KY; Nestorov I; Vicini P
    J Pharmacokinet Pharmacodyn; 2007 Oct; 34(5):595-621. PubMed ID: 17710517
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A fuzzy physiologically based pharmacokinetic modeling framework to predict drug disposition in humans.
    Seng KY; Vicini P; Nestorov IA
    Conf Proc IEEE Eng Med Biol Soc; 2006; Suppl():6485-8. PubMed ID: 17959432
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Linking preclinical and clinical whole-body physiologically based pharmacokinetic models with prior distributions in NONMEM.
    Langdon G; Gueorguieva I; Aarons L; Karlsson M
    Eur J Clin Pharmacol; 2007 May; 63(5):485-98. PubMed ID: 17345074
    [TBL] [Abstract][Full Text] [Related]  

  • 9. The Constraints, Construction, and Verification of a Strain-Specific Physiologically Based Pharmacokinetic Rat Model.
    Musther H; Harwood MD; Yang J; Turner DB; Rostami-Hodjegan A; Jamei M
    J Pharm Sci; 2017 Sep; 106(9):2826-2838. PubMed ID: 28495566
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Comprehensive Eutrophication Assessment Based on Fuzzy Matter Element Model and Monte Carlo-Triangular Fuzzy Numbers Approach.
    Wang Y; Ran W
    Int J Environ Res Public Health; 2019 May; 16(10):. PubMed ID: 31109129
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Comparison of Monte Carlo and fuzzy math simulation methods for quantitative microbial risk assessment.
    Davidson VJ; Ryks J
    J Food Prot; 2003 Oct; 66(10):1900-10. PubMed ID: 14572230
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Reducing whole body physiologically based pharmacokinetic models using global sensitivity analysis: diazepam case study.
    Gueorguieva I; Nestorov IA; Rowland M
    J Pharmacokinet Pharmacodyn; 2006 Feb; 33(1):1-27. PubMed ID: 16369700
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Modelling and simulation of variability and uncertainty in toxicokinetics and pharmacokinetics.
    Nestorov I
    Toxicol Lett; 2001 Mar; 120(1-3):411-20. PubMed ID: 11323201
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A combined Monte Carlo and possibilistic approach to uncertainty propagation in event tree analysis.
    Baraldi P; Zio E
    Risk Anal; 2008 Oct; 28(5):1309-26. PubMed ID: 18631304
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Integrating fuzzy logic with Pearson correlation to optimize contaminant detection in water distribution system with uncertainty analyses.
    Osmani SA; Banik BK; Ali H
    Environ Monit Assess; 2019 Jun; 191(7):441. PubMed ID: 31203453
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Modeling biological systems with uncertain kinetic data using fuzzy continuous Petri nets.
    Liu F; Chen S; Heiner M; Song H
    BMC Syst Biol; 2018 Apr; 12(Suppl 4):42. PubMed ID: 29745860
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Fuzzy Stochastic Petri Nets for Modeling Biological Systems with Uncertain Kinetic Parameters.
    Liu F; Heiner M; Yang M
    PLoS One; 2016; 11(2):e0149674. PubMed ID: 26910830
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Different methodologies to quantify uncertainties of air emissions.
    Romano D; Bernetti A; De Lauretis R
    Environ Int; 2004 Oct; 30(8):1099-107. PubMed ID: 15337355
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Analysis and prediction of flow from local source in a river basin using a Neuro-fuzzy modeling tool.
    Aqil M; Kita I; Yano A; Nishiyama S
    J Environ Manage; 2007 Oct; 85(1):215-23. PubMed ID: 17110016
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Fuzzy least squares for identification of individual pharmacokinetic parameters.
    Seng KY; Nestorov I; Vicini P
    IEEE Trans Biomed Eng; 2009 Dec; 56(12):2796-805. PubMed ID: 19695981
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.