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1 2014 25 37 China 010-67096862 E-mail 010-67098036 E-mail / Phar-macokinetic/Pharmacodynamic PK/PD [1] NONMEM Phoenix S-ADAPT PDx-MC-PEM MONO-LIX WinBUGS CAPP PK/PD S2 3 PK PD PK/PD PK/PD 3 PD PK/PD PK/PD PK/PD 1 Science Citation Index SCI Webof Science PK/PD software program procedure 1986

2 2013 11 29 321 PK/PD 9 [1-9] [10] PK/PD 2 PK/PD Nonlinear mixed-effect model NONMEM 1977 Dr. Sheiner Fortran NONMEM PK/PD First-order estimation FO First-order conditional estimation FOCE LAPLAS-CIAN Microsoft Windows UNIX Windows NONMEM DOS Fortran NONMEM Windows NONMEM NONMEM ICON NONMEM Control file Data file NM-TRAN NONMEMPRED PREDPP NONMEM output files 1 1

3 NONMEM NONMEM PDx-Pop Pirana PsN WFN ESN Excel S-plus ICON NONMEM http http / 1 2 2 2 1# 1. 100050 2. 100038 R9-39 TP31 A 1001-0408 2014 / PK/PD Web of Science PK/PD software program procedure 1986 2013 11 29 PK/PD PK/PD 321 9 PK/PD NONMEN Phoenix S-ADAPT PDx-MC-PEM MONOLIX WinBUGS NONMEN PK/PD Phoenix PK PK/PD S-ADAPT NONMEN PDx-MC-PEM MONOLIX WinBUGS

4 Phoenix NONMEN S-ADAPT / 1 NONMEM NONMEN PREDPPNONMEM PDx-Pop Pirana PsN WFN ESN 3541 China 2014 25 37 com/Public/nonmem http http NONMEM Pharsight WinNonLin NLME Nonlinear mixed effects PK PK/PD [11] Windows PK PD Phoenix Phoenix Noncompartment analysis NCA PK PK/PD PK http Fortran95

5 MCPEM Stochastic approximation expectation maximization SAEM Raptiva 6 16 Intel Windows98 Intel Visual Fortran compilerCompaq Visual Fortran compiler g95 Windows Intel Visual Fortran compiler ADAPTII PK/PD S-ADAPT S-ADAPT http Serge Guzy ICON Monte-Carlo parametric expectation maximization MCPEM PDx-POP NONMEM PK PD PK/PD Fortran Inter Fortran Com-paq Fortran Gfortran 3 OFV http Mentre INSERM andUniversity Paris MarcLavielle University Rene Descartesand University Pairs-Sud MONOLIX MOd les NOnLIn aires effets miXtes - SAEM PK/PD

6 1 5 200 300 PK/PD MONOLIX Matlab PK/PD Matlab MONO-LIX PK/PD http Bayesian Inference Using Gibbs Sampling - Mar-kov chain Monte Carlo MCMC MCMC MCMC Fortran BUGS MCMC WinBUGS BUGS Windows WinBUGS [2-3] PK/PD [4-6] PKBUGS WinBUGS 1 2 3 PK PKBUGS Black-Box Pascal Pascal WinBUGS BlackBox http PK/PD ADAPTII NPML NLINMIX MIXNLIN PPHARM PK/PD [7]

7 PK PK Tornoe CW [8] NLME ODE nlmeODE PK NONMEM Galecki AT[9] NLIN-MIX NLMEM 3 NONMEM - PK/PD 3542 2014 25 37 China FO / FOCE FO / FOCE LAPLASCIAN FO FOCE LAPLACE Fortran

8 Phoenix PK PK PK/PD PML PML NLME NONMEM S-ADAPT PK/PD NONMEM PDx-MC-PEM MCPEM MONOLIX MONOLIX Matlab Matlab WinBUGS PK/PD WinBUGS

9 For-tran Pascal PK/PD awk Wings for NONMEM WFN R Xpose Rfor NONMEM NPDE PLT-Tools perl Perl-speaks-NONMEM PsN Census Pirana XML NLMEc ICON NONMEM PDX-Pop PK/PD 4 PK/PD PK/PD Phoenix NONMEM S-ADAPT [1]Bauer RJ Guzy S Ng C. A survey of population analysismethods and software for complex pharmacokinetic andpharmacodynamic models with examples[J].

10 AAPS J 2007 9 1 E60.[2]Best NG Tan KK Gilks WR et al. Estimation of popu-lation pharmacokinetics using the Gibbs sampler[J].JPharmacokinet Biopharm 1995 23 4 407.[3]Lunn DJ Best N Thomas A et al. Bayesian analysis ofpopulation PK/PD models g