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PKfit - A Pharmacokinetic Data Analysis Tool in R Speaker: Chun-ying Lee 1 Advisor: Yung-jin Lee 2 1 Pharmacy Department, Changhua Christian Hospital Changhua, Taiwan 2 College of Pharmacy, Kaohsiung Medical University, Kaohsiung, Taiwan

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2015/5/4 2 Motivation Using available packages in R to create the program Selecting menu-driven mode as the user interface Studying the application of genetic algorithm to PK data analysis Comparing with WinNonlin and Boomer WinNonlin http://www.pharsight.comhttp://www.pharsight.com Boomer http://www.boomer.orghttp://www.boomer.org

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2015/5/4 3 User Interface Menu-driven mode Users need not require to be familiar with programming of R Analyses data step by step

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2015/5/4 4 PK models included Fourteen PK models are currently available (all single-dosed) Intravenous drug administrations with i.v. bolus or i.v. infusion Extravascular drug administrations, linear PK with 1 st -order absorption/elimination or with nonlinear (Michaelis-Menten) elimination models

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Model fitting

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2015/5/4 6 Packages required odesolve (by R. Woodrow Setzer) lsoda function: solving differential equations rgenoud (by Walter R. Mebane and Jasjeet S. Sekhon ) genoud function: Genetic algorithm stats nls function: Gauss-Newton algorithm (by Douglas M. Bates and Saikat DebRoy) optim function: Nelder-Mead simplex method logLik function: Log-Likelihood (by Jose Pinheiro and Douglas Bates) AIC function: Akaike’s Information Criterion (by Jose Pinheiro and Douglas Bates) stats4 BIC function: Bayesian information criterion

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2015/5/4 7 Coding process

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2015/5/4 8 Output information Summary table Time, observed and calculated concentrations Weighted residuals Area under plasma concentration curves (AUC) Area under the first moment curves (AUMC) Final values of PK parameters Model selection criteria Log-Likelihood (LL) Akaike’s Information Criterion (AIC) Schwarz’s Bayesian Criterion (SBC) Diagnostic plots Linear plots Semi-log plots Residual plots

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2015/5/4 9 Validation All the conditions are set the same in these three software Data sets Selected models Initial values for parameters Fitting algorithms and numerical integration tools WinNonlin: Nelder-Mead Simplex method / RKF5 Boomer: Nelder-Mead Simplex Gauss-Newton / RKF5 Criteria Prediction (absolute) error (PE) Percentage of prediction (absolute) error (%PE)

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2015/5/4 10 Comparison of software WinNonlinBoomerPKfit equal1/Cp1/Cp 2 equal1/Cp1/Cp 2 equal1/Cp1/Cp 2 Model 1 Model 2 Model 3 Model 4 Model 1: One-Compartment PK Model I.V. Bolus Single-Dose with Linear Elimination Model 2: One-Compartment PK Model I.V. Bolus Single-Dose with Nonlinear Elimination Model 3: One-Compartment PK Model I.V. Infusion Single-Dose with Linear Elimination Model 4: One-Compartment PK Model I.V. Infusion Single-Dose with Nonlinear Elimination : Running O.K. (AE% 5%)

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2015/5/4 11 Comparison of software WinNonlinBoomerPKfit equal1/Cp1/Cp 2 equal1/Cp1/Cp 2 equal1/Cp1/Cp 2 Model 5 Model 6 X Model 7 X Model 8 XX Model 5: One-Compartment PK Model Extravascular Single-Dose with First-Ordered Absorption and Linear Elimination without Lag Time Model 6: One-Compartment PK Model Extravascular Single-Dose with First-Ordered Absorption and Nonlinear Elimination without Lag Time Model 7: One-Compartment PK Model Extravascular Single-Dose with Zero-Ordered Absorption and Linear Elimination without Lag Time Model 8: One-Compartment PK Model Extravascular Single-Dose with Zero-Ordered Absorption and Nonlinear Elimination without Lag Time : Running O.K. (AE% 5%) X: Not acceptable for final PK parameters (AE% > 5%)

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2015/5/4 12 Comparison of software WinNonlinBoomerPKfit equal1/Cp1/Cp 2 equal1/Cp1/Cp 2 equal1/Cp1/Cp 2 Model 9 Model 10 Model 11 X Model 9: Two-Compartment PK Model I.V. Bolus Single-Dose with Linear Elimination Model 10: Two-Compartment PK Model I.V. Infusion Single-Dose with Linear Elimination Model 11: Two-Compartment PK Model Extravascular Single-Dose with First-Ordered Absorption and Linear Elimination without Lag Time : Running O.K. (AE% 5%) X: Not acceptable for final PK parameters (AE% > 5%)

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2015/5/4 13 Comparison of software WinNonlinBoomerPKfit equal1/Cp1/Cp 2 equal1/Cp1/Cp 2 equal1/Cp1/Cp 2 Model 12 Model 13 Model 14XXX X Model 12: One-Exponential Term Model 13: Two-Exponential Term Model 14: Three-Exponential Term : Running O.K. (AE% 5%) X: Not acceptable for final PK parameters (AE% > 5%) X: Crashed

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Simulation

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2015/5/4 15 Packages required stats runif function: random uniform distribution derivates rnorm function: random normal distribution derivates

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2015/5/4 16 Coding process

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2015/5/4 17 Output information Time and concentration Linear plot Semi-log plot

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2015/5/4 18 Validation very similar All the simulation results in these three software are very similar with “Error type = No error” with four significant digits WinNonlinBoomerPKfit TimeConc. 0.512.39 122.29 236.15 344.14 448.08 648.64 844.33 1038.37 1232.27 1621.82 2014.34 24 9.314 A one-compartment PK model with extravascular, single-dose with first-ordered absorption without lag time and linear elimination Dose= 500 (mg) ka= 0.32 (1/hr) kel= 0.11 (1/hr) Vd= 5.8 (L)

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2015/5/4 19 Thanks to… Dr. Woodrow Setzer for odesolve Dr. Jasjeet Sekhon for rgenoud Dr. Anthony Rossini for scripting

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2015/5/4 20 Reference R Installation and Administration, Version 2.0.1, 2001. (http://cran.r-project.org/doc/manuals/R-admin.html) R Language Definition, Version 1.9.1, 2004. (http://cran.r-project.org/doc/manuals/R-lang.html) Sekhon, J.S. and Mebane, W.R.Jr., Genetic Optimization Using Derivatives: Theory and Application to Nonlinear Models. Political Analysis, 7:187-210, 1998. Setzer, R.W., The odeslove Package, 2004. The R Project for Statistical Computing. (http://www.r-project.org) Writing R Extensions, Version 1.9.1, 2004. (http://cran.r-project.org/doc/manuals/R-exts.html)

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Thanks for your attention!

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