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PKfit is a user-friendly pharmacokinetic data analysis tool in R, utilizing genetic algorithms and various PK models for efficient analysis. It compares with WinNonlin and Boomer, providing model fitting and validation with detailed output information and model comparisons.
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PKfit - A Pharmacokinetic Data Analysis Tool in R Speaker: Chun-ying Lee1 Advisor: Yung-jin Lee2 1Pharmacy Department, Changhua Christian Hospital Changhua, Taiwan 2College of Pharmacy, Kaohsiung Medical University, Kaohsiung, Taiwan
Motivation • Using available packagesin R to create theprogram • Selecting menu-driven mode as the user interface • Studying the application ofgenetic algorithm to PK data analysis • Comparing with WinNonlin and Boomer • WinNonlin http://www.pharsight.com • Boomer http://www.boomer.org
User Interface • Menu-driven mode • Users need not require to be familiar with programming of R • Analyses data step by step
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 1st-order absorption/elimination or with nonlinear (Michaelis-Menten) elimination models
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
Coding process 7 2020/1/1
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
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)
Comparison of software 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%)
Comparison of software 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%)
Comparison of software 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%)
Comparison of software 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
Packages required • stats • runif function: random uniform distribution derivates • rnorm function: random normal distribution derivates
Coding process 16 2020/1/1
Output information • Time and concentration • Linear plot • Semi-log plot
Validation • All the simulation results in these three software are very similar with “Error type = No error” with four significant digits 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)
Thanks to… • Dr. Woodrow Setzer for odesolve • Dr. Jasjeet Sekhon for rgenoud • Dr. Anthony Rossini for scripting
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)