1. Популяционное моделирование

2. Постановка задачи Наблюдаемые данные и ковариаты -> оценка β, b, σ,Ψ Значения параметров -> предсказание

3. nlme library for R Pinheiro J.C., Bates D.M. Mixed-Effect Models in S and S-PLUS, 2000. nlmeODE Tornoe C.W., Agerso H., Jonson E.N., Madse H., Nielsen H.A. Non-linear mixed-effects pharmacokinetic/pharmacodynamic modelling in NLME using differential equations. 2004.

4. nlmeODE Data retreiving PK model nlmeODE structural function nlme call

5. Population modeling NLME diagram R script Code generation Estimation results nlme Java classes rJava Structural diagram: - ODE - PDE - composite - agent … Structural diagram: - ODE - PDE - composite - agent … Tabled data (dosing, group factors) Tabled data (dosing, group factors) PharmML SBML CellML … Import, export

6. Distribution visualization WinBUGSBioUML

7. Популяционное моделирование

11. Сравнение atol = 1E-12, rtol = 1E-8 BioUMLnlmeODE Duration (s)23.94108.84 Loglike-181.177-177.038 AIC374,354366,076 BIC391.6508383.3728 Fixed effectska = 0.468757 ke = -2.458947 CL = -3.228863 ka = 0.4672482 ke= -2.4557651 CL = -3.227748 Random effectska = 0.6343257 CL = 0.217 ka = 0.6433165 CL = 0.1665241 Residual0.71022040.709441

12. Спасибо за внимание