# Script generated by the UniPV WinBUGS converter
# 'WinBUGSConverter' copyright (c) BMS - University of Pavia (2016)
# Converter Version: 1.0.0
# Source: PharmML 0.8.1
# Target: WINBUGS 1.4.3
# Run ID: run_id_0
# Model: Generated from MDL. MOG ID: warfarin_PK_ODE_mog
# File: UseCase5Prova4
# Dated: Mon Aug 01 11:29:11 CEST 2016

model {
  for (ind_subj in 1:N_subj) {
    for (ind_t in 1:N_t[ind_subj]) {
      Y_mean[ind_subj,ind_t] <- (CC[ind_subj,ind_t] + 0)
      Y_prec[ind_subj,ind_t] <- 1 / ((pow(((RUV_ADD + (RUV_PROP * CC[ind_subj,ind_t]))),2))*1)
      Y[ind_subj,ind_t] ~ dnorm(Y_mean[ind_subj,ind_t], Y_prec[ind_subj,ind_t])
      Y_res[ind_subj,ind_t] <- Y[ind_subj,ind_t]-Y_mean[ind_subj,ind_t]
    }
    ETA_KA[ind_subj] ~ dnorm(0, ETA_KA_prec)
    ETA_TLAG[ind_subj] ~ dnorm(0, ETA_TLAG_prec)
    log(CL[ind_subj]) <- log(POP_CL) + ETA_CL[ind_subj]
    log(V[ind_subj]) <- log(POP_V) + ETA_V[ind_subj]
    log(KA[ind_subj])<- log(POP_KA) + ETA_KA[ind_subj]
    log(TLAG[ind_subj])<- log(POP_TLAG) + ETA_TLAG[ind_subj]
    ETA1[ind_subj,1:2] ~ dmnorm(mu1[], T1[,])
    ETA_CL[ind_subj] <- ETA1[ind_subj,1]
    ETA_V[ind_subj] <- ETA1[ind_subj,2]
    der99wb_unipv[ind_subj,1:N_t[ind_subj], 1:2]<- function.model1(grid[ind_subj,1:N_t[ind_subj]], amt[ind_subj,1:N_t[ind_subj]],  rate[ind_subj,1:N_t[ind_subj]], ii[ind_subj,1:N_t[ind_subj]], evid[ind_subj,1:N_t[ind_subj]], cmt[ind_subj,1:N_t[ind_subj]], addl[ind_subj,1:N_t[ind_subj]], ss[ind_subj,1:N_t[ind_subj]], theta[ind_subj,])
    theta[ind_subj,1] <- ETA_KA[ind_subj]
    theta[ind_subj,2] <- POP_KA
    theta[ind_subj,3] <- ETA_CL[ind_subj]
    theta[ind_subj,4] <- POP_CL
    theta[ind_subj,5] <- ETA_V[ind_subj]
    theta[ind_subj,6] <- POP_V
    theta[ind_subj,7] <- 0.0 #IC Ad1
    theta[ind_subj,8] <- 0.0 #IC CENTRAL
    theta[ind_subj,9] <- 1 #F Ad1
    theta[ind_subj,10] <- 1 #F CENTRAL
    theta[ind_subj,11] <- TLAG[ind_subj] #TLAG Ad1
    theta[ind_subj,12] <- 0 #TLAG CENTRAL
    for (ind_q in 1:N_t[ind_subj]) {
      Ad1[ind_subj,ind_q] <- der99wb_unipv[ind_subj,ind_q,1] + 0.0
      CENTRAL[ind_subj,ind_q] <- der99wb_unipv[ind_subj,ind_q,2] + 0.0
      CC[ind_subj,ind_q] <- (CENTRAL[ind_subj,ind_q] / V[ind_subj])
    }
  }
  ETA_KA_prec <- (1/(pow(PPV_KA,2)))
  ETA_TLAG_prec <- (1/(pow(PPV_TLAG,2)))
  T1[1:2,1:2] <- inverse(OMEGA1[,])
  mu1[1] <- 0.0
  mu1[2] <- 0.0
  OMEGA1[1,1] <- pow(PPV_CL,2)
  OMEGA1[1,2] <- CORR_CL_V*PPV_CL*PPV_V
  OMEGA1[2,1] <- CORR_CL_V*PPV_CL*PPV_V
  OMEGA1[2,2] <- pow(PPV_V,2)
  MU_CL <- (log(0.1))
  MU_V <- (log(8))
  MU_KA <- (log(0.362))
  MU_TLAG <- (log(1))
  MU_PPV_CL <- (log(0.1))
  MU_PPV_V <- (log(0.1))
  MU_PPV_KA <- (log(0.1))
  MU_FORAL <- (log(0.7))
  MU_PPV_FORAL <- (log(0.1))
  MU_CORR_CL_V <- (log(0.01))
  MU_BETA_CL_AGE <- (log(0.001))
  MU_POP_FCL_FEM <- (log(1))
  MU_RUV_PROP <- (log(0.1))
  MU_RUV_ADD <- (log(0.1))
  VAR_CL <- pow((log(pow(0.1,2))),2)
  VAR_V <- pow((log(pow(8,2))),2)
  VAR_KA <- pow((log(pow(0.362,2))),2)
  VAR_TLAG <- pow((log(pow(1,2))),2)
  VAR_PPV_CL <- pow((log(pow(0.1,2))),2)
  VAR_PPV_V <- pow((log(pow(0.1,2))),2)
  VAR_PPV_KA <- pow((log(pow(0.1,2))),2)
  VAR_FORAL <- pow((log(pow(0.7,2))),2)
  VAR_PPV_FORAL <- pow((log(pow(0.1,2))),2)
  VAR_CORR_CL_V <- pow((log(pow(0.01,2))),2)
  VAR_BETA_CL_AGE <- pow((log(pow(0.001,2))),2)
  VAR_POP_FCL_FEM <- pow((log(pow(1,2))),2)
  VAR_RUV_PROP <- pow((log(pow(0.1,2))),2)
  VAR_RUV_ADD <- pow((log(pow(0.1,2))),2)
  BETA_CL_WT <- 0.75
  BETA_V_WT <- 1
  PPV_TLAG <- 0.1
  POP_CL <- 0.1
  POP_V <- 8
  POP_KA <- 0.36
  POP_TLAG <- 1
  PPV_CL <- 0.1
  PPV_V <- 0.14
  PPV_KA <- 0.94
  CORR_CL_V <- 0.29
  RUV_PROP <- 0.11
  RUV_ADD <- 0.001
  BETA_CL_AGE <- 0.001
  POP_FCL_FEM <- 1
  POP_FORAL <- 0.1
  # PRIORS
}
