[LONGITUDINAL]  
  input={K, KDE, KPQ, KQPP, LAMBDAP, GAMMA, DELTAQP}
  
  PK:
  depot(target=C)
  
  EQUATION:
  PT_0=5
  Q_0 = 40
  PSTAR = PT+Q+QP
  ddt_C = -KDE*C
  ddt_PT = LAMBDAP*PT*(1-PSTAR/K) + KQPP*QP - KPQ*PT - GAMMA*KDE*PT*C
  ddt_Q = KPQ*PT - GAMMA*KDE*Q*C
  ddt_QP = GAMMA*KDE*Q*C - KQPP*QP - DELTAQP*QP  

#-----   Dosing regimen  ------------------------------
adm <- list(time=seq(0, 45, by= 9),  amount=1)


#-----   Parameter values  ----------------------------
psi <- list( name  = c('K','KDE','KPQ','KQPP','LAMBDAP','GAMMA','DELTAQP'),
             value = c(100, 0.3, 0.025, 0.004, 0.12, 1, 0.01))

#-----   Predicted tumor size  ------------------------
of  <- list(name='PSTAR', time=seq(-50,100,by=1))
res <- simulx(model="tgi_model.txt",parameter=psi,output=of,treatment=adm)


#-----  Plot the predicted tumor size --
plot1=ggplot() + geom_line(data=res$PSTAR, aes(x=time, y=PSTAR))
print(plot1)

shinyUI(fluidPage(
  
titlePanel("tumor growth inhibition model",windowTitle="tumor growth"),
    
  fluidRow(
    column(3, offset=1,
           h5("dosage regimen"),
           sliderInput("nd", "Number of doses:", value=6, min=0, max = 20, step=1, animate=TRUE),
           sliderInput("ii", "Interdose interval:", value = 9, min = 1, max = 20, step=1),
           sliderInput("amt", "Amount:", value = 1, min = 0, max = 5, step=0.25)
    ),
    column(2, offset=1,
           h5("parameters"),
           sliderInput("GAMMA", "GAMMA:", value = 1, min = 0, max = 4, step=0.1), 
           sliderInput("K", "K:", value = 100, min = 0, max = 200, step=5),
           sliderInput("KDE", "KDE:", value = 0.3, min = 0, max = 1, step=0.05)
    ),
    column(2,
           br(),br(),
           sliderInput("LAMBDAP", "LAMBDAP:", value = 0.12, min = 0, max = 0.5, step=0.025) ,
           sliderInput("DELTAQP", "DELTAQP:", value = 0.01, min = 0, max = 0.05, step=0.0025),
           sliderInput("KPQ", "KPQ:", value = 0.025, min = 0, max = 0.1, step=0.005)
    ),
    column(2,
           br(),br(),
           sliderInput("KQPP", "KQPP:", value = 0.004, min = 0, max = 0.01, step=0.0005)
    )
  ),
  tabsetPanel(
    tabPanel("Plot",   
             fluidRow(
               column(10, plotOutput("plot")),
               column(2, 
                      sliderInput("range", "time range", min = -100, max = 500, value = c(-50,200), step=10),
                      sliderInput("ngp", "grid size", min = 10, max = 1000, value = 200, step=10),
                      sliderInput("lsize", "line size", min = 0, max = 3, value = 0.75, step=0.25)
               )
    )), 
    tabPanel("Table", tableOutput("table")),
    tabPanel("Mlxtran", pre(includeText("tgi_model.txt"))),
    tabPanel("Simulx", pre(includeText("tgi_compute.R"))),
    tabPanel("ui.R", pre(includeText("ui.R"))),
    tabPanel("server.R", pre(includeText("server.R")))
  )

))

my.dir=getwd()
source("../initMlxR.R")
setwd(my.dir)

shinyServer(function(input, output) {

  r <- reactive({  
    param.value=c(input$K,input$KDE,input$KPQ,input$KQPP,input$LAMBDAP,input$GAMMA,input$DELTAQP)
    t.value=seq(input$range[1],input$range[2],length.out=input$ngp)
    t1=0
    t2=input$ii*(input$nd-1)+t1
    if (t2>=t1){
      t.dose=seq(t1,t2,by=input$ii)
      adm <- list(time=t.dose, amount=input$amt)
    }else{
      adm <- list(time=t1, amount=0)
    }
    
    f  <- list(name='PSTAR',time=t.value)
    p   <- list(name=c('K','KDE','KPQ','KQPP','LAMBDAP','GAMMA','DELTAQP'), value=param.value)
    
    res <- simulx( model     = 'tgi_model.txt',
                   treatment = adm, 
                 parameter = p,
                 output    = f)
    res$PSTAR
  })
  
  output$plot <- renderPlot({
    pl=ggplot(data=r(), aes(x=time, y=PSTAR)) + geom_line(size=input$lsize)
    print(pl)
  })

output$table <- renderTable({ r() })

  
})