tumor growth inhibition model

dosage regimen 1
dosage regimen 2
parameters

  [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(2, offset=1,
           h5("dosage regimen 1"),
           sliderInput("nd1", "Number of doses:", value=6, min=0, max = 20, step=1),
           sliderInput("ii1", "Interdose interval:", value = 12, min = 1, max = 20, step=1),
           sliderInput("amt1", "Amount:", value = 1, min = 0, max = 5, step=0.25)
    ),
    column(2,
           h5("dosage regimen 2"),
           sliderInput("nd2", "Number of doses:", value=6, min=0, max = 20, step=1),
           sliderInput("ii2", "Interdose interval:", value = 4, min = 1, max = 20, step=1),
           sliderInput("amt2", "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(),
           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),
           sliderInput("KQPP", "KQPP:", value = 0.004, min = 0, max = 0.01, step=0.0005)
    )
  ),

  tabsetPanel(
    tabPanel("Plot", 
             fluidRow(
               column(10, plotOutput("plot")),
               column(2, 
                      checkboxGroupInput("checkGroup", label = h4("id"), 
                                         choices = list("1" = 1, "2" = 2),
                                         selected = c(1,2)),
                      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)

    t11=0
    t12=input$ii1*(input$nd1-1)+t11
    if (t12>=t11){
      t1.dose=seq(t11,t12,by=input$ii1)
      adm1 <- list(time=t1.dose, amount=input$amt1)
    }else{
      adm1 <- list(time=t11, amount=0, type=1)
    }
    t21=0
    t22=input$ii2*(input$nd2-1)+t21
    if (t22>=t21){
      t2.dose=seq(t21,t22,by=input$ii2)
      adm2 <- list(time=t2.dose, amount=input$amt2)
    }else{
      adm2 <- list(time=t21, amount=0, type=2)
    }
    
    g <- list(list(treatment=adm1),list(treatment=adm2))
      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',
                   group = g, 
                 parameter = p,
                 output    = f)
    res$PSTAR
  })
  
  output$plot <- renderPlot({
    palette=c("#000000", "#CC79A7")
    id <- as.numeric(input$checkGroup)
    if (length(id>0)){
    palette <- palette[id]
    r=r()
    r=r[(r$id %in% id),]
#    palette[as.numeric(input$checkGroup)]="#FFFFFF"
    pl=ggplot(data=r, aes(x=time, y=PSTAR, colour=id)) + geom_line(size=1) + 
       scale_colour_manual(values=palette)
    print(pl)
}
  })

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

  
})