ode <- "
   C2 = centr/V2;
   C3 = peri/V3;
   d/dt(depot) =-KA*depot;
   d/dt(centr) = KA*depot - CL*C2 - Q*C2 + Q*C3;
   d/dt(peri)  =                    Q*C2 - Q*C3;
   d/dt(eff)  = Kin - Kout*(1-C2/(EC50+C2))*eff;
"

m1 <- RxODE(model = ode, modName = "m1")

# create dosing and observation (sampling) events
# QD (once daily) dosing, 5 days

qd <- eventTable(amount.units="umg", time.units = "hours")
qd$add.dosing(dose=10000, nbr.doses=5, dosing.interval = 24)

# hourly sampling during 1st day, every 4 hours afterwards
qd$add.sampling(0:24)                        # hourly
qd$add.sampling(seq(from=28, to=96, by=4) )  # every 4 hours

# BID dosing, 5 days

bid <- eventTable(amount.units="ug", time.units="days")  # only dosing
bid$add.dosing(dose = 10000, 
   nbr.doses = 2*5, 
   dosing.interval = 12)

bid$add.sampling(0:24)
bid$add.sampling(96+0:24)

# init values
theta <- 
   c(KA=2.94E-01,  CL=1.86E+01,  V2=4.02E+01,  Q=1.05E+01,  V3=2.97E+02,
     Kin=1, Kout=1, EC50=200)

qd.cp <- m1$solve(theta, qd, inits = c(0,0,0,1))
bid.cp <- m1$solve(theta, bid, inits = c(0,0,0,1))

cp.plot <-
function(cp, xlab = "Time (days)", ...)
{
   xtime <- cp[,"time"]
   matplot(xtime, cp[,c("depot", "centr", "peri")], type = "l", ...,
      xlab = xlab, ylab = "Drug amount (ug)")

   legend("topright", 
      legend = c("Depot", "Central", "Peripheral"), 
      title = "Compartment",
      col=1:3, lty = 1:3, bty = "n")

   plot(xtime, cp[,"eff"], type = "l", ...,
      xlab = xlab, ylab = "Effect compartment")
}

cp.plot(qd.cp, main = "QD dosing, 5 days")

cp.plot(bid.cp, main = "BID dosing, 5 days")
