This adds a dosing event to the event table. This is provided for
piping syntax through magrittr. It can also be accessed by eventTable$add.dosing(...)
Usage
add.dosing(
eventTable,
dose,
nbr.doses = 1L,
dosing.interval = 24,
dosing.to = 1L,
rate = NULL,
amount.units = NA_character_,
start.time = 0,
do.sampling = FALSE,
time.units = NA_character_,
...
)
Arguments
- eventTable
eventTable object; When accessed from object it would be
eventTable$
- dose
numeric scalar, dose amount in
amount.units
;- nbr.doses
integer, number of doses;
- dosing.interval
required numeric scalar, time between doses in
time.units
, defaults to 24 oftime.units="hours"
;- dosing.to
integer, compartment the dose goes into (first compartment by default);
- rate
for infusions, the rate of infusion (default is
NULL
, for bolus dosing;- amount.units
optional string indicating the dosing units. Defaults to
NA
to indicate as per the originalEventTable
definition.- start.time
required dosing start time;
- do.sampling
logical, should observation sampling records be added at the dosing times? Defaults to
FALSE
.- time.units
optional string indicating the time units. Defaults to
"hours"
to indicate as per the originalEventTable
definition.- ...
Other parameters passed to
et()
.
References
Wang W, Hallow K, James D (2015). "A Tutorial on rxode2: Simulating Differential Equation Pharmacometric Models in R." CPT: Pharmacometrics and Systems Pharmacology, 5(1), 3-10. ISSN 2163-8306
See also
eventTable
, add.sampling
,
add.dosing
, et
,
etRep
, etRbind
,
rxode2
Examples
if (FALSE) { # \dontrun{
library(rxode2)
library(units)
# Model from rxode2 tutorial
# Using a nlmixr2 style function
mod1 <-function(){
ini({
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
})
model({
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
})
}
## These are making the more complex regimens of the rxode2 tutorial
## bid for 5 days
bid <- et(timeUnits="hr") |>
et(amt=10000,ii=12,until=set_units(5, "days"))
## qd for 5 days
qd <- et(timeUnits="hr") |>
et(amt=20000,ii=24,until=set_units(5, "days"))
## bid for 5 days followed by qd for 5 days
et <- seq(bid,qd) |>
et(seq(0,11*24,length.out=100))
bidQd <- rxSolve(mod1, et)
plot(bidQd, C2)
## Now Infusion for 5 days followed by oral for 5 days
## note you can dose to a named compartment instead of using the compartment number
infusion <- et(timeUnits = "hr") |>
et(amt=10000, rate=5000, ii=24, until=set_units(5, "days"), cmt="centr")
qd <- et(timeUnits = "hr") |>
et(amt=10000, ii=24, until=set_units(5, "days"), cmt="depot")
et <- seq(infusion,qd)
infusionQd <- rxSolve(mod1, et)
plot(infusionQd, C2)
## 2wk-on, 1wk-off
qd <- et(timeUnits = "hr") |>
et(amt=10000, ii=24, until=set_units(2, "weeks"), cmt="depot")
et <- seq(qd, set_units(1,"weeks"), qd) |>
add.sampling(set_units(seq(0, 5.5,by=0.005),weeks))
wkOnOff <- rxSolve(mod1, et)
plot(wkOnOff, C2)
## You can also repeat the cycle easily with the rep function
qd <-et(timeUnits = "hr") |>
et(amt=10000, ii=24, until=set_units(2, "weeks"), cmt="depot")
et <- etRep(qd, times=4, wait=set_units(1,"weeks")) |>
add.sampling(set_units(seq(0, 12.5,by=0.005),weeks))
repCycle4 <- rxSolve(mod1, et)
plot(repCycle4, C2)
} # }