Repeat an RxODE event table

Repeat an RxODE event table

etRep(
  x,
  times = 1,
  length.out = NA,
  each = NA,
  n = NULL,
  wait = 0,
  id = integer(0),
  samples = c("clear", "use"),
  waitII = c("smart", "+ii"),
  ii = 24
)

# S3 method for rxEt
rep(x, ...)

Arguments

x	An RxODE event table
times	Number of times to repeat the event table
length.out	Invalid with RxODE event tables, will throw an error if used.
each	Invalid with RxODE event tables, will throw an error if used.
n	The number of times to repeat the event table. Overrides times.
wait	Waiting time between each repeated event table. By default there is no waiting, or wait=0
id	A integer vector of IDs to add or remove from the event table. If the event table is identical for each ID, then you may expand it to include all the IDs in this vector. All the negative IDs in this vector will be removed.
samples	How to handle samples when repeating an event table. The options are: "clear" Clear sampling records before combining the datasets "use" Use the sampling records when combining the datasets
waitII	This determines how waiting times between events are handled. The options are: "smart" This "smart" handling of waiting times is the default option. In this case, if the waiting time is above the last observed inter-dose interval in the first combined event table, then the actual time between doses is given by the wait time. If it is smaller than the last observed inter-dose interval, the time between event tables is given by the inter-dose interval + the waiting time between event tables. "+ii" In this case, the wait time is added to the inter-dose interval no matter the length of the wait time or inter-dose interval
ii	When specifying a dose, this is the inter-dose interval for ss, addl and until options (described below).
...	Times or event tables. They can also be one of the named arguments below.

Value

An event table

References

Wang W, Hallow K, James D (2015). "A Tutorial on RxODE: Simulating Differential Equation Pharmacometric Models in R." CPT: Pharmacometrics \& Systems Pharmacology, 5(1), 3-10. ISSN 2163-8306, <URL: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4728294/>.

See also

eventTable, add.sampling, add.dosing, et, etRep, etRbind, RxODE

Author

Matthew L Fidler, Wenping Wang

Examples

# \donttest{

library(RxODE)
library(units)

## Model from RxODE tutorial
mod1 <-RxODE({
    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;
    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 RxODE 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)


# }