Add sampling to eventTable

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.sampling()

add.sampling(eventTable, time, time.units = NA)

Arguments

eventTable	An eventTable object. When accessed from object it would be eventTable$
time	a vector of time values (in time.units).
time.units	an optional string specifying the time units. Defaults to the units specified when the EventTable was initialized.

Value

eventTable with updated sampling. (Note the event table will be updated even if you don't reassign the eventTable)

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)


# }