R: Event Table Function

et {RxODE} | R Documentation

## Event Table Function

### Description

Event Table Function

### Usage

    et(x, ..., envir = parent.frame())

    ## S3 method for class 'RxODE'
    et(x, ..., envir = parent.frame())

    ## S3 method for class 'rxSolve'
    et(x, ..., envir = parent.frame())

    ## S3 method for class 'rxParams'
    et(x, ..., envir = parent.frame())

    ## Default S3 method:
    et(
      x,
      ...,
      time,
      amt,
      evid,
      cmt,
      ii,
      addl,
      ss,
      rate,
      dur,
      until,
      id,
      amountUnits,
      timeUnits,
      addSampling,
      envir = parent.frame(),
      by = NULL,
      length.out = NULL
    )

### Arguments

`x` | This is the first argument supplied to the event table. This is named to allow `et` to be used in a pipe-line with arbitrary objects.
`...` | Times or event tables. They can also be one of the named arguments below.
`envir` | the `environment` in which `expr` is to be evaluated. May also be `NULL`, a list, a data frame, a pairlist or an integer as specified to `sys.call`.
`time` | Time is the time of the dose or the sampling times. This can also be unspecified and is determined by the object type (list or numeric/integer).
`amt` | Amount of the dose. If specified, this assumes a dosing record, instead of a sampling record.
`evid` | Event ID; This can be:
Numeric Value | Description
0 | An observation. This can also be specified as `evid=obs`
1 | A dose observation. This can also be specified as `evid=dose`
2 | A non-dose event. This can also be specified as `evid=other`
3 | A reset event. This can also be specified as `evid=reset`.
4 | Dose and reset event. This can also be specified as `evid=doseReset` or `evid=resetDose`
Note a reset event resets all the compartment values to zero and turns off all infusions.
`cmt` | Compartment name or number. If a number, this is an integer starting at 1. Negative compartments turn off a compartment. If the compartment is a name, the compartment name is changed to the correct state/compartment number before running the simulation. For a compartment named "-cmt" the compartment is turned off.
    Can also specify `cmt` as `dosing.to`,
    `dose.to`, `doseTo`, `dosingTo`, and
    `state`.
`ii` | When specifying a dose, this is the inter-dose interval for `ss`, `addl` and `until` options (described below).
`addl` | The number of additional doses at a inter-dose interval after one dose.
`ss` | Steady state flag; It can be one of:
Value | Description
0 | This dose is not a steady state dose
1 | This dose is a steady state dose with the between/inter-dose interval of `ii`
2 | Superposition steady state
When `ss=2` the steady state dose that uses the super-position principle to allow more complex steady states, like 10 mg in the morning and 20 mg at night, or dosing at 8 am 12 pm and 8 pm instead of every 12 hours. Since it uses the super positioning principle, it only makes sense when you know the kinetics are linear. All other values of `SS` are currently invalid.
`rate` | When positive, this is the rate of infusion. Otherwise:
Value | Description
0 | No infusion is on this record
-1 | Modeled rate (in RxODE:`rate(cmt) =`); Can be `et(rate=model)`.
-2 | Modeled duration (in RxODE: `dur(cmt) =`); Can be`et(dur=model)` or `et(rate=dur)`.
When a modeled bioavailability is applied to positive rates (`rate` > 0), the duration of infusion is changed. This is because the data specify the rate and amount, the only think that modeled bioavailability can affect is duration. If instead you want the modeled bioavailability to increase the rate of infusion instead of the duration of infusion, specify the `dur` instead or model the duration with `rate=2`.
`dur` | Duration of infusion. When `amt` and `dur` are specified the rate is calculated from the two data items. When `dur` is specified instead of `rate`, the bioavailability changes will increase rate instead of duration.
`until` | This is the time until the dosing should end. It can be an easier way to figure out how many additional doses are needed over your sampling period.
`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.
`amountUnits` | The units for the dosing records (`amt`)
`timeUnits` | The units for the time records (`time`)
`addSampling` | This is a boolean indicating if a sampling time should be added at the same time as a dosing time. By default this is `FALSE`.
`by` | When there are no observations in the event table, this is the amount to increment for the observations between `from` and `to`.
`length.out` | The number of observations to create if there isn't any observations in the event table. By default this is 200.

### Value

A new event table

### Author(s)

Matthew L Fidler, Wenping Wang

### 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`

### Examples

    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)

[Package RxODE version 1.0.9 Index]