Simulate responses from a `pkmod` or `poppkmod` object using TCI control. Infusion rates are calculated to reach targets using `pkmod_prior`. Data values are simulated using `pkmod_true`. `pkmod_prior` and `pkmod_true` do not need to have the same parameters or structure and should be different when simulating responses under model misspecification. If update times (argument `update_tms`) are provided then the function `simulate_clc` is called for "closed-loop" control and model parameters will be updated via Bayes' rule using available data. Only parameters with values in the Omega matrix will be updated. A data processing delay can be added through the argument `delay`. See ?bayes_update? for more details. If update times are not specified, then the function `simulate_olc` will be called to implement "open-loop" control and model parameters will not be updated. Simulation results have class `tci_sim` and can be plotted using `plot.tci_sim()`.
simulate_tci(
pkmod_prior,
pkmod_true,
target_vals,
target_tms,
obs_tms,
update_tms = NULL,
type = c("effect", "plasma"),
custom_alg = NULL,
resp_bounds = NULL,
delay = 0,
seed = NULL,
verbose = TRUE
)`pkmod` or `poppkmod` object describing a PK/PK-PD model that is used to calculate TCI infusion rates and is updated as data are simulated and incorporated. Must have an associated Omega matrix.
`pkmod` or `poppkmod` object describing the patient's "true" response. This model will be used to simulate observations.
A vector of numeric values indicating PK or PD targets for TCI algorithm.
A vector of numeric values indicating times at which the TCI algorithm should begin targeting each value.
Times at which data values should be simulated from `pkmod_true`.
Times at which `pkmod_prior` should be updated using all available simulated observations.
Type of TCI algorithm to be used. Options are "plasma" and "effect". Defaults to "effect". Will be overwritten if `custom_alg` is non-null.
Custom TCI algorithm to overwrite default plasma- or effect-site targeting.
Optional vector of two values indicating minimum and maximum values possible for the response.
Optional numeric value indicating a temporal delay between when observations are simulated and when they should be made available for updating `pkmod_prior`. For example, a delay should be set to account for a processing time delay in Bispectral Index measurements or the time required to measure drug concentrations from collected samples.
An integer used to initialize the random number generator.
Logical. Print progress as simulation is run.
data <- data.frame(ID = 1:3, AGE = c(20,30,40), TBW = c(60,70,80),
HGT = c(150,160,170), MALE = c(TRUE,FALSE,TRUE))
pkmod_prior <- poppkmod(data, drug = "ppf", model = "eleveld")
pkmod_true <- poppkmod(data, drug = "ppf", model = "eleveld", sample = TRUE)
obs_tms <- seq(1/6,10,1/6)
target_vals = c(75,60,50,50)
target_tms = c(0,3,6,10)
# open-loop simulation (without updates)
sim_ol <- simulate_tci(pkmod_prior, pkmod_true, target_vals, target_tms, obs_tms,
seed = 200)
plot(sim_ol)
# closed-loop simulation (with updates)
if (FALSE) {
sim_cl <- simulate_tci(pkmod_prior, pkmod_true, target_vals, target_tms, obs_tms,
update_tms = c(2,4,6,8), seed = 200)
plot(sim_cl, wrap_id = TRUE, show_inf = TRUE, show_data = TRUE)
}
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