apply_tci {tci} | R Documentation |
Apply a TCI algorithm to a 'pkmod' object
Description
Apply a TCI algorithm to a set of targets and a 'pkmod' object to calculate infusion rates.
Usage
apply_tci(
pkmod,
target_vals,
target_tms,
type = c("plasma", "effect"),
dtm = NULL,
custom_alg = NULL,
inittm = 0,
ignore_pd = FALSE,
...
)
Arguments
pkmod |
'pkmod' object created by 'pkmod()'. |
target_vals |
A vector of numeric values indicating PK or PD targets for TCI algorithm. |
target_tms |
A vector of numeric values indicating times at which the TCI algorithm should begin targeting each value. |
type |
Type of TCI algorithm to be used. Options are plasma- or effect-site targeting. |
dtm |
TCI update frequency. Defaults to 1/6, corresponding to 10-second intervals if model parameters are in terms of minutes. |
custom_alg |
Custom TCI algorithm to be used instead of default plasma- or effect-site targeting algorithms. The algorithm should be a function that takes minimum arguments 'Ct', 'pkmod', and 'dtm' and returns a single infusion rate. See 'tci_plasma' or 'tci_effect' for examples and vignette on custom models/algorithms for more details. |
inittm |
Initial time to start TCI algorithm. Cannot be greater than the minimum value of 'target_tms'. |
ignore_pd |
Logical. Should the PD component of the pkmod object (if present) be ignored. By default, predict.tciinf will assume that 'value' refers to PD targets if a PD model is specified. |
... |
Arguments passed to TCI algorithm |
Examples
# 3-compartment model with effect-site
my_mod <- pkmod(pars_pk = c(v1 = 8.995, v2 = 17.297, v3 = 120.963, cl = 1.382,
q2 = 0.919, q3 = 0.609, ke0 = 1.289))
# plasma targeting
apply_tci(my_mod, target_vals = c(2,3,4,4), target_tms = c(0,2,3,10), "plasma")
# effect-site targeting
apply_tci(my_mod, target_vals = c(2,3,4,4), target_tms = c(0,2,3,10), "effect")
# incorporate PD model
my_mod_pd <- update(my_mod, pars_pd = c(c50 = 2.8, gamma = 1.47, e0 = 93, emx = 93),
pdfn = emax, pdinv = emax_inv)
apply_tci(my_mod_pd, target_vals = c(70,60,50,50), target_tms = c(0,2,3,10), "effect")