View source: R/tci_algorithms.R
apply_tci | R Documentation |
Apply a TCI algorithm to a set of targets and a 'pkmod' object to calculate infusion rates.
apply_tci( pkmod, target_vals, target_tms, type = c("plasma", "effect"), dtm = NULL, custom_alg = NULL, inittm = 0, ignore_pd = FALSE, ... )
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 |
# 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")
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