View source: R/tci_algorithms.R
inf_tci | R Documentation |
Apply a TCI algorithm to a set of targets and a 'pkmod' or 'poppkmod' object to calculate infusion rates.
inf_tci( pkmod, target_vals, target_tms, type = c("plasma", "effect"), dtm = NULL, custom_alg = NULL, inittm = 0, ignore_pd = FALSE, pop_fn = NULL, ... )
pkmod |
'pkmod' object created by 'pkmod()' or a 'poppkmod' object created by 'poppkmod()'. |
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. |
pop_fn |
Function applied to the distribution of predicted values. E.g., 'median' will calculate doses such that the median value in the population will obtain the target value. Only applicable to 'poppkmod' objects. |
... |
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 inf_tci(my_mod, target_vals = c(2,3,4,4), target_tms = c(0,2,3,10), "plasma") # effect-site targeting inf_tci(my_mod, target_vals = c(2,3,4,4), target_tms = c(0,2,3,10), "effect") # poppkmod object data <- data.frame(ID = 1:5, AGE = seq(20,60,by=10), TBW = seq(60,80,by=5), HGT = seq(150,190,by=10), MALE = c(TRUE,TRUE,FALSE,FALSE,FALSE)) elvd_mod <- poppkmod(data, drug = "ppf", model = "eleveld") inf_tci(elvd_mod, target_vals = c(2,3,4,4), target_tms = c(0,2,3,10), "effect")
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