poso_time_cmin {posologyr} | R Documentation |
Estimate the time required to reach a target trough concentration (Cmin)
Description
Estimates the time required to reach a target trough concentration (Cmin) given a population pharmacokinetic model, a set of individual parameters, a dose, and a target Cmin.
Usage
poso_time_cmin(
dat = NULL,
prior_model = NULL,
tdm = FALSE,
target_cmin,
dose = NULL,
cmt_dose = 1,
endpoint = "Cc",
estim_method = "map",
nocb = FALSE,
p = NULL,
greater_than = TRUE,
from = 0.2,
last_time = 72,
add_dose = NULL,
interdose_interval = NULL,
duration = 0,
indiv_param = NULL
)
Arguments
dat |
Dataframe. An individual subject dataset following the structure of NONMEM/rxode2 event records. |
prior_model |
A |
tdm |
A boolean. If
|
target_cmin |
Numeric. Target trough concentration (Cmin). |
dose |
Numeric. Dose administered. This argument is ignored if |
cmt_dose |
Character or numeric. The compartment in which the dose is to be administered. Must match one of the compartments in the prior model. Defaults to 1. |
endpoint |
Character. The endpoint of the prior model to be optimised for. The default is "Cc", which is the central concentration. |
estim_method |
A character string. An estimation method to be used for
the individual parameters. The default method "map" is the Maximum A
Posteriori estimation, the method "prior" simulates from the prior
population model, and "sir" uses the Sequential Importance Resampling
algorithm to estimate the a posteriori distribution of the individual
parameters. This argument is ignored if |
nocb |
A boolean. For time-varying covariates: the next observation
carried backward (nocb) interpolation style, similar to NONMEM. If
|
p |
Numeric. The proportion of the distribution of Cmin to consider for
the estimation. Mandatory for |
greater_than |
A boolean. If |
from |
Numeric. Starting time for the simulation of the individual
time-concentration profile. The default value is 0.2. When |
last_time |
Numeric. Ending time for the simulation of the individual
time-concentration profile. The default value is 72. When |
add_dose |
Numeric. Additional doses administered at inter-dose interval
after the first dose. Optional. This argument is ignored if |
interdose_interval |
Numeric. Time for the inter-dose interval for
multiple dose regimen. Must be provided when add_dose is used. This
argument is ignored if |
duration |
Numeric. Duration of infusion, for zero-order
administrations. This argument is ignored if |
indiv_param |
Optional. A set of individual parameters : THETA, estimates of ETA, and covariates. |
Value
A list containing the following components:
- time
Numeric. Time needed to reach the selected Cmin.
- type_of_estimate
Character string. The type of estimate of the individual parameters. Either a point estimate, or a distribution.
- cmin_estimate
A vector of numeric estimates of the Cmin. Either a single value (for a point estimate of ETA), or a distribution.
- indiv_param
A
data.frame
. The set of individual parameters used for the determination of the time needed to reach a selected Cmin: THETA, estimates of ETA, and covariates
Examples
rxode2::setRxThreads(2L) # limit the number of threads
# model
mod_run001 <- function() {
ini({
THETA_Cl <- 4.0
THETA_Vc <- 70.0
THETA_Ka <- 1.0
ETA_Cl ~ 0.2
ETA_Vc ~ 0.2
ETA_Ka ~ 0.2
prop.sd <- sqrt(0.05)
})
model({
TVCl <- THETA_Cl
TVVc <- THETA_Vc
TVKa <- THETA_Ka
Cl <- TVCl*exp(ETA_Cl)
Vc <- TVVc*exp(ETA_Vc)
Ka <- TVKa*exp(ETA_Ka)
K20 <- Cl/Vc
Cc <- centr/Vc
d/dt(depot) = -Ka*depot
d/dt(centr) = Ka*depot - K20*centr
Cc ~ prop(prop.sd)
})
}
# df_patient01: event table for Patient01, following a 30 minutes intravenous
# infusion
df_patient01 <- data.frame(ID=1,
TIME=c(0.0,1.0,14.0),
DV=c(NA,25.0,5.5),
AMT=c(2000,0,0),
EVID=c(1,0,0),
DUR=c(0.5,NA,NA))
# predict the time needed to reach a concentration of 2.5 mg/l
# after the administration of a 2500 mg dose over a 30 minutes
# infusion
poso_time_cmin(dat=df_patient01,prior_model=mod_run001,
dose=2500,duration=0.5,from=0.5,target_cmin=2.5)