poppkmod: Implement a population pharmacokinetic/pharmacodynamic model.

In tci: Target Controlled Infusion (TCI)

Implement a population pharmacokinetic/pharmacodynamic model.

Description

Create a 'poppkmod' object using an existing population PK model for propofol or remifentanil using patient covariates. Available models for propofol are the Marsh, Schnider, and Eleveld models. Available models for remifentanil are the Minto, Kim, and Eleveld models. Input is a data frame with rows corresponding to individuals and columns recording patient covariates. An ID column is optional, but will be generated as 1:nrow(data) if not supplied. Covariates required by each model are

Propofol

• Marsh: TBW

• Schnider: (AGE, HGT, TBW, MALE) or (AGE, HGT, LBW)

• Eleveld: AGE, TBW, HGT, MALE

Remifentanil

• Minto: (AGE, HGT, TBW, MALE) or (AGE, HGT, LBW)

• Kim: (AGE, TBW, BMI, HGT) or (AGE, TBW, FFM)

• Eleveld: (AGE, MALE, TBW, HGT) or (AGE, MALE, TBW, BMI)

Abbreviations

• TBW = Total body weight (kg)

• LBW = Lean body weight (kg)

• FFM = Fat-free mass (kg)

• AGE = Age (years)

• HGT = Height (cm)

• MALE = Male (1/0, TRUE/FALSE)

• BMI = Body mass index (kg/m^2)

Usage

poppkmod(
  data,
  drug = c("ppf", "remi"),
  model = c("marsh", "schnider", "eleveld", "minto", "kim"),
  sample = FALSE,
  PD = TRUE,
  ...
)

Arguments

data	Data frame of patient covariates. ID values, if used, should be in a column labeled "id" or "ID"
drug	"ppf" for propofol or "remi" for remifentanil. Defaults to "ppf".
model	Model name. Options are "marsh", "schnider", or "eleveld" if drug = "ppf", or "minto", "kim", or "eleveld" if drug = "remi".
sample	Logical. Should parameter values be sampled from interindividual distribution (TRUE) or evaluated at point estimates for covariates (FALSE)? Defaults to FALSE.
PD	Logical. If applicable, should the PD component be evaluated for PK-PD models. Defaults to TRUE.
...	Arguments passed on to each pkmod object

Value

'poppkmod' object

Examples

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))
poppkmod(data, drug = "ppf", model = "eleveld")
poppkmod(data, drug = "remi", model = "kim")

tci documentation built on Aug. 15, 2022, 9:09 a.m.