R: Pharmacokinetic Compartment Models

pkpd {rmutil} | R Documentation

## Pharmacokinetic Compartment Models

### Description

Mean functions for use in fitting pharmacokineticcompartment models models.

`mu1.0o1c`: open zero-order one-compartment model

`mu1.1o1c`: open first-order one-compartment model

`mu1.1o2c`: open first-order two-compartment model (ordered)

`mu1.1o2cl`: open first-order two-compartment model (ordered, absorption and transfer equal)

`mu1.1o2cc`: open first-order two-compartment model (circular)

Simultaneous models for parent drug and metabolite:

`mu2.0o1c`: zero-order one-compartment model

`mu2.0o2c1`: zero-order two-compartment for parent, one-compartment for metabolite, model

`mu2.0o2c2`: zero-order two-compartment model for both parent and metabolite

`mu2.1o1c`: first-order one-compartment model

`mu2.0o1cfp`: zero-order one-compartment first-pass model

`mu2.0o2c1fp`: zero-order two-compartment for parent, one-compartment for metabolite, model with first-pass

`mu2.0o2c2fp`: zero-order two-compartment model for both parent and metabolite with first-pass

`mu2.1o1cfp`: first-order one-compartment first-pass model

### Usage

    mu1.0o1c(p, times, dose=1, end=0.5)
    mu1.1o1c(p, times, dose=1)
    mu1.1o2c(p, times, dose=1)
    mu1.1o2cl(p, times, dose=1)
    mu1.1o2cc(p, times, dose=1)
    mu2.0o1c(p, times, dose=1, ind, end=0.5)
    mu2.0o2c1(p, times, dose=1, ind, end=0.5)
    mu2.0o2c2(p, times, dose=1, ind, end=0.5)
    mu2.1o1c(p, times, dose=1, ind)
    mu2.0o1cfp(p, times, dose=1, ind, end=0.5)
    mu2.0o2c1fp(p, times, dose=1, ind, end=0.5)
    mu2.0o2c2fp(p, times, dose=1, ind, end=0.5)
    mu2.1o1cfp(p, times, dose=1, ind)

### Arguments

`p` | Vector of parameters. See the source file for details.
`times` | Vector of times.
`dose` | Vector of dose levels.
`ind` | Indicator whether parent drug or metabolite.
`end` | Time infusion ends.

### Value

The profile of mean concentrations for the given times and doses is returned.

### Author(s)

J.K. Lindsey

### Examples

    ## Not run:
    library(repeated)
    times <- rep(1:20,2)
    dose <- c(rep(2,20),rep(5,20))
    # set up a mean function for gar based on mu1.1o1c:
    mu <- function(p) {
    	ka <- exp(p[2])
    	ke <- exp(p[3])
    	exp(p[2]-p[1])/(ka-ke)*(exp(-ke*times)-exp(-ka*times))}
    conc <- matrix(rgamma(40,2,scale=mu(log(c(1,0.3,0.2)))/2),ncol=20,byrow=TRUE)
    conc[,2:20] <- conc[,2:20]+0.5*(conc[,1:19]-matrix(mu(log(c(1,0.3,0.2))),
    	ncol=20,byrow=TRUE)[,1:19])
    conc <- ifelse(conc>0,conc,0.01)
    gar(conc, dist="gamma", times=1:20, mu=mu, preg=log(c(1,0.4,0.1)),
    	pdepend=0.1, pshape=1)
    # changing variance
    shape <- mu
    gar(conc, dist="gamma", times=1:20, mu=mu, preg=log(c(0.5,0.4,0.1)),
    	pdep=0.1, shape=shape, pshape=log(c(0.5,0.4,0.1)))

    ## End(Not run)

[Package rmutil version 1.1.3 Index]