| rxDerived {RxODE} | R Documentation |
This calculates the derived parameters based on what is provided in a data frame or arguments
rxDerived(..., verbose = FALSE, digits = 0)
... |
The input can be:
|
verbose |
boolean that when TRUE provides a message about the detected pk parameters
and the detected compartmental model. By default this is |
digits |
represents the number of significant digits for the output; If the number is zero or below (default), do not round. |
Return a data.frame of derived PK parameters for a 1-, 2-, or 3-compartment linear model given provided clearances and volumes based on the inferred model type.
The model parameters that will be provided in the data frame are:
vc: Central Volume (for 1-, 2- and 3-
compartment models)
kel: First-order elimination rate (for 1-, 2-, and
3-compartment models)
k12: First-order rate of transfer from central to
first peripheral compartment; (for 2- and 3-compartment models)
k21: First-order rate of transfer from first
peripheral to central compartment, (for 2- and 3-compartment
models)
k13: First-order rate of transfer from central to
second peripheral compartment; (3-compartment model)
k31: First-order rate of transfer from second
peripheral to central compartment (3-compartment model)
vp: Peripheral Volume (for 2- and 3- compartment models)
vp2: Peripheral Volume for 3rd compartment (3- compartment model)
vss: Volume of distribution at steady state; (1-, 2-, and 3-compartment models)
t12alpha: t_{1/2,α}; (1-, 2-, and 3-compartment models)
t12beta: t_{1/2,β}; (2- and 3-compartment models)
t12gamma: t_{1/2,γ}; (3-compartment model)
alpha: α; (1-, 2-, and 3-compartment models)
beta: β; (2- and 3-compartment models)
gamma: β; (3-compartment model)
A: true A; (1-, 2-, and 3-compartment models)
B: true B; (2- and 3-compartment models)
C: true C; (3-compartment model)
fracA: fractional A; (1-, 2-, and 3-compartment models)
fracB: fractional B; (2- and 3-compartment models)
fracC: fractional C; (3-compartment model)
Matthew Fidler and documentation from Justin Wilkins, justin.wilkins@occams.com
Shafer S. L. CONVERT.XLS
Rowland M, Tozer TN. Clinical Pharmacokinetics and Pharmacodynamics: Concepts and Applications (4th). Clipping Williams & Wilkins, Philadelphia, 2010.
## Note that RxODE parses the names to figure out the best PK parameter params <- rxDerived(cl=29.4, v=23.4, Vp=114, vp2=4614, q=270, q2=73) ## That is why this gives the same results as the value before params <- rxDerived(CL=29.4, V1=23.4, V2=114, V3=4614, Q2=270, Q3=73) ## You may also use micro-constants alpha/beta etc. params <- rxDerived(k12=0.1, k21=0.2, k13=0.3, k31=0.4, kel=10, v=10) ## or you can mix vectors and scalars params <- rxDerived(CL=29.4, V=1:3) ## If you want, you can round to a number of significant digits ## with the `digits` argument: params <- rxDerived(CL=29.4, V=1:3, digits=2)