evalUrsaModel {braidrm} | R Documentation |
Evaluate URSA response surface model
Description
Numerically estimates the universal response surface approach (URSA) model for the given data and parameters (Greco, Park, and Rustum 1990).
Usage
evalUrsaModel(DA, DB, upar)
Arguments
DA |
A vector of concentrations of drug A in a combination (values 0
and |
DB |
A vector of concentrations of drug B in a combination (values 0
and |
upar |
A length seven URSA response surface parameter vector (see Details) |
Details
The URSA model is described by the following seven values
IDMA: The dose of median effect of drug A, also called the EC50
IDMB: The dose of median effect of drug B
na: The Hill slope, or sigmoidicity, of drug A
nb: The Hill slope of drug B
alpha: The URSA interaction parameter, indicating additivity (alpha = 0), antagonism (alpha < 0), or synergy (alpha > 0)
E0: The minimal effect, the effect observed when neither drug is present
Ef: The maximal effect of the drugs, theoretically observed when either drug is present at infinite concentration
Value
A numeric vector the same length as DA
and/or DB
with the predicted URSA response surface values.
References
Greco, William R, Hyoung Sook Park, and Youcef M Rustum. 1990. “Application of a New Approach for the Quantitation of Drug Synergism to the Combination of Cis-Diamminedichloroplatinum and 1-b-d-Arabinofuranosylcytosine.” Cancer Research 50 (17): 5318–27.
Examples
concentrations <- c(0, 2^(-3:3))
surface <- data.frame(
concA = rep(concentrations,each=length(concentrations)),
concB = rep(concentrations,times=length(concentrations))
)
surface$uadditive <- evalUrsaModel(
surface$concA,
surface$concB,
c(1, 1, 3, 3, 0, 0, 100)
)
surface$usynergy <- evalUrsaModel(
surface$concA,
surface$concB,
c(1, 1, 3, 3, 5, 0, 80)
)
surface$uantagonism <- evalUrsaModel(
surface$concA,
surface$concB,
c(1, 1, 3, 3, -0.5, 0, 100)
)
head(surface)