calculateIAE: Calculate the Index of Achievable Efficacy
In braidReports: Visualize Combined Action Response Surfaces and Report BRAID Analyses

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/braidReports.R

Calculates the index of achievable efficacy, or IAE, (a measure of a drug combination's efficacy relative to toxicological and pharmacological constraints) based on a response surface representation of a combination in the form of a full BRAID surface parameter vector.

1	calculateIAE(parv, lev, macs, same = FALSE)

`parv`	a full 10-element BRAID surface parameter vector
`lev`	a single value or vector representing the effect level or levels at which the IAE should be calculated
`macs`	the maximum achievable concentrations of the two drugs whose effects are represented by the response surface. A single value may be given, which will be used for both drugs
`same`	a boolean variable representing whether the two drugs in the combination are believed to be the same drug (their dose-response parameters need not be identical). If `TRUE`, the values in `macs` must be identical

The IAE is a measure of the aggregate ratio of achievable dose-pairs for a given combination and the minimum dose pairs required to achieve a given effect. Formally, it is defined as

IAE = (Int(AC)[dDA dDB]/Int(AC)[(1-H[(EAB(DA,DB)-E)/(Ef-E)])dDA dDB])^(1/2)

where AC is the space of all achievable dose pairs as determined by pharmacological or toxicological constraints. In this function, this space is represented either as a rectangular region in dose-pair-space bounded by the two values in the parameter macs (when same is FALSE) or the lower triangular region of dose-pair-space in which the sum of the two doses is less than the single value in macs (when same is TRUE).

A single value or vector of values containing the estimated IAE for the response surface at the effect level or levels specified in lev.

Nathaniel R. Twarog

Twarog, N.R., Stewart, E., Vowell Hamill, C., and Shelat, A. BRAID: A Unifying Paradigm for the Analysis of Combined Drug Action. Scientific Reports In Press (2016).

makeBRAIDreport

data(es8analysis)
bfit <- es8analysis$braidFit
# Modelled effect is base-10 logarithm of cell survival relative to negative controls,
# so a level of -2 reflects 99% cell killing
calculateIAE(bfit$fullpar,c(-1,-2),c(1.015*10^-6,5*10^-5))