evalMusycModel: Evaluate MuSyC Response Surfaces

In braidrm: Fitting Combined Action with the BRAID Response Surface Model

Evaluate MuSyC Response Surfaces

Description

Evaluates the Mulitdimensional Synergy of Combinations (MuSyC) model of combined action for the given values and parameters (Wooten et al. 2021).

Usage

evalMusycModel(DA, DB, mupar, calcderivs = FALSE)

Arguments

DA	A vector of concentrations of drug A in a combination (values 0 and Inf are permitted). Must be length 1 or the same length as DB.
DB	A vector of concentrations of drug B in a combination (values 0 and Inf are permitted). Must be length 1 or the same length as DA.
mupar	A MuSyC response surface parameter vector; may be length 8, 10, or 12 (see details for specifics of MuSyC parameters)
calcderivs	Primarily used by fitting functions for non-linear optimization. If FALSE (the default), the function returns a vector of response values; if TRUE, it returns a list including the partial derivatives of the BRAID parameters.

Details

The multi-dimensional synergy of combinatoins, or MySyC, model is a parametric response surface model introduced by Wooten et al. in 2021. The method models the effect of combination by simulating occupancy in four compartments in which compounds are affected or unaffected by either drug. The full MuSyC model can be specified by a total of twelve parameters:

• IDMA: dose of median effect of first drug

• IDMB: dose of median effect of second drug

• na: Hill slope of first drug

• nb: Hill slope of second drug

• alpha12: factor by which first drug potentiates the second

• alpha21: factor by which second drug potentiates the first

• gamma12: factor by which first drug increases second drug's Hill slope

• gamma21: factor by which second drug increases first drug's Hill slope

• E0 - the observed effect when unaffected by either drug

• EfA - the observed effect when affected by drug 1 but not drug 2

• EfB - the observed effect when affected by drug 2 but not drug 1

• Ef - the observed effect when affected by both drugs

In practice, gamma12 and gamma21 are rarely used, so a ten-element parameter vector specifies the other 10 values and assumes that gamma12 and gamma21 are both equal to 1. In some cases it is even useful to specify a MuSyC surface with no interaction at all with an eight-element vector, in which case alpha12, alpha21, gamma12, and gamma21 are all set equal to 1.

Value

If calcderivs is FALSE, a numeric vector the same length as DA and/or DB with the predicted MuSyC response surface values. If calcderivs is TRUE, a list with two elements: value, containing the response surface values, and derivatives, a matrix with as many rows as value has elements, and all columns containing the partial derivatives of the response surface with respect to the fitted MuSyC response surface parameters

References

Wooten, David J, Christian T Meyer, Alexander LR Lubbock, Vito Quaranta, and Carlos F Lopez. 2021. “MuSyC Is a Consensus Framework That Unifies Multi-Drug Synergy Metrics for Combinatorial Drug Discovery.” Nature Communications 12 (1): 4607.

Examples

efficacyPar <- c(
    1, 1, 3, 3,
                      # Omitted shape synergy parameters assume to be 1
    0, 100, 100, 125  # Elevated Ef indicates efficacy synergy
)
potencyPar <- c(
    1, 1, 3, 3,
    10, 15,           # alphas above 1 indicate potency synergy
    0, 100, 100, 100  # No efficacy synergy
)

concentrations <- c(0, 2^(-3:3))
surface <- data.frame(
    concA = rep(concentrations,each=length(concentrations)),
    concB = rep(concentrations,times=length(concentrations))
)
surface$efficacy <- evalMusycModel(surface$concA, surface$concB, efficacyPar)
surface$potency  <- evalMusycModel(surface$concA, surface$concB, potencyPar)

head(surface)

braidrm documentation built on Sept. 30, 2024, 9:40 a.m.