Characterization of a three-drug nonlinear mixture response model.

Our group recently developed a response-surface modeling paradigm (White et al: Curr Drug Metab 2, 399-409, 2003) and tested its application to both mixtures of anticancer agents and antifungals. This new model is a Hill-type equation, with the slope and potency parameters being functions of the normalized drug ratios, using polynomial expressions. Response surface methods allow one to model and interpret all of the information present in the full concentration-effect data set, to visualize local regions of synergy, additivity and antagonism, and even to quantify the degree of synergy or antagonism, both globally, and across local regions of the response surface.

Simultaneous modeling of concentration-effect and time-course patterns in gene expression data from microarrays.

Background: Time-course and concentration-effect experiments with multiple time-points and drug concentrations provide far more valuable information than experiments with just two design-points (treated vs. control), as commonly performed in most microarray studies. Analysis of the data from such complex experiments, however, remains a challenge.

Modeling the combination of amphotericin B, micafungin, and nikkomycin Z against Aspergillus fumigatus in vitro using a novel response surface paradigm.

Response surface methods for the study of multiple-agent interaction allow one to model all of the information present in full concentration-effect data sets and to visualize and quantify local regions of synergy, additivity, and antagonism. In randomized wells of 96-well plates, Aspergillus fumigatus was exposed to various combinations of amphotericin B, micafungin, and nikkomycin Z. The experimental design was comprised of 91 different fixed-ratio mixtures, all performed in quintuplicate.