PII-057

G. Vlasakakis,1 R. L. O'Connor-Semmes,2 M. A. Young2; 1GlaxoSmithKline, London, United Kingdom, 2GlaxoSmithKline, Research Triangle Park, NC

BACKGROUND: The assessment of synergy between drug entities is critical in therapeutic areas such as HIV, oncology, anaesthesiology, diabetes, and obesity where combination therapies are commonly used to maximize drug effect and minimize toxicity. A major component aiding research in this direction is the utilization of modern in silico resources and surface response analyses to identify regions of synergistic efficacy among molecules by using modeling and visualization tools. The objective of this work was to illustrate a surface response analysis tool for the assessment of drug synergy implemented in the R computing environment.
METHODS: A surface response is a mathematical 3D representation that relates a dependent variable, such as drug effect, to two (or more) independent inputs, such as doses or drug concentrations (Kern, 2004). In this example, a surface response was constructed by simulating dosing combinations for two agonists in order to assess their maximum synergistic efficacy.
RESULTS: Figure
CONCLUSION: A surface response analysis is part of a library of functions in R (“rgl”) which makes it easy to understand, adjust and debug. Surface response analyses support informed decision-making by providing a method to fit and visualize additive, synergistic data and identify regions of clinical interest.