Weiss, AndreaDing, XiantingVan Beijnum, Judy R.Wong, IeongWong, Tse J.Berndsen, Robert H.Dormond, OlivierDallinga, MarchienShen, LiSchlingemann, Reinier O.Pili, RobertoHo, Chih-MingDyson, Paul J.Van Den Bergh, HubertGriffioen, Arjan W.Nowak-Sliwinska, Patrycja2015-09-282015-09-282015-09-28201510.1007/s10456-015-9462-9https://infoscience.epfl.ch/handle/20.500.14299/119023WOS:000356451300002Drug combinations can improve angiostatic cancer treatment efficacy and enable the reduction of side effects and drug resistance. Combining drugs is non-trivial due to the high number of possibilities. We applied a feedback system control (FSC) technique with a population-based stochastic search algorithm to navigate through the large parametric space of nine angiostatic drugs at four concentrations to identify optimal low-dose drug combinations. This implied an iterative approach of in vitro testing of endothelial cell viability and algorithm-based analysis. The optimal synergistic drug combination, containing erlotinib, BEZ-235 and RAPTA-C, was reached in a small number of iterations. Final drug combinations showed enhanced endothelial cell specificity and synergistically inhibited proliferation (p < 0.001), but not migration of endothelial cells, and forced enhanced numbers of endothelial cells to undergo apoptosis (p < 0.01). Successful translation of this drug combination was achieved in two preclinical in vivo tumor models. Tumor growth was inhibited synergistically and significantly (p < 0.05 and p < 0.01, respectively) using reduced drug doses as compared to optimal single-drug concentrations. At the applied conditions, single-drug monotherapies had no or negligible activity in these models. We suggest that FSC can be used for rapid identification of effective, reduced dose, multi-drug combinations for the treatment of cancer and other diseases.Anti-angiogenesisCombination therapyDrug-drug interactionsFeedback system controlSearch algorithmtext::journal::journal article::research article