title: Optimization of drug combinations using Feedback System Control.
abstract: We describe a protocol for the discovery of synergistic drug combinations for the treatment of disease. Synergistic drug combinations lead to the use of drugs at lower doses, which reduces side effects and can potentially lead to reduced drug resistance, while being clinically more effective than the individual drugs. To cope with the extremely large search space for these combinations, we developed an efficient combinatorial drug screening method called the Feedback System Control (FSC) technique. Starting with a broad selection of drugs, the method follows an iterative approach of experimental testing in a relevant bioassay and analysis of the results by FSC. First, the protocol uses a cell viability assay to generate broad dose-response curves to assess the efficacy of individual compounds. These curves are then used to guide the dosage input of each drug to be tested in combination. Data from applied drug combinations are input into the differential evolution (DE) algorithm, which predicts new combinations to be tested in vitro. This process identifies optimal drug-dose combinations, while saving orders of magnitude in experimental effort. The complete optimization process is estimated to take ∼4 weeks. FSC does not require insight into the disease mechanism, and it has therefore been applied to find combination therapies for many different pathologies, including cancer and infectious diseases, and it has also been used in organ transplantation.
authors.affiliation: Department of Medical Oncology, Angiogenesis Laboratory, Vrije Universiteit (VU) University Medical Center, Amsterdam, the Netherlands.
authors.forename: Patrycja
authors.initials: P
authors.lastname: Nowak-Sliwinska
authors.affiliation: Department of Medical Oncology, Angiogenesis Laboratory, Vrije Universiteit (VU) University Medical Center, Amsterdam, the Netherlands.
authors.forename: Andrea
authors.initials: A
authors.lastname: Weiss
authors.affiliation: Med-X Research Institute, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
authors.forename: Xianting
authors.initials: X
authors.lastname: Ding
authors.affiliation: Institute of Chemical Sciences and Engineering, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland.
authors.forename: Paul J
authors.initials: PJ
authors.lastname: Dyson
authors.affiliation: Institute of Chemical Sciences and Engineering, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland.
authors.forename: Hubert
authors.initials: H
authors.lastname: van den Bergh
authors.affiliation: Department of Medical Oncology, Angiogenesis Laboratory, Vrije Universiteit (VU) University Medical Center, Amsterdam, the Netherlands.
authors.forename: Arjan W
authors.initials: AW
authors.lastname: Griffioen
authors.affiliation: Department of Mechanical and Aerospace Engineering, University of California, Los Angeles, California, USA.
authors.forename: Chih-Ming
authors.identifier: http://orcid.org/0000-0001-7369-5446
authors.initials: CM
authors.lastname: Ho
mesh_terms: D001681:Biological Assay; D004338:Drug Combinations; D004353:Drug Evaluation, Preclinical / Q000379:methods*; D004357:Drug Synergism; D004359:Drug Therapy, Combination / Q000379:methods; D006801:Humans
chemical_list: D004338:Drug Combinations