title: Discovery of a low order drug-cell response surface for applications in personalized medicine.
abstract: The cell is a complex system involving numerous components, which may often interact in a non-linear dynamic manner. Diseases at the cellular level are thus likely to involve multiple cellular constituents and pathways. As some drugs, or drug combinations, may act synergistically on these multiple pathways, they might be more effective than the respective single target agents. Optimizing a drug mixture for a given disease in a particular patient is particularly challenging due to both the difficulty in the selection of the drug mixture components to start out with, and the all-important doses of these drugs to be applied. For n concentrations of m drugs, in principle, n(m) combinations will have to be tested. As this may lead to a costly and time-consuming investigation for each individual patient, we have developed a Feedback System Control (FSC) technique which can rapidly select the optimal drug-dose combination from the often millions of possible combinations. By testing this FSC technique in a number of experimental systems representing different disease states, we found that the response of cells to multiple drugs is well described by a low order, rather smooth, drug-mixture-input/drug-effect-output multidimensional surface. The main consequences of this are that optimal drug combinations can be found in a surprisingly small number of tests, and that translation from in vitro to in vivo is simplified. This points to the possibility of personalized optimal drug mixtures in the near future. This unexpectedly simple input-output relationship may also lead to a simple solution for handling the issue of human diversity in cancer therapeutics.
authors.affiliation: School of Biomedical Engineering, Med-X Research Institute, Shanghai Jiao Tong University (SJTU), 1954 Huashan Road, 200030, Shanghai, People's Republic of China.
authors.forename: Xianting
authors.initials: X
authors.lastname: Ding
authors.forename: Wenjia
authors.initials: W
authors.lastname: Liu
authors.forename: Andrea
authors.initials: A
authors.lastname: Weiss
authors.forename: Yiyang
authors.initials: Y
authors.lastname: Li
authors.forename: Ieong
authors.initials: I
authors.lastname: Wong
authors.forename: Arjan W
authors.initials: AW
authors.lastname: Griffioen
authors.forename: Hubert
authors.initials: H
authors.lastname: van den Bergh
authors.forename: Hongquan
authors.initials: H
authors.lastname: Xu
authors.forename: Patrycja
authors.initials: P
authors.lastname: Nowak-Sliwinska
authors.forename: Chih-Ming
authors.initials: CM
authors.lastname: Ho
mesh_terms: D002460:Cell Line; D004305:Dose-Response Relationship, Drug; D004359:Drug Therapy, Combination; D006801:Humans; D008954:Models, Biological; D058990:Molecular Targeted Therapy / Q000379:methods*; D004364:Pharmaceutical Preparations / Q000008:administration & dosage*; D057285:Precision Medicine / Q000379:methods*; D012044:Regression Analysis
chemical_list: D004364:Pharmaceutical Preparations