Closed-loop control of cellular functions using combinatory drugs guided by a stochastic search algorithm.
A mixture of drugs is often more effective than using a single effector. However, it is extremely challenging to identify potent drug combinations by trial and error because of the large number of possible combinations and the inherent complexity of the underlying biological network. With a closed-loop optimization modality, we experimentally demonstrate effective searching for potent drug combinations for controlling cellular functions through a large parametric space. Only tens of iterations out of one hundred thousand possible trials were needed to determine a potent combination of drugs for inhibiting vesicular stomatitis virus infection of NIH 3T3 fibroblasts. In addition, the drug combination reduced the required dosage by approximately 10-fold compared with individual drugs. In another example, a potent mixture was identified in thirty iterations out of a possible million combinations of six cytokines that regulate the activity of nuclear factor kappa B in 293T cells. The closed-loop optimization approach possesses the potential of being an effective approach for manipulating a wide class of biological systems.
Wong
Pak Kin
PK
Department of Aerospace and Mechanical Engineering and Bio5 Institute, University of Arizona, N718, 1130 North Mountain Avenue, Tucson, AZ 85721, USA. pak@email.arizona.edu
Yu
Fuqu
F
Shahangian
Arash
A
Cheng
Genhong
G
Sun
Ren
R
Ho
Chih-Ming
CM
D000465:Algorithms; D000818:Animals; D002460:Cell Line; D002468:Cell Physiological Phenomena / Q000187:drug effects*; D016207:Cytokines / Q000494:pharmacology; D004338:Drug Combinations; D006801:Humans; D051379:Mice; D016328:NF-kappa B / Q000378:metabolism; D004364:Pharmaceutical Preparations; D012680:Sensitivity and Specificity; D013269:Stochastic Processes
D016207:Cytokines; D004338:Drug Combinations; D016328:NF-kappa B; D004364:Pharmaceutical Preparations