TY - JOUR
T1 - Mathematical modeling in cancer drug discovery
AU - Wang, Zhihui
AU - Deisboeck, Thomas S.
N1 - Funding Information:
This work has been supported in part by the Harvard-MIT (HST) Athinoula A. Martinos Center for Biomedical Imaging and the Department of Radiology at Massachusetts General Hospital .
PY - 2014/1/1
Y1 - 2014/1/1
N2 - Mathematical models have the potential to help discover new therapeutic targets and treatment strategies. In this review, we discuss how the latest developments in mathematical modeling can provide useful context for the rational design, validation and prioritization of novel cancer drug targets and their combinations. We give special attention to two modeling approaches: network-based modeling and multiscale modeling, because they have begun to show promise in facilitating the process of effective cancer drug discovery. Both modeling approaches are integrated with a variety of experimental methods to ensure proper parameterization and to maximize their predictive value. We also discuss several challenges faced in modeling-based drug discovery.
AB - Mathematical models have the potential to help discover new therapeutic targets and treatment strategies. In this review, we discuss how the latest developments in mathematical modeling can provide useful context for the rational design, validation and prioritization of novel cancer drug targets and their combinations. We give special attention to two modeling approaches: network-based modeling and multiscale modeling, because they have begun to show promise in facilitating the process of effective cancer drug discovery. Both modeling approaches are integrated with a variety of experimental methods to ensure proper parameterization and to maximize their predictive value. We also discuss several challenges faced in modeling-based drug discovery.
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U2 - 10.1016/j.drudis.2013.06.015
DO - 10.1016/j.drudis.2013.06.015
M3 - Review article
C2 - 23831857
AN - SCOPUS:84895922732
SN - 1359-6446
VL - 19
SP - 145
EP - 150
JO - Drug Discovery Today
JF - Drug Discovery Today
IS - 2
ER -