Interaction Analysis of Three Combination Drugs via a Modified Genetic Algorithm

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dc.contributor.authorWan, Wenen
dc.contributor.authorPei, Xin-Yanen
dc.contributor.authorGrant, Stevenen
dc.contributor.authorBirch, Jeffrey B.en
dc.contributor.authorFelthousen, Jessicaen
dc.contributor.authorDai, Yunen
dc.contributor.authorFang, Hong-Binen
dc.contributor.authorTan, Mingen
dc.contributor.authorSun, Shumeien
dc.contributor.departmentStatisticsen
dc.date.accessioned2019-05-08T19:46:20Zen
dc.date.available2019-05-08T19:46:20Zen
dc.date.issued2014en
dc.description.abstractFew articles have been written on analyzing and visualizing three-way interactions between drugs. Although it may be quite straightforward to extend a statistical method from two-drugs to three-drugs, it is hard to visually illustrate which dose regions are synergistic, additive, or antagonistic, due to a four-dimensional (4-D) problem of plot- ting three-drug dose regions plus a response. This problem can be converted and solved by showing some dose regions of our interest in a 3-D, three-drug dose regions. We propose to apply a modified genetic algorithm (MGA) to construct the dose regions of interest after fitting the response surface to the interaction index (II) by a semiparametric method, the model robust regression method (MRR). A case study with three anti-cancer drugs in an in vitro experiment is employed to illustrate how to find the dose regions of interest. For example, suppose researchers are interested in visualizing where the synergistic areas with II ≤ 0:4 are in 3-D. After fitting a MRR model to the calculated II, the MGA procedure is used to collect those feasible points that satisfy the estimated values of II ≤ 0:4. All these feasible points are used to construct the approximate dose regions of interest in a 3-D.en
dc.description.sponsorshipNCI grants CA100866, CA142509, CA167708en
dc.format.extent18 pagesen
dc.format.mimetypeapplication/pdfen
dc.identifier.sourceurlhttps://www.stat.vt.edu/content/dam/stat_vt_edu/graphics-and-pdfs/research-papers/Technical_Reports/TechReport14-4.pdfen
dc.identifier.urihttp://hdl.handle.net/10919/89422en
dc.language.isoenen
dc.publisherVirginia Techen
dc.relation.ispartofseriesTechnical Report No. 14-4en
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectGenetic Algorithm (GA)en
dc.subjectInteraction Index (II)en
dc.subjectModel Robust Regression (MRR)en
dc.subjectSynergismen
dc.subjectThree-drug combinationen
dc.subjectViabilityen
dc.titleInteraction Analysis of Three Combination Drugs via a Modified Genetic Algorithmen
dc.typeTechnical reporten
dc.type.dcmitypeTexten

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