title: Mathematical models for absorption and efficacy of ovarian cancer treatments.
abstract: The creation of personal and individualized anti-cancer treatments has been a major goal in the progression of cancer discovery as evident by the continuous research efforts in genetics and population based PK/PD studies. In this paper we use our clinical decision support tool, called ChemoDSS, to evaluate the effectiveness of three treatments recommended by the NCCN guidelines for ovarian cancer using pre-clinical data from the literature. In particular, we analyze the treatments of PC (i.e., Paclitaxel and Cispaltin), DC (i.e., Docetaxel and Carboplatin), and PBC (i.e., Paclitaxel, Bevacizumab, and Carboplatin). Our in silico analysis of the ovarian cancer treatments shows that PC was the most effective regimen for treating ovarian cancer compared to DC and PBC, which is consistent with literature findings. We demonstrate that we can successfully evaluate the effectiveness of the selected ovarian cancer treatment regimens using ChemoDSS.
authors.forename: Jianmin
authors.initials: J
authors.lastname: Zou
authors.forename: Stephen
authors.initials: S
authors.lastname: Gundry
authors.forename: Emir
authors.initials: E
authors.lastname: Ganic
authors.forename: M Ümit
authors.initials: MÜ
authors.lastname: Uyar
mesh_terms: D065567:Absorption, Physiological; D000818:Animals; D000970:Antineoplastic Agents / Q000493:pharmacokinetics / Q000627:therapeutic use*; D000971:Antineoplastic Combined Chemotherapy Protocols / Q000493:pharmacokinetics / Q000627:therapeutic use*; D003198:Computer Simulation; D020000:Decision Support Systems, Clinical; D004195:Disease Models, Animal; D005260:Female; D006801:Humans; D051379:Mice; D008954:Models, Biological; D010051:Ovarian Neoplasms / Q000188:drug therapy*; D012984:Software; D016896:Treatment Outcome; D014584:User-Computer Interface
chemical_list: D000970:Antineoplastic Agents