title: Model predictive control for optimally scheduling intermittent androgen suppression of prostate cancer.
abstract: Mathematical modeling of prostate cancer under intermittent androgen suppression revealed that we may be able to delay relapse by optimally scheduling the hormone therapy for each patient. However, our previous study showed the difficulty of the scheduling by minimizing the maximal tumor growth rate because the transient dynamics is also important and can help to delay the relapse for a finite time. Here, we propose to use model predictive control for scheduling intermittent androgen suppression. We find that model predictive control tends to delay the relapse of prostate specific antigen more than the method with minimizing the maximal tumor growth rate. Therefore, model predictive control is a promising approach for practically applying the mathematical model to optimally schedule intermittent androgen suppression.
authors.affiliation: Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan. Electronic address: yoshito@sat.t.u-tokyo.ac.jp.
authors.forename: Yoshito
authors.initials: Y
authors.lastname: Hirata
authors.affiliation: Graduate School of Informatics, Kyoto University, Kyoto 611-0011, Japan.
authors.forename: Shun-ichi
authors.initials: S
authors.lastname: Azuma
authors.affiliation: Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan.
authors.forename: Kazuyuki
authors.initials: K
authors.lastname: Aihara
mesh_terms: D000726:Androgen Antagonists / Q000627:therapeutic use*; D006801:Humans; D008297:Male; D008954:Models, Biological; D008962:Models, Theoretical; D011471:Prostatic Neoplasms / Q000188:drug therapy*
chemical_list: D000726:Androgen Antagonists
keywords: Delaying relapse; Intermittent androgen suppression; Model predictive control; Optimal schedule; Personalized medicine; Prostate cancer