Literature DB >> 21129386

Optimal control for selected cancer chemotherapy ODE models: a view on the potential of optimal schedules and choice of objective function.

Michael Engelhart1, Dirk Lebiedz, Sebastian Sager.   

Abstract

In this article, four different mathematical models of chemotherapy from the literature are investigated with respect to optimal control of drug treatment schedules. The various models are based on two different sets of ordinary differential equations and contain either chemotherapy, immunotherapy, anti-angiogenic therapy or combinations of these. Optimal control problem formulations based on these models are proposed, discussed and compared. For different parameter sets, scenarios, and objective functions optimal control problems are solved numerically with Bock's direct multiple shooting method. In particular, we show that an optimally controlled therapy can be the reason for the difference between a growing and a totally vanishing tumor in comparison to standard treatment schemes and untreated or wrongly treated tumors. Furthermore, we compare different objective functions. Eventually, we propose an optimization-driven indicator for the potential gain of optimal controls. Based on this indicator, we show that there is a high potential for optimization of chemotherapy schedules, although the currently available models are not yet appropriate for transferring the optimal therapies into medical practice due to patient-, cancer-, and therapy-specific components.
© 2010 Elsevier Inc. All rights reserved.

Entities:  

Mesh:

Substances:

Year:  2010        PMID: 21129386     DOI: 10.1016/j.mbs.2010.11.007

Source DB:  PubMed          Journal:  Math Biosci        ISSN: 0025-5564            Impact factor:   2.144


  11 in total

1.  Evaluating optimal therapy robustness by virtual expansion of a sample population, with a case study in cancer immunotherapy.

Authors:  Syndi Barish; Michael F Ochs; Eduardo D Sontag; Jana L Gevertz
Journal:  Proc Natl Acad Sci U S A       Date:  2017-07-17       Impact factor: 11.205

2.  Opportunities for improving cancer treatment using systems biology.

Authors:  Jason I Griffiths; Adam L Cohen; Veronica Jones; Ravi Salgia; Jeffrey T Chang; Andrea H Bild
Journal:  Curr Opin Syst Biol       Date:  2019-11-27

3.  Cancer treatment as a game: integrating evolutionary game theory into the optimal control of chemotherapy.

Authors:  Paul A Orlando; Robert A Gatenby; Joel S Brown
Journal:  Phys Biol       Date:  2012-11-29       Impact factor: 2.583

4.  Dynamic optimization of distributed biological systems using robust and efficient numerical techniques.

Authors:  Carlos Vilas; Eva Balsa-Canto; Maria-Sonia G García; Julio R Banga; Antonio A Alonso
Journal:  BMC Syst Biol       Date:  2012-07-02

5.  Comparison of simple models of periodic protocols for combined anticancer therapy.

Authors:  Marzena Dołbniak; Andrzej Swierniak
Journal:  Comput Math Methods Med       Date:  2013-04-07       Impact factor: 2.238

6.  Optimal treatment strategy for a tumor model under immune suppression.

Authors:  Kwang Su Kim; Giphil Cho; Il Hyo Jung
Journal:  Comput Math Methods Med       Date:  2014-07-23       Impact factor: 2.238

7.  A matter of timing: identifying significant multi-dose radiotherapy improvements by numerical simulation and genetic algorithm search.

Authors:  Simon D Angus; Monika Joanna Piotrowska
Journal:  PLoS One       Date:  2014-12-02       Impact factor: 3.240

8.  Dose Titration Algorithm Tuning (DTAT) should supersede 'the' Maximum Tolerated Dose (MTD) in oncology dose-finding trials.

Authors:  David C Norris
Journal:  F1000Res       Date:  2017-02-07

9.  Optimal dynamic control approach in a multi-objective therapeutic scenario: Application to drug delivery in the treatment of prostate cancer.

Authors:  Itziar Irurzun-Arana; Alvaro Janda; Sergio Ardanza-Trevijano; Iñaki F Trocóniz
Journal:  PLoS Comput Biol       Date:  2018-04-19       Impact factor: 4.475

Review 10.  Optimal Control Theory for Personalized Therapeutic Regimens in Oncology: Background, History, Challenges, and Opportunities.

Authors:  Angela M Jarrett; Danial Faghihi; David A Hormuth Ii; Ernesto A B F Lima; John Virostko; George Biros; Debra Patt; Thomas E Yankeelov
Journal:  J Clin Med       Date:  2020-05-02       Impact factor: 4.241

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.