Strategies to Reduce Long-Term Drug Resistance by Considering Effects of Differential Selective Treatments.

Tina Ghodsi Asnaashari, Young Hwan Chang
{"title":"Strategies to Reduce Long-Term Drug Resistance by Considering Effects of Differential Selective Treatments.","authors":"Tina Ghodsi Asnaashari,&nbsp;Young Hwan Chang","doi":"10.1007/978-3-030-91241-3_5","DOIUrl":null,"url":null,"abstract":"<p><p>Despite great advances in modeling and cancer therapy using optimal control theory, tumor heterogeneity and drug resistance are major obstacles in cancer treatments. Since recent biological studies demonstrated the evidence of tumor heterogeneity and assessed potential biological and clinical implications, tumor heterogeneity should be taken into account in the optimal control problem to improve treatment strategies. Here, first we study the effects of two different treatment strategies (i.e., symmetric and asymmetric) in a minimal two-population model to examine the long-term effects of these treatment methods on the system. Second, by considering tumor adaptation to treatment as a factor of the cost function, the optimal treatment strategy is derived. Numerical examples show that optimal treatment decreases tumor burden for the long-term by decreasing rate of tumor adaptation over time.</p>","PeriodicalId":74122,"journal":{"name":"Mathematical and computational oncology : third international symposium, ISMCO 2021, virtual event, October 11-13, 2021 : proceedings. ISMCO (Symposium) (3rd : 2021 : Online)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10280777/pdf/nihms-1907163.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mathematical and computational oncology : third international symposium, ISMCO 2021, virtual event, October 11-13, 2021 : proceedings. ISMCO (Symposium) (3rd : 2021 : Online)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/978-3-030-91241-3_5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Despite great advances in modeling and cancer therapy using optimal control theory, tumor heterogeneity and drug resistance are major obstacles in cancer treatments. Since recent biological studies demonstrated the evidence of tumor heterogeneity and assessed potential biological and clinical implications, tumor heterogeneity should be taken into account in the optimal control problem to improve treatment strategies. Here, first we study the effects of two different treatment strategies (i.e., symmetric and asymmetric) in a minimal two-population model to examine the long-term effects of these treatment methods on the system. Second, by considering tumor adaptation to treatment as a factor of the cost function, the optimal treatment strategy is derived. Numerical examples show that optimal treatment decreases tumor burden for the long-term by decreasing rate of tumor adaptation over time.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
通过考虑不同选择治疗的效果来降低长期耐药的策略。
尽管最优控制理论在建模和癌症治疗方面取得了很大进展,但肿瘤异质性和耐药性是癌症治疗的主要障碍。由于最近的生物学研究证明了肿瘤异质性的证据,并评估了潜在的生物学和临床意义,因此在最优控制问题中应考虑肿瘤异质性,以改进治疗策略。在这里,我们首先在最小双种群模型中研究了两种不同的处理策略(即对称和非对称)的效果,以检验这些处理方法对系统的长期影响。其次,考虑肿瘤对治疗的适应性作为成本函数的一个因素,推导出最优治疗策略。数值算例表明,最优治疗通过降低肿瘤的适应率来降低肿瘤的长期负担。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Strategies to Reduce Long-Term Drug Resistance by Considering Effects of Differential Selective Treatments. Mathematical and Computational Oncology: Third International Symposium, ISMCO 2021, Virtual Event, October 11–13, 2021, Proceedings Mathematical and Computational Oncology: Second International Symposium, ISMCO 2020, San Diego, CA, USA, October 8–10, 2020, Proceedings Mathematical and Computational Oncology: First International Symposium, ISMCO 2019, Lake Tahoe, NV, USA, October 14–16, 2019, Proceedings
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1