{"title":"Optimal control in therapeutics and epidemiology","authors":"Camille Pouchol, Nastassia Pouradier Duteil","doi":"10.1002/oca.3114","DOIUrl":null,"url":null,"abstract":"<h2> Context</h2>\n<p>Optimal control has become a tool of choice for in silico optimization of drug infusion protocols, as is the case in cancer therapy. The relatively less developed area of optimal control for epidemiology has received considerable attention recently due to the Covid-19 pandemic.</p>\n<p>Though apparently different, these two contexts usually involve models-whether finite-dimensional or infinite dimensional-which come from population dynamics, while considering cost functionals of the same type. Furthermore, they often encounter the same specific difficulties, such as considerable model uncertainty and require ad-hoc techniques to make optimal control strategies implementable (frequency of drug infusions, discrete controls).</p>\n<p>Consequently, optimal control techniques used and developed in the Special Issue share strong similarities in how they tackle control problems arising in therapeutics and epidemiology.</p>","PeriodicalId":501055,"journal":{"name":"Optimal Control Applications and Methods","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Optimal Control Applications and Methods","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/oca.3114","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
Context
Optimal control has become a tool of choice for in silico optimization of drug infusion protocols, as is the case in cancer therapy. The relatively less developed area of optimal control for epidemiology has received considerable attention recently due to the Covid-19 pandemic.
Though apparently different, these two contexts usually involve models-whether finite-dimensional or infinite dimensional-which come from population dynamics, while considering cost functionals of the same type. Furthermore, they often encounter the same specific difficulties, such as considerable model uncertainty and require ad-hoc techniques to make optimal control strategies implementable (frequency of drug infusions, discrete controls).
Consequently, optimal control techniques used and developed in the Special Issue share strong similarities in how they tackle control problems arising in therapeutics and epidemiology.