D. Drexler, Johanna Sápi, A. Szeles, I. Harmati, A. Kovács, L. Kovács
{"title":"Flat control of tumor growth with angiogenic inhibition","authors":"D. Drexler, Johanna Sápi, A. Szeles, I. Harmati, A. Kovács, L. Kovács","doi":"10.1109/SACI.2012.6249998","DOIUrl":null,"url":null,"abstract":"Cancer represents nowadays one of the most destructive and lethal illnesses of our civilization. In the last decades, clinical cancer research shifted towards molecular targeted therapies which have limited side effects in comparison to conventional chemotherapy and radiation therapy. Antiangiogenic therapy is proved to be one of the most promising cancer treatment methods. This paper concerns on the model-based control of tumor growth under angiogenic inhibition. The tumor growth model is nonlinear, augmented with a linear model representing the pharmacokinetics of the applied inhibitor in tumor treatment. The control strategy is based on feedback linearization and path tracking. The result are compared with other, basically linear control strategies which were previously published by our group.","PeriodicalId":293436,"journal":{"name":"2012 7th IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 7th IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SACI.2012.6249998","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 21
Abstract
Cancer represents nowadays one of the most destructive and lethal illnesses of our civilization. In the last decades, clinical cancer research shifted towards molecular targeted therapies which have limited side effects in comparison to conventional chemotherapy and radiation therapy. Antiangiogenic therapy is proved to be one of the most promising cancer treatment methods. This paper concerns on the model-based control of tumor growth under angiogenic inhibition. The tumor growth model is nonlinear, augmented with a linear model representing the pharmacokinetics of the applied inhibitor in tumor treatment. The control strategy is based on feedback linearization and path tracking. The result are compared with other, basically linear control strategies which were previously published by our group.