Your browser doesn't support javascript.
loading
Tumour growth control: analysis of alternative approaches.
Papa, Federico; Borri, Alessandro; Palumbo, Pasquale.
Afiliação
  • Papa F; CNR-IASI, National Research Council of Italy, Via dei Taurini 19, Rome, Italy. Electronic address: federico.papa@iasi.cnr.it.
  • Borri A; CNR-IASI Biomathematics Laboratory, National Research Council of Italy, L.go A. Gemelli 8, Rome, Italy; Center of Excellence for Research DEWS, University of L'Aquila, Via Vetoio, L'Aquila, Italy. Electronic address: alessandro.borri@iasi.cnr.it.
  • Palumbo P; CNR-IASI, National Research Council of Italy, Via dei Taurini 19, Rome, Italy; Department of Biotechnology and Biosciences, University of Milano-Bicocca, Piazza della Scienza 2, 20126 Milan, Italy. Electronic address: pasquale.palumbo@unimib.it.
J Theor Biol ; 562: 111420, 2023 04 07.
Article em En | MEDLINE | ID: mdl-36736855
In this work we address the problem of tumour growth control by properly exploiting a low-dimensional model that grounds on the Chemical Reaction Network (CRN) formalism. Originally conceived to work both in deterministic and stochastic frameworks, it is shown that, except for the case of very low number of tumour cells, the deterministic approach is appropriate to characterize the system behaviour, especially for control planning purposes. Two alternative control approaches are here investigated. One trivially assumes a constant infusion of external drug administration, the other is designed according to a state-feedback control scheme, with complete or partial knowledge of the state. Pros and cons of both control laws are investigated, showing that the tumour size at the beginning of the therapy plays a role of paramount importance for fixed infusion therapies, whilst only state-feedback laws can eradicate arbitrarily large tumours.
Assuntos
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Modelos Biológicos / Neoplasias Limite: Humans Idioma: En Revista: J Theor Biol Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Modelos Biológicos / Neoplasias Limite: Humans Idioma: En Revista: J Theor Biol Ano de publicação: 2023 Tipo de documento: Article