Agent-based modeling in cancer biomedicine: applications and tools for calibration and validation.
Cancer Biol Ther
; 25(1): 2344600, 2024 Dec 31.
Article
em En
| MEDLINE
| ID: mdl-38678381
ABSTRACT
Computational models are not just appealing because they can simulate and predict the development of biological phenomena across multiple spatial and temporal scales, but also because they can integrate information from well-established in vitro and in vivo models and test new hypotheses in cancer biomedicine. Agent-based models and simulations are especially interesting candidates among computational modeling procedures in cancer research due to the capability to, for instance, recapitulate the dynamics of neoplasia and tumor - host interactions. Yet, the absence of methods to validate the consistency of the results across scales can hinder adoption by turning fine-tuned models into black boxes. This review compiles relevant literature that explores strategies to leverage high-fidelity simulations of multi-scale, or multi-level, cancer models with a focus on verification approached as simulation calibration. We consolidate our review with an outline of modern approaches for agent-based models' validation and provide an ambitious outlook toward rigorous and reliable calibration.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Modelos Biológicos
/
Neoplasias
Limite:
Animals
/
Humans
Idioma:
En
Revista:
Cancer Biol Ther
Assunto da revista:
NEOPLASIAS
/
TERAPEUTICA
Ano de publicação:
2024
Tipo de documento:
Article
País de afiliação:
Estados Unidos