Assessing the role of model choice in parameter identifiability of cancer treatment efficacy DOI Creative Commons

Nadine Kuehle Genannt Botmann,

Hana M. Dobrovolny

Frontiers in Applied Mathematics and Statistics, Год журнала: 2025, Номер 11

Опубликована: Март 24, 2025

Several mathematical models are commonly used to describe cancer growth dynamics. Fitting of these experimental data has not yet determined which particular model best describes growth. Unfortunately, choice is known drastically alter the predictions both future tumor and effectiveness applied treatment. Since there growing interest in using help predict chemotherapy, we need determine if affects estimates chemotherapy efficacy. Here, simulate an vitro study by creating synthetic treatment each seven fit sets other (“wrong”) models. We estimate ε max (the maximum efficacy drug) IC 50 drug concentration at half effect achieved) effort whether use incorrect changes parameters. find that largely weakly practically identifiable no matter generate or data. The more likely be identifiable, but sensitive model, showing poor identifiability when Bertalanffy either

Язык: Английский

Assessing the role of model choice in parameter identifiability of cancer treatment efficacy DOI Creative Commons

Nadine Kuehle Genannt Botmann,

Hana M. Dobrovolny

Frontiers in Applied Mathematics and Statistics, Год журнала: 2025, Номер 11

Опубликована: Март 24, 2025

Several mathematical models are commonly used to describe cancer growth dynamics. Fitting of these experimental data has not yet determined which particular model best describes growth. Unfortunately, choice is known drastically alter the predictions both future tumor and effectiveness applied treatment. Since there growing interest in using help predict chemotherapy, we need determine if affects estimates chemotherapy efficacy. Here, simulate an vitro study by creating synthetic treatment each seven fit sets other (“wrong”) models. We estimate ε max (the maximum efficacy drug) IC 50 drug concentration at half effect achieved) effort whether use incorrect changes parameters. find that largely weakly practically identifiable no matter generate or data. The more likely be identifiable, but sensitive model, showing poor identifiability when Bertalanffy either

Язык: Английский

Процитировано

0