Innovációs szolgáltató bázis létrehozása diagnosztikai, terápiás és kutatási célú
kiberorvosi ren...(2019-1-3-1-KK-2019-00007) Támogató: NKFIH
Mathematical models of tumor growth in response to chemotherapy are crucial for therapy
optimization and outcome. We create a relatively simple tumor growth model describing
the antitumor effect of pegylated liposomal doxorubicin (PLD) validated with real
experimental data obtained in a genetically engineered mouse model of breast cancer.
We use formal reaction kinetics to describe the pathophysiological phenomena using
differential equations, and carry out parametric identification based on experiments
using a mixed-effect model with stochastic approximation expectation maximization.
The model gives a sufficient fit to describe tumor growth and pharmacokinetic data,
and a satisfactory fit for the complex case, i.e., tumor response to chemotherapy.
The results showed that identification of certain subsystems is easy using experimental
data even if it is not specifically designed for identification. However, the identification
of the complex pathophysiological phenomena may require experiments specially designed
for identification purposes. Copyright (C) 2020 The Authors.
