Optimization of Low Dose Metronomic Therapy based on Pharmacological Parameters ?

摘要

Therapeutic optimization is a promising direction of computer aided medicine. Optimization of chemotherapy based on mathematical models can result in lower doses, fewer side effects, a smaller chance of acquired drug resistance and more efficient personification. We explore model-based chemotherapy optimization for high frequency low dose therapies with impulsive inputs. We keep the drug level over a specified value using the minimal value of injection doses. We generate therapy for population mean parameters acquired from identification based on mice experiments. We carry out in silico trials based on the results of the individual fits from the identification process and test the therapy generated for the population mean parameters. The results show that therapy optimization based on population mean parameters can be used to generate therapy for the individuals and results in a solution close to the optimal one without using specific knowledge about the individual.