Mathematical Modeling in Immunotherapy of Cancer: Personalizing Clinical Trials

Mathematical modeling in immunotherapy of cancer: personalizing clinical trials.

Personalizing Androgen Suppression for Prostate Cancer Using Mathematical Modeling

Using a dataset of 150 patients treated with intermittent androgen suppression (IAS) through a fixed treatment schedule, we retrospectively designed a personalized treatment schedule mathematically for each patient. We estimated 100 sets of parameter values for each patient by randomly resampling each patient's time points to take into account the uncertainty for observations of prostate specif...

Personalizing immunotherapy

Despite great expectations and research efforts, anticancer immunotherapy has not yet become a definitive cure. Perhaps, this is because past reductionist approaches were too simplistic for the patient-specific complex system of co-evolving tumor cells and host immunity. Recent efforts based on a systems-based approach promise improved clinical outcomes engendered by a dynamic modification of p...

Immunotherapy of Cancer

This article has no abstract.

Predicting analysis times in randomized clinical trials with cancer immunotherapy

BACKGROUND A new class of immuno-oncology agents has recently been shown to induce long-term survival in a proportion of treated patients. This phenomenon poses unique challenges for the prediction of analysis time in event-driven studies. If the phenomenon of long-term survival is not accounted for properly, the accuracy of the prediction based on the existing methods may be substantially comp...