BACK TO INDEX
Publications of Eduardo D. Sontag jointly with S. Barish
Articles in journal or book chapters
and J.L. Gevertz.
Evaluating optimal therapy robustness by virtual expansion of a sample population, with a case study in cancer immunotherapy.
Proc Natl Acad Sci USA,
This paper proposes a technique that combines experimental data, mathematical modeling, and statistical analyses for identifying optimal treatment protocols that are robust with respect to individual variability. Experimental data from a small sample population is amplified using bootstrapping to obtain a large number of virtual populations that statistically match the expected heterogeneity. Alternative therapies chosen from among a set of clinically-realizable protocols are then compared and scored according to coverage. As proof of concept, the method is used to evaluate a treatment with oncolytic viruses and dendritic cell vaccines in a mouse model of melanoma. The analysis shows that while every scheduling variant of an experimentally-utilized treatment protocol is fragile (non-robust), there is an alternative region of dosing space (lower oncolytic virus dose, higher dendritic cell dose) for which a robust optimal protocol exists.
BACK TO INDEX
This material is presented to ensure timely dissemination of
scholarly and technical work. Copyright and all rights therein
are retained by authors or by other copyright holders.
Last modified: Sun Feb 13 12:55:49 2022
This document was translated from BibTEX by