Evaluating optimal therapy robustness by virtual expansion of a sample population, with a case study in cancer immunotherapy

• Published in: Proceedings of the National Academy of Sciences - PNAS Vol. 114; no. 31; pp. E6277 - E6286
• Main Authors: Barish, Syndi, Ochs, Michael F., Sontag, Eduardo D., Gevertz, Jana L.
• Format: Journal Article
• Language: English
• Published: United States National Academy of Sciences 01.08.2017
• Series: PNAS Plus
• Subjects: Biological Sciences; Cancer; Cancer immunotherapy; Dendritic cells; Experimental data; Immunostimulation; Immunotherapy; Mathematical analysis; Mathematical models; Melanoma; Nonparametric statistics; Oncolysis; Optimization; Physical Sciences; PNAS Plus; Population (statistical); Population studies; Robustness (mathematics); Scheduling; Statistical analysis; Temporal variations; Therapy; Vaccines; Viruses; mathematical modeling; cancer treatment; robust therapies; virotherapy; immunotherapy

Cancer is a highly heterogeneous disease, exhibiting spatial and temporal variations that pose challenges for designing robust therapies. Here, we propose the VEPART (Virtual Expansion of Populations for Analyzing Robustness of Therapies) technique as a platform that integrates experimental data, ma...