| Literature DB >> 31698614 |
Celia Schacht1, Annabel Meade1, H T Banks1, Heiko Enderling2, Daniel Abate-Daga2.
Abstract
In this effort we explain fundamental formulations for aggregate data inverse problems requiring estimation of probability distribution parameters. We use as a motivating example a class of CAR T-call cancer models in mice. After ascertaining results on model stability and sensitivity with respect to parameters, we carry out first elementary computations on the question how much data is needed for successful estimation of probability distributions.Entities:
Keywords: CAR T-cell therapy ; aggregate data ; cancer model ; design of experiments ; inverse problems
Year: 2019 PMID: 31698614 DOI: 10.3934/mbe.2019365
Source DB: PubMed Journal: Math Biosci Eng ISSN: 1547-1063 Impact factor: 2.080