PT  - JOURNAL ARTICLE
AU  - Ronan Duchesne
AU  - Anissa Guillemin
AU  - Olivier Gandrillon
AU  - Fabien Crauste
TI  - Practical Identifiability in the Frame of Nonlinear Mixed Effects Models: the Example of the <em>in vitro</em> Erythropoiesis
AID  - 10.1101/2021.03.01.433388
DP  - 2021 Jan 01
TA  - bioRxiv
PG  - 2021.03.01.433388
4099  - http://biorxiv.org/content/early/2021/03/01/2021.03.01.433388.short
4100  - http://biorxiv.org/content/early/2021/03/01/2021.03.01.433388.full
AB  - Nonlinear mixed effects models provide a way to mathematically describe experimental data involving a lot of inter-individual heterogeneity. In order to assess their practical identifiability and estimate confidence intervals for their parameters, most mixed effects modelling programs use the Fisher Information Matrix. However, in complex nonlinear models, this approach can mask practical unidentifiabilities. Herein we rather propose a multistart approach, and use it to simplify our model by reducing the number of its parameters, in order to make it identifiable. Our model describes several cell populations involved in the in vitro differentiation of chicken erythroid progenitors grown in the same environment. Inter-individual variability observed in cell population counts is explained by variations of the differentiation and proliferation rates between replicates of the experiment. Alternatively, we test a model with varying initial condition. We conclude by relating experimental variability to precise and identifiable variations between the replicates of the experiment of some model parameters.Competing Interest StatementThe authors have declared no competing interest.