Figure 2

The identifiability analysis module. This module determines, classifies and solves (if found) non-identifiable parameters. The issue of non-identifiability is attacked two fold, directly via a ranking of the parameters and identification of both correlation(s) and non-linear functional relationship(s) between parameters, and indirectly via the generation of the informed prior. This detailed schema highlights the data driven nature of the identifiability analysis via the multiple interconnections between the IA and the parameter estimation module.