More Efficient Identifiability Verification in ODE Models by Reducing Non-Identifiability

TL;DR

This paper introduces a method to speed up the process of verifying parameter identifiability in ODE models by removing non-identifiable parameters, enhancing computational efficiency.

Contribution

It proposes a novel algebraic approach to eliminate non-identifiable parameters, improving the speed of global identifiability verification in ODE models.

Findings

Significant performance improvements across multiple computer algebra systems.

Effective elimination of algebraically independent non-identifiable parameters.

Enhanced efficiency in identifiability analysis workflows.

Abstract

Structural global parameter identifiability indicates whether one can determine a parameter's value from given inputs and outputs in the absence of noise. If a given model has parameters for which there may be infinitely many values, such parameters are called non-identifiable. We present a procedure for accelerating a global identifiability query by eliminating algebraically independent non-identifiable parameters. Our proposed approach significantly improves performance across different computer algebra frameworks.