How to check and improve optimization

The challenge

Parameter optimization of ODE models is challenging because

• there is no analytical solution of the ODEs, thus the objective function (and derivatives) can only be evaluated numerically with limited accuracy
• the objective function depends non-linearly on the parameters
• models might be large, i.e. have many parameters
• the amount of available data and observables is typically restricted which yields non-identifiability
• usually only rough knowledge is available about parameter ranges
• additional numerical challenges like events have to be accounted for

It is therefore essential to ensure that optimization works reliably.

Checks for reliable optimization

Literature

Lessons Learned from Quantitative Dynamical Modeling in Systems Biology