  Identification of dynamics underlying biochemical pathways of interest in
oncology is a primary goal in current systems biology. Understanding structures
and interactions that govern the evolution of such systems is believed to be a
cornerstone in this research. Systems theory and systems identification theory
are primary resources for this task since they both provide a self consistent
framework for modelling and manipulating models of dynamical systems that are
best suited for the problem under investigation. We address herein the issue of
obtaining an informative dataset ZN to be used as starting point for
identification of EGFR pathway dynamics. In order to match experimental
identifiability criteria we propose a theoretical framework for input stimulus
design based on dynamical properties of the system under investigation. A
feasible optofluidic design has been designed on the basis of the spectral
properties of the driving inputs that maximize information content after the
theoretical studies.
