These models will provide functional understanding of complex nonlinear pathophysiological systems and their interactions, will allow scientists to explore system dynamics and biological hypotheses, will yield insight into responses to different pharmacological approaches to modulating biological systems, and will provide mechanistic insights to inform Eisai's R&D decisions (for example FIH translation, dose selection, candidate selection, selection of target population, and combination strategies). Deep knowledge of the principles and theoretical aspects of applied mathematical modeling, including numerical methods, ordinary differential equations (ODEs), partial differential equations (PDEs), parameter estimation/optimization, and how these tools can be applied in the development of complex biochemical models.