This paper is concerned with the utilization of deterministically modelled chemical reaction networks for implementation (feed-forward) neural networks. We develop a general mathematical framework and prove that ordinary differential equations (ODEs) associated certain network implementations have desirable properties including (i) existence unique positive fixed points are smooth in parameters...