This is an expository note on large deviations, Hamilton-Jacobi-Bellman (HJB) equations, and the role of the Freidlin-Wentzell quasipotential in Chemical Reaction Networks (CRNs). The note was motivated by observations which identified Lyapunov functions for deterministic descriptions of CRNs by taking appropriate scaling limits of invariant distributions for the corresponding stochastic dynamics. We explain how this is a special case of a classical theory due to Freidlin and Wentzell. We also show that this Lyapunov function is a solution to the HJB partial differential equation if and only if the network is "complex-balanced". The target audience are researchers in the CRN community who are familiar with the Markov process description of CRNs, but do not have the time to invest in learning the technical machinery of large deviations. We conclude by exploring some possible relationships with Kähler geometry which suggest an interesting and unexplored research direction.