While colloids are promising building blocks for the self-assembly of materials with novel microstructures, their numerous tunable parameters inhibit brute force searching for appropriate parameter combinations that yield self-assembly of a desired structure. Instead, inverse approaches that invoke a systematic optimization framework can effectively navigate this design space. In this proceeding, we apply one such inverse technique, Relative Entropy Minimization, to discover isotropic pairwise interaction potentials that prompt self-assembly of clusters in silico. The functional form of the pair interaction is chosen to model a mixture of charged colloids and neutral polymers that act as depletants, and the parameters are directly connected to experimentally tunable quantities.