Retrieving specific interaction about target connectivity information acquired from WikiPathways allowed us to select combinations for predictions based upon publicly known pathway data about connectivity of gene products that share the same biological course. It is this connectivity that allows this approach to be rooted in accepted biological principles. The project was successful in proposing drug combinations based only on biologically relevant connections from pathway data, and the application of the Loewe mathematical model to conditions outside the model's normal parameters, unique combinations can be identified that are overlooked by the standard Loewe model. What we saw as the networks grew was that as the networks grew bigger, it allowed for more permutations of drug combinations. If the drug targets were too distant from each other, then almost all permutations of the two drug combinations were possible. One way to help combat this is to use directional information about the connectivity between the two targets to keep combinations in the same branch with the assumption that regulation of one of the targets has a downstream effect upon the other target and targeting the processes at different points has the potential to have a greater than standard effect at the drug dosage. The distance between elements cannot grow too large as the possibilities of alternative paths of expression becomes greater.