Bioinformatics and computationally based techniques are now experiencing increased attention as a means of improving the costly and time consuming drug development process. Recently, drug repositioning has been suggested as an interim way of harnessing existing drugs to different diseases or medical conditions than the original target. The numerous online databases of chemical, protein interactions, side-effects, drug mechanisms and drug toxicology information make drug repurposing a suitable application area for computational intelligence. Thus in-silico analysis can be used as a useful first stage to screen potential candidate drugs for possible redeployment. We hypothesize that the side-effects of the current Alzheimer’s drugs can be used to screen the SIDER (side-effects) database for potential drug candidates with similar side-effects, that is to say they are probably affecting the same protein targets. Thus, a previously harmful situation has been turned into a mechanism for drug re-positioning. Our system uses complex graph network techniques to analyze drugs with known side effects and compares the proteins involved in these side-effects with proteins known to be identified with other diseases. Our intention is to find potential candidates for treating Alzheimer's disease.