Computationally predicting the metabolic fates of drugs is a very complex task which is owed not only to the huge and diverse biochemical network in the living cell, but also to the majority of in vivo transformations that occur through the action of hepatocytes and gastro-intestinal micro-flora. Thus, xenobiotics are metabolised by more than a single cell type. However, the prediction of metabolic fates is definitely a problem worth solving since it would allow facilitate the development of drugs in a way less relying on animal testing. As a first step in this direction, PharmBiosim is being developed, a biosimulation tool which is based on substantial data reduction and on attributing metabolic fates of drug molecules to functional groups and substituents. This approach works with yeast as a model organism and is restricted to drugs that are mainly transformed by enzymes of the central metabolism, especially sugar metabolism. The reason for the latter is that the qualitative functioning of the involved biochemistry is very similar in diverse cell types involved in drug metabolism. Further it allows for using glycolytic oscillations as a tool to quantify interactions of a drug with this metabolic pathway.