1. A model system, wherein the model predicts, without dosing, the post-dose response of an individual where the response is dependent on the individual's metabolic phenotype, the model system comprising: a) pre-dose data of a plurality of subjects or samples thereof before dosing with a dosing substance; b) post-dose data of the plurality of subjects or samples thereof after dosing with the dosing substance; and c) a processor that identifies and correlates inter-subject variation in the pre-dose data with inter-subject variation in the post-dose data using a pattern recognition (PR) technique, wherein the inter-subject variation in the post-dose data corresponds to different responses of the subjects to the dosed substance, thereby producing a pre-to-post-dose predictive model, wherein the processor applies the pre-to-post-dose predictive model to the individual's pre-dose data and classifies the individual's post-dose response, without dosing of the individual; wherein the pre- and/or post-dose data comprise chemical composition data and/or physical parameter data of samples and/or subjects; wherein the pre-to-post-dose predictive model consists of one or more mathematical equations defining the relationship between pre-dose and post-dose data.