SYSTEM AND METHOD FOR MULTI-DIMENSIONAL PHYSICIAN-SPECIFIC DATA MINING FOR PHARMACEUTICAL SALES AND MARKETING

The present invention relates to a system and method for electronic and algorithmic data mining of an individual physician's prescribing history to determine the approximate distribution of diseases within their practice population for optimizing pharmaceutical sales and marketing. Rapid and large-scale determination of specific clinical safety and efficacy attributes of a marketed drug which are most pertinent and relevant to a given physician, when compared to a competitor's drug, are defined and tabularized. Major clinical characteristics taken into account include a drug's safety, efficacy, cost, dosing convenience, formulary insurance coverage, side effect profiles, and FDA approval for the intended use. A symbolic representation of knowledge is employed in which the marketed drug and each competitor's drug are compared algorithmically against each other with a scoring system that is based upon machine analysis of each major clinical characteristic. The score is further refined according to the number and severity of safety interactions which are relevant to the comparison, and also based upon predicted prevalence of such interactions within a specific physician's practice.