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An increasing number of patients and family members interact online and exchange their experiences with diseases and therapies. The huge amount of online health data represents a rich source of knowledge pharmaceutical companies. The analysis of this data enables the identification of strengths and weaknesses of their drugs. An approach is presented which allows the extraction and analysis of patient experiences with drugs expressed in online reviews by combining methods coming from text mining and data mining. The approach is exemplarily applied to a data set comprising patients' experiences with smoking deterrents. [ABSTRACT FROM PUBLISHER]