In this paper we present a rule-engine-based framework to support personalized and context-aware OTC medication safety advice. We describe how high-level architectural choices impact the system. We report on our prototype implementation and initial experiments. We also describe a means of representing drug safety rules in an appropriate language for automated decision making and some of the challenges associated with rule authorship.
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