Appropriate drug prescription for an increasingly ageing and multi-morbid population can be a challenge for general practitioners. This study uses unsupervised learning methods to identify different types of patient profiles which could inform policymakers and regulators about patterns of drug use, and identify specific clusters of users with unknown drug effects (risk and benefit). Hard and soft clustering methods are proposed to detect patterns of medication use by patients and to estimate ...