The identification of sub-populations of patients with similar characteristics, called patient subtyping, is important for realizing the goals of Precision Medicine. Accurate subtyping is crucial for tailoring therapeutic strategies that can potentially lead to reduced mortality and morbidity. Model-based clustering, such as Gaussian mixture models, provides a principled and interpretable methodology that is widely used to identify subtypes. However, they impose identical marginal distributions on each variable, such assumptions restrict their modeling flexibility and deteriorates clustering performance.