  In recent decades, there has been an increase in polypharmacy, the concurrent
administration of multiple drugs per patient. Studies have shown that
polypharmacy is linked to adverse patient outcomes and there is interest in
elucidating the exact causes behind this observation. In this paper, we are
studying the relationship between drug prescriptions, drug-drug interactions
(DDIs) and patient mortality. Our focus is not so much on the number of
prescribed drugs, the typical metric in polypharmacy research, but rather on
the specific combinations of drugs leading to a DDI. To learn the space of
real-world drug combinations, we first assessed the drug prescription landscape
of the UK Biobank, a large patient data registry. We observed distinct drug
constellation patterns driven by the UK Biobank participants' disease status.
We show that these drug prescription clusters matter in terms of the number and
types of expected DDIs, and may possibly explain observed differences in health
outcomes.
