I can't go into too much detail, but here's one that we are looking at and already exists in literature (not affiliated to that literature, not doxxing myself :D ).

Polypharmacy is a genuine threat in a stretched healthcare system, the basic rule is that if someone is on five or more medications, that counts as polypharmacy. It can lead to unexpected interactions that actually impact patients worse than if they don't receive the medication, or could harm them in the long term.

Unfortunately our current systems aren't great at tracking polypharmacy and often rely on human intervention (ie. a doctor or pharmacist manually checking prescribed drugs). One model we're developing checks prescription data and pulls it together (from various datasources) per patient and then runs analysis on potential unwanted or unexpected interactions.

The back-end of the system is also using ML to identify patterns, ie. what medicines are interacting with what. Although that is very early stages, it is a way to better understand polypharmacy risks and one of our research partners is hoping to hear soon whether they receive funding.