Clinical validation and integration.

The ability to transfer the technology to a clinical or research setting has often been the stumbling block for health technology projects.

An up to date knowledge of the latest clinical guidelines and actual practise means your project will have an authority which sets it apart from others when it comes to pitching your project against other health tech competitors.

For investors faced with choosing between several projects, an international perspective, years of varied clinical experience combined with a sharp mind mean that I sort the wheat from the chaff. Whether leading a trauma team to save a severely injured patient life combining all the skill sets available in the room (nurses, anaesthetists, surgeons, radiologists, and porters amongst others) or setting up a solo clinic in the Atlas mountains, working out what works in that context has to be a well considered decision under great pressure. Taking into account human and material resources, setting, required outcome now and further down the line, I also need to know my own personal abilities and where to look for any skills I don’t have yet. Being part of a team and bringing out the best of everyone is what sets me aside from other external consultants.

Big data and innovation.

Any AI project in health now has the potential to harvest big data. Knowing what and how to use that big data needs industry specific knowledge. Research and pharmacological applications are ever changing and having current clinical knowledge is a must in order to be first in line for new opportunities. Make sure your product is exploited in every possible way to get maximum yield. You will be pleasantly surprised by the applications and uses which you have not yet discovered but which an experienced clinician can identify.