Can you kind of just talk me briefly through your career, through those big companies and how you developed?

Yeah, so I started in Roche in the U.S. And that was the time when looking into where I knew I wanted to go to industry.

And I found this job ad that had pretty much me described.

And then, well, it became a reality.

And coming into industry from academia, you used to do things on your own and being self-sufficient, if you want.

I started basically being self-sufficient while leveraging the value of, again, collaboration, competencies, and skills that are synergistic to yours.

And something that also was very evident at the beginning for me was identifying a gap and feeling it, but without necessarily being asked to feel it, right? So if there is a problem and I can fix it, I will fix it.

What was the thought process behind

But could you tell me how ValoHealth is different to the rest?

Yes, I think one of the important elements that we have as a company is the platform that connects, as I said, the human central element to the chemistry.

So it's not only because we are accessing human data.

I mean, many companies are accessing human data, but the difference here is that we're able to access not only very broad data, very deep data cohorts.

We have about 20 million data pieces with the very deep phenotyping of the patient through electronic health records, for example, and that is coupled with omics such as genetics or other sorts of omics.

And we are able to triangulate these different elements to let the data paint the patient.

So rather than just relying on what the code is telling you about the disease, we are letting all the different parameters tell you what the patient really has.

How important are partnerships between small and large biotech companies and also the relationships between them and AI providers and academia?