Modern medicine likes certainty. A diagnosis. A symptom. A number that crosses a line and justifies action. Sir Peter Donnelly, founder and CEO Genomics, a genomic medicine company, is interested in what happens long before any of that.

In his view, some of the most important indicators about your future health are already present, shaping probabilities rather than defining outcomes. Heart disease. Diabetes. Breast and prostate cancer. They are risks, unevenly distributed, mathematically knowable yet, until recently, largely unmeasurable at an individual level.

Speaking to Unfiltered at HLTH Europe in Amsterdam, Donnelly has spent decades building the tools that make those risks legible. Genetics has always mattered, he says. What has changed is that we can now quantify how much. Not in broad population terms, but person by person. Some people, for example, are dozens of times more likely than others to develop specific diseases. 

Health systems, however, still behave as though prevention begins once symptoms appear. Ten minute appointments. Risk models built from averages. A focus on treating illness rather than anticipating it. 

Donnelly’s work challenges that approach. He talks about adding an important layer of information to decisions doctors already make, and giving individuals the chance to move from passive to active participants in their own health trajectories.

Prevention is widely praised and rarely funded. Health systems talk about moving upstream while remaining structurally anchored downstream. Even when the science works, the pathways to use it often do not. Donnelly’s argument is simple; we are already living in an era where risk can be measured with unprecedented accuracy. The question is whether healthcare is prepared to be proactive about probabilities rather than waiting for proof in the form of disease.

What are the recent breakthroughs that you have made with the product that you think are most interesting?

We recently announced a new product in the UK. We already have a product in the US, which is about capturing and measuring the genetic component of risk for all of the common diseases.

It turns out that for heart disease, diabetes, breast or prostate cancer, a major factor of risk for individuals is their genetics. We now have a really good way of measuring that and quantifying that.

We spent ten years developing those algorithms. So our product gets a saliva sample from individuals. They can provide that at home. It does the genetics. We run the analysis and we feed results back in the UK product to their doctors, who then have a much better informed conversation with their patient, based on much better information about their risk for diseases, for heart disease, diabetes, breast cancer for women, and prostate cancer.

Can you put that in some sort of context about how big a step forward that is, as far as you’re concerned?

We’ve known for many years that genetics is a major risk factor for all of the common diseases, but it’s only now that we’ve been able to measure and quantify that, and it turns out to matter a lot.

Some people are 30 times more likely than others to develop diabetes because of their genetic risk. Some men are 40 times more likely than others to develop prostate cancer because of their genetics. And even for diseases like heart disease or cardiovascular disease, where we know a lot of other risk factors like blood pressure and BMI and cholesterol, genetics is a big part of that risk.

For a man between 40 and 55, the genetic component of risk is as important as all of those clinical risk factors put together.

Can you paint a picture of a case study about the potential benefit that this discovery, this breakthrough, might actually offer for an individual?

There are many diseases where doctors already estimate the risk for their patients. Cardiovascular disease and heart disease and stroke is one example. They do that by combining blood pressure, BMI, cholesterol level, and so on, in an algorithm.

What we enable them to do is to add in the genetic component of risk. So they get a much more precise understanding of risk for that patient. That will help them give recommendations directly to the patient, but it will also help them give the patient advice about things they can do to reduce their risk.

And then stepping back a level, as we expand to many more diseases, we’re all going to be at high risk for two or three diseases because of our genetics. We just have no idea which ones they are, and neither do our doctors. It’s actually not very related to family history, for example.

So as individuals, this gives us a chance to learn where our risks are, learn what we can do about it, and so we can become copilots in our health journey rather than, as we are currently, just passengers.

What potentially lies down the track as far as you’re concerned? 

I think these kinds of approaches will change the way we do prevention. Many, many people have argued, and they’re absolutely right, that health systems need to move upstream to get better at preventing disease, rather than waiting for people who are really sick and treating them.

This is going to be a game changer. It will transform our ability to get a very precise understanding of risks for each individual, so health systems can get them into the right screening programs or prevention programmes or treatment programs at the right time. And as individuals, we know what we can do to reduce our risks.

What do you think is holding us back from moving even further towards a preventative approach to health?

I think there are always challenges with new technologies. Health systems are understandably conservative, and a lot of that makes sense. I think also, although health systems all talk about prevention, many of them don’t have budgets for it. They don’t have a person in charge of prevention. So this gives them a way of operationalising that to make a real difference. 

If you had levels of control that are way beyond your imagination, and you could just go in and change the system, what would you alter?

I would make this available initially to people in middle age, from their 40s upwards, and then plumb that into the pathways we have with healthcare systems. They’re already there. We can just do them much better.

And in parallel, give people the information so that they can manage their risk and they can do the things to reduce their risk, as well as taking advantage of what health systems offer.

And what don’t we know at the moment? What do you wish that we did have an awareness of?

At the moment, we’re really good at using this technology for prevention, and that’s where it’ll first have an impact. But over time, we’ll use genetics much more broadly.

There’ll be algorithms that will help a doctor choose the right medication when they have a sick patient. For one person, this drug might be better than that drug because of their genetics. That’s why, in most cases, we don’t have enough data yet to develop those algorithms. There are some examples where we can.

And then beyond that, we’ll go to a world where doctors will use this kind of information to decide what’s the right intervention for a patient. What I’d love is more data so we can develop the algorithms to be able to do that. But that will come in time.

You’re obviously in a commercial enterprise. How have you found building a business? What’s that process been like?

Building a business has been a really interesting journey. I was an academic all my professional career. So as I joked with my colleagues, although they may not find it very funny, I’ve never even worked in a company. And now I run one.

There are lots of new challenges, but lots of opportunities. If you’re founding a business, you need to have a real passion and a real clarity of vision, because a lot of it is amazing, but there are really tough times as well. You need that drive and vision to get through the tough times. Most importantly, you need a fantastic team, and I’m very lucky in that.

What’s the biggest life lesson it’s taught you so far?

I think one of the biggest things I’ve learned is it’s never too early to think about what the product will be and how you’ll commercialise it.

We spent a lot of time very successfully developing algorithms, but thought about the commercial side a bit later than we should have. We’re now at a very good place. And the difference that a team of really, really excited people around you makes is phenomenal.

What’s it like to grow a business in the UK at the moment?

I think there are many positive things about growing a business in the UK. We have very good and supportive UK investors. We also have investors who are among the top life sciences businesses in the US.

The National Health Service in the UK is a potential opportunity because of the cradle-to-grave system with, in principle, linked records. They’re also, at times, slower than one would hope to adopt innovation.

So there are many positives. But as a company, we think globally. We have a lot of our income currently coming from the US. We have tests available in the US. This launch of our UK product is an important step for us in the UK.

Do you think the UK could learn anything from the US, where the integration between research and the commercial world is more established?

I think there are real pockets of strength in the UK. Oxford and Cambridge and London are definitely up there with some of the best US universities in terms of the infrastructure and the funding for startups.

Many other UK universities are now building really interesting infrastructure support and financial support for startups.

It’s still more natural for students and academics to think entrepreneurially in the US, but that’s growing in the UK in a really positive way. It’s very different now from five or ten years ago.

Sir Peter Donnelly was speaking at HLTH Europe in Amsterdam. For more in Genomics, click here.