Architecting the future of predictive genomics – a blueprint for health economies and systems

Mark Bailey, CEO, Zetta Genomics

This blog is one in a new series from Zetta Genomics CEO, Mark Bailley, on the opportunities of predictive genomics – and the challenges we need to overcome to realise them.

We are in a golden age of medical discovery. As research accelerates, we are seeing an explosion in novel drugs, treatments and therapies. Technology is transforming research environments and clinical settings. Today, we can treat conditions that we could only have dreamed of a generation ago. 

Yet, this golden age threatens to levy too high a price. Health economies and health systems are already buckling under the strain. We are in danger of getting to a place where healthcare is for a wealthy few – where more effective health technologies lead to less effective health outcomes. 

To save our health economies we need to rethink our health systems: to pay for the healthcare we have to, and not the healthcare we don’t. Simply, we must unlock the power of predictive medicine – and genomics is the key. 

The challenges facing health economies and systems 

Health costs are spiralling. If we look at the world’s largest healthcare economy – the US – we can see rising costs over time. In 1960, national health spending represented just 5% of GDP, but by 2021 it had hit 18% (around US$4 trillion) and is still rising.  

Globally, health now costs around US$9 trillion a year: almost twice what the world spends on education and 4.5 times defence spending. If we paid out a dollar a second, it would take an astonishing 288,000 years to burn through the world’s annual health budget. 

Improved health provision and other factors mean that people are living for longer – which is hugely encouraging. Yet, the burden on the economically active to pay for a growing and largely economically inactive older population becomes ever greater. In 2020, the world’s over-60s outnumbered its under-fives. 

Most of this spending is funnelled into reactive care – curing illnesses or conditions, and returning patients to a healthy state. Zeroing in on the UK health system, we can see the scale of the problem.  

In 2018, healthcare accounted for 10% of UK GDP. The government spent around £166 billion, with 64% of this focused on curative and rehabilitative (largely reactive) care, while just 5% was spent trying to prevent illness. In 2021, healthcare claimed 12% of UK GDP. Government spending leapt to an estimated £229 billion and, if we assume similar percentages to 2018, reactive care claimed over £140 billion, while preventative care just £11 billion. 

This inability to predict and prevent disease impacts the wider economy. 2023 research suggests that ill health in working-age people costs the UK economy £150 billion a year. Add £70 billion in lost tax revenues and increased social security spending and we get to £220 billion. I’ll let that sink in: potentially preventable working age illness costs the UK almost as much as a second NHS every year.  

It’s easy to forget, when talking about such vast sums, the human cost: millions of people suffering from illnesses, conditions and enduring often debilitating treatments that could have been prevented.  

We are moving to the point, in the UK and elsewhere, where state funded health systems won’t be able to levy sufficient tax revenues to pay for care without crippling their economies. Private reactive systems will fare no better as premiums rise beyond most customers’ ability to pay.  

The opportunities of predictive healthcare 

Now, imagine a new future: where we can predict susceptibility to conditions from birth; where decisions on diet, exercise and even career choice, are informed by their actual health impacts; where early interventions spare people from conditions in later life; where our health records don’t just tell us what has happened to us, but what will.  

Genomics has long promised this kind of predictive capability. If our bodies are a biological machine, our genome is a unique and detailed instruction manual. With this manual, we can optimise maintenance while also identifying known ‘faults’ with our specific machine – such as mutations in BRCA 1 and 2 genes – and take action to limit, or even prevent, harm. 

While genomics is currently focused on some cancers and rare diseases, our understanding grows daily. In the UK, for example, research has just linked over 500 genes to lung function. As genomic data uncovers more of the mutations that cause conditions, we will be able to predict an increasing number of them. It means that we can prevent illness in millions of people and transform the economics of health. 

The opportunities of predictive research  

Predictive genomic data can also help us to transform the economics of medical and pharmaceutical research.  

Drug development is one of the primary factors driving healthcare costs, with estimates varying between US$300 million and nearly US$3 billion to bring a medicine to market. Clinical trials are a significant cost component, with major investment needed to recruit the large participant populations that deliver statistical precision. 

Now, however, genomic data allows researchers to target recruitment on genomically pre-selected individuals, thus reducing the need for large participant populations. It has the potential to greatly enhance trial efficiency, efficacy and safety – cutting significant costs from drug development. By extension, cheaper and more effective drug development will lead to cheaper, more effective treatments.  

Predictive genomic data can also help to spare people from treatments that will deliver little benefit or even prove dangerous. In the UK, the NHS already selects patients suitable for chemotherapy based on genomic testing. As well as improving patient safety, it cuts costs. 

Healthcare for the many, not just the few 

Now, increasingly high-cost technologies and treatments can be focused precisely where they’re needed. Now, health systems can accurately plan – and afford – effective healthcare delivery. Now, populations can understand how to stay healthier at the individual level. Now, preventable diseases can be avoided. 

Genomic data’s ability to help us predict disease brings health economies, health systems and individuals control. With the predictive genomic data blueprint in place, we can architect a new healthcare future and transform health outcomes for the many, and not just the few.