Over the last two years, I’ve been helping medical laboratories to provide genomic testing at scale. In that time, I’ve extended my experience in building and implementing health systems, and added a new string to my bow as a genomic health informatician.
My work is about understanding the problems that laboratories face when it comes to genomic data and assisting each lab to find solutions.
It’s been quite the learning curve, but so rewarding. Here are the top five things I’ve learned about bringing genomic data into healthcare.
1. Genomic data is huge. Cloud computing is the only viable option in the longer term.
A single genomic test can create more than a terabyte of data, and genomic testing is increasing exponentially. Analysing the data then takes lots of processing power. This means labs that manage their data and systems on-premises are constantly having to upgrade.
On top of this, a lot of the tools used in genomic testing are in the cloud, because of the sheer size of the data they handle. If labs have to keep moving data back and forth between cloud-based tools and onsite servers, each test will take even longer.
Melbourne Genomics members worked out early on that the flexibility of cloud services is the best option for scalability.
Genomical® is a software platform that takes the manual work out of a genomic test. Built by Melbourne Genomics members, it’s now managed by a new venture called Transcendomics.
2. Genomic data has lifetime value. We’re wasting its potential with one-off uses.
Most other pathology data – like a blood glucose test or an x-ray – is only relevant at one point in time. But your genome sequence is yours for life.
Your genome might be sequenced to find the cause of a specific problem. But that data holds many more insights about your health, including things that medical research has not yet discovered. There is immense value in retaining that data and reanalysing it in the future.
3. Genomic data must be shareable – and therefore standardised.
If genomic data is held for reanalysis, then it can’t be siloed.
As long as you give your consent, your doctors should be able to find any previous test data, no matter where it is held. That means two things. First, that the lab holding your data should be able to share it other labs on request in a way that meets both privacy and security needs. Second, that the data is standardised so that it is easy make it easy to read alongside other pieces of useful health information, like your phenotype.
4. Rigorous cybersecurity and data governance measures are non-negotiable.
Genomic data is subject to the same cybersecurity threats as any other personal data. But that’s not a reason to lock it away forever.
Rather, labs and healthcare providers need to think carefully about data governance in this space – who can request a patient’s genomic data, with whose consent, under what circumstances, and for what purpose? And when someone requests this data, how will the lab provide it to them? Can the analysis be performed on the data where it’s held, rather than the data being sent somewhere else?
5. We need a common language to discuss genomic data.
Genomic data is important to clinical care, digital health and medical research – but people in each of these domains see it in very different ways.
Take ‘data sharing’ for example. To a patient, that might mean making their data accessible to a new doctor. To a laboratory scientist, it might mean sharing gene variations with other laboratories. To a researcher, it might mean sharing genomic data for reanalysis to find new genes or gene variations .
All these perspectives are important, so when we design data sharing capability, we need to know exactly what the data will be used for and by whom.
That’s where I come in – an interpreter between worlds, combining my expertise in digital health and patient data with my growing understanding of genomics, and becoming a champion of genomics in the digital health system.
Genomics offers each of us a lifetime of better healthcare, and that’s worth working through its challenges.