Genomic sequencing is now a core clinical service in Australia. But when laboratories talk about the cost of genomic data, the conversation is often reduced to simple questions like how much does it cost to store the Fastq and BAM files.
While it’s a valid question, it’s also misleading. In a regulated, clinical setting, storage is rarely the dominant cost-driver when it comes to managing the data. The real cost of being in the business of genomic data is in the work required to operate as trusted, compliant clinical infrastructure.
Here are the top cost drivers your laboratory should consider and how you can develop a useful and realistic cost model for genomic data.
Integration is where the money goes
On its own, a sequencing pipeline that produces a VCF is not a clinical service. To deliver clinical value, genomics must integrate with:
- Lab Information management systems (LIMS)
- Ordering pathways
- Patient identity systems
- Secondary and tertiary genomic analysis tools
- Systems that generate the raw genomic data
- Other downstream clinical systems
Every interface must be built, tested, monitored, and maintained. Often, it can take a year or more to establish each interface, and every upstream change can break it.
Integration isn’t a one-off project; it’s a permanent maintenance burden that should grow as your service scales.
Doing genomics creates perpetual obligations.
A key benefit of genomic testing is the ability to reanalyse data over time. With new evidence and new tools comes new diagnoses. But reuse is (unfortunately) not a free bonus. Genomic data analysis requirescomputing, validated workflows, provenance tracking, and careful governance. In regulated settings, the lab must be able to explain exactly how a result was generated at the time, prove that processes were accurate, and guarantee that only authorized people accessed the data. This requires a sophisticated system.
Compliance isn’t a box-ticking exercise: it’s engineering and operations
Australian laboratories operate in an environment with high accreditation, privacy and quality expectations. Add modern cybersecurity to the mix, and compliance for doing genomics becomes a dedicated operational IT discipline. Laboratories must actively manage their access control, logging, monitoring, vulnerability management, incident response, supplier assurance, evidence capture and change control as part of their BAU work. These are no longer occasional tasks; they’re continuous activities that need specialised people and tools.
Sustaining a highly specialised data workforce
All genomic services depend on data-skilled staff:
- Clinical bioinformaticians keeping pipelines operating
- Software engineers maintaining integrations
- Quality specialists managing validation and change control
- Security experts operating technical controls
These roles are scarce and expensive, and their cost is often underestimated because it doesn’t sit neatly within a per-test cost line item. Notably, the cost of IT services is often hidden to laboratories, viewed as a back-of-house function rather than a specialisation embedded within all aspects of genomic testing.
Why this matters now
Australia’s policies are increasingly focused on value-for-money, sustainability, and equitable access. If reimbursement and investment decisions are anchored to incomplete cost models, laboratories will either:
- Absorb hidden costs (reducing sustainability); or
- Delay adoption (reducing access)
Getting the economics right requires everyone to expand the conversation: Genomics is not just a test; it’s a regulated data service with lifelong obligations.
Developing a realistic cost model
If laboratories and payers want evidence-based adoption at the right scale and pace, the total cost of doing business should be modelled. A practical approach to this should consider:
- System integration build and ongoing maintenance
- Validation and re-validation costs for pipeline and software changes
- Security and privacy operations across multiple third-party systems often in the cloud
- Quality management overhead and audit readiness
- Vendor management and shared responsibility controls
- Reanalysis workflows (including governance, accessibility of data, provenance and traceability)
- Workforce capacity and training (including clinician and senior management time to account for errors and non-conformances)
The good news? Once laboratories cost these elements explicitly, they can:
- Unlock the pace of innovation adoption
- Unlock efficiency
- Embed security best practice and controls
- Maintain currency of data workflows and reliability
- Make genomic data management financially sustainable
This is how genomics becomes routine care; not just routine sequencing.
Interested in learning more about the real costs of genomic data in a regulated environment? Fill in this form to access a free practical cost framework for genomic data management to get you started.
The hidden cost of doing business: Why storage of genomic data is just one part of the puzzle 
