Cranfield, UK, 13^th February 2026

After completing our Genomics IT World Market Research Report, Signify Research has shared three critical truths that genomics IT vendors need to understand before attempting to commercialise in clinical markets successfully in 2026.

Healthcare has never been an easy market to crack. Even established vendors operating in mature segments contend with long sales cycles, complex procurement processes and demanding end users.

For companies attempting market development in this environment, including those commercialising NGS and genomics IT software, the challenge is significantly greater. A cursory glance at LinkedIn surfaces familiar frustrations: bureaucratic decision making, highly fragmented integration environments, and the uncomfortable historical reality that clinicians have rarely been buyers of genomics software.

Against this backdrop, vendors must confront a fundamental question for 2026; how do you build a sustainable business in a market that remains price-sensitive, partially commoditised, and long dominated by a small number of incumbents?

And yet, despite these headwinds, the clinical genomics IT market is clearly opening up.

High-profile deployments in recent years, such as Dana-Farber’s collaboration with Philips and Penn Medicine’s partnership with Sectra in the United States, demonstrate that clinical adoption of advanced genomic software is achievable. Independent software vendors including DNAnexus, SeqOne and others are also actively repositioning their platforms for clinical growth.

Roche’s renewed focus on next-generation sequencing reinforces this shift. In unveiling its “Sequencing by Expansion” technology, the company emphasised the ability to reduce the sample-to-genome turnaround time from days to hours, while explicitly positioning the technology to support translational and clinical applications. This signals a clear strategic intent to enable scalable, rapid sequencing solutions capable of underpinning routine clinical genomics workflows and diagnostics in the years ahead.

Drawing on deep experience across healthcare IT, alongside an expanding body of insight into NGS and molecular diagnostics, Signify Research’s analysts highlight three strategic considerations* for vendors seeking to bridge the gap between genomic innovation and clinical reality:

1. Clinical IT is complex: integration is non-negotiable
2. ROI must be immediate and defensible
3. Storage is not just a technical problem; it is a commercial one

Taken together, these considerations help explain why many genomics platforms struggle to scale beyond early clinical deployments…

*These themes are explored in greater depth in Signify Research’s Genomics IT World Market Research Report, which provides additional context on how commercial, clinical and technology dynamics are converging.

1. Clinical IT is complex: integration is non-negotiable

Selling into clinical environments rarely means integrating into a single laboratory system. Genomics software must operate across a geographically and technically fragmented healthcare IT landscape, spanning private laboratories, public healthcare providers and regional care networks. Success therefore depends not only on technical capability, but on making disciplined integration choices that align with established clinical workflows and commercial realities.

In practice, Electronic Health Records and Laboratory Information Systems act as the primary gateways through which genomic data enters routine patient care. As a result, they are typically the first systems genomics vendors are expected to integrate with. However, these platforms face significant challenges of their own, including legacy architectures, interoperability constraints, inconsistent data formats and uneven levels of commercial maturity across regions.

Outside the United States in particular, EHR and LIS markets remain highly fragmented. Many deployments are still on-premise, APIs are inconsistent, and underlying infrastructure is often outdated. This fragmentation has already slowed the adoption of digital pathology and is having a similar effect on newer genomics applications. Integration is therefore complex, time-consuming and expensive, with HL7 connectivity alone often representing a substantial upfront cost per hospital.

Against this backdrop, partner selection becomes a critical strategic decision for genomics IT vendors. Targeting platforms with large installed bases is not sufficient. Commercial sustainability depends on partnering with vendors that combine meaningful market share with proven profitability and the ability to scale integrations across regions. (A large number of low-value installations does not translate into predictable revenue or long-term growth!)

Over the past two years, this reality has increasingly shaped vendor behaviour. EHR and LIS suppliers have made tangible progress in expanding their genomics capabilities, improving interoperability and forming more selective partnerships. The DNAnexus–Oracle Health collaboration announced in 2025, which aims to embed structured genomic data within the Oracle EHR, is one example. Vendors such as Meditech and Clinisys are also strengthening workflows, although as a rule most EHR platforms continue to prioritise breadth over best-of-breed depth.

For genomics software providers, these partnerships offer access to established distribution channels, increased credibility with procurement teams and a clearer route into clinical practice. Deeper, workflow-centred integrations allow vendors to move beyond standalone analytics tools and position themselves as part of the broader precision medicine infrastructure.

However, scalability remains constrained by regional market structure. As mentioned previously, the United States has seen increasing consolidation around a small number of enterprise EHR platforms, while Western Europe continues to favour many individual best-of-breed LIS deployments and domestic suppliers. This divergence reinforces the need for geographically targeted partnership strategies rather than one-size-fits-all approaches.

As a result, the genomics vendors most likely to succeed will resist highly customised, one-off integrations. Instead, they will prioritise a small number of deep, technically mature partnerships aligned to specific geographies and clinical use cases, whether oncology diagnostics, pharmacogenomics or molecular pathology. Making these choices requires a clear understanding of which clinical IT platforms are commercially viable, scalable and actively investing in genomics capabilities, particularly within the LIS ecosystem.

Even with the right partners identified, a more fundamental question remains: how much integration is actually necessary, and at what stage of the genomic workflow. While integration with EHRs and LIS is essential for embedding genomics into routine clinical care, there is a growing risk that parts of the industry are over-prioritising deep clinical integration too early.

Although genomics extensions to FHIR are available, adoption remains uneven, and many healthcare organisations, including well-resourced academic centres, have yet to upgrade core systems. In practice, integration approaches vary widely. Large institutions are more likely to rely on FHIR-based interfaces, while smaller laboratories often continue to deliver genomic results as static reports, frequently in PDF format, with limited or no structured data exchange.

For genomics software vendors, this creates a disconnect between where analytical value is generated and where integration is currently expected. Deep EHR integration delivers the greatest value at the point of tertiary interpretation and clinical decision-making. Earlier stages of genomic analysis are often better served by simpler, standardised data formats that support reuse, collaboration and downstream integration across both research and clinical environments. Over-emphasising full clinical integration at these stages can introduce unnecessary complexity and cost.

Without a more phased approach to integration, genomics software development risks being constrained by expensive, bespoke interfaces that limit scalability rather than enabling broader clinical adoption.

However, integration alone does not guarantee commercial success. Even with the right technical partnerships in place, vendors must still navigate who actually buys genomics software, how purchasing decisions are made, and where budget ownership sits within clinical organisations. This leads directly to the second challenge vendors must address: understanding the clinical buyer, and the realities of procurement and reimbursement in genomics IT.

2. ROI must be immediate and defensible

Healthcare organisations operate under persistent staffing, budgetary and capacity constraints. For genomics IT vendors, this means that before integration is even considered, buyers want a clear answer to a simple question: how quickly is tangible value added?

The framing of ROI varies by setting. Public healthcare systems often prioritise impact on patient outcomes, workforce efficiency and service sustainability, while private providers are driven by margin, throughput and utilisation. In both cases, laboratories are typically underfunded and resource constrained. Vendors must articulate precisely what their software does, which steps or complexities it removes, how much time it saves, and how those efficiencies translate into measurable cost or productivity gains. If the benefit is indirect or long term, the challenge becomes convincing customers why the investment should be made now.

Newer sequencing vendors have been effective in anchoring ROI to efficiency and speed early on. Roche, for example, has consistently linked its sequencing innovation to reductions in turnaround time and operational complexity, reinforcing the economic case for clinical adoption alongside the scientific one. This emphasis on efficiency provides a useful reference point for software vendors seeking to align their value proposition with laboratory realities.

One common route to justification is reimbursement, either by enabling reimbursable tests or supporting compliance with emerging reimbursement pathways. However, as seen across radiology IT and clinical AI, reimbursement alone rarely guarantees adoption. Pricing, sales execution and business model design often matter more. Demonstrating improvements in workflow efficiency, clinical decision making or patient outcomes is increasingly essential, particularly where software is perceived as an additional cost rather than a replacement.

At the same time, structural market dynamics are reshaping where sequencing occurs. The majority of US NGS testing continues to be performed in large private diagnostic chains rather than hospitals, driven by the high capital cost of sequencers and the operational complexity of running them in-house. Managed service agreements and centralised testing models are becoming more common, consolidating purchasing power among a smaller number of large providers.

Importantly, this shift does not reduce the need for genomics software within hospitals. Whether sequencing is performed on site or outsourced, hospitals still require software to order tests, interpret results, integrate genomic insights into clinical workflows and support downstream decision making. For vendors, this creates parallel opportunities across provider types but also reinforces the need to align pricing and ROI messaging with highly cost-sensitive buyers.

However, even with a compelling ROI narrative, vendors must confront a further challenge. Adoption ultimately depends on how genomic insights are used in day-to-day clinical practice, not just on who pays for the software. This brings us to the next challenge: ensuring that genomics IT delivers value at the point of care, and is trusted, usable and actionable by clinicians.

3. Storage is not just a technical problem; it is a commercial one

Diagnostic data does not disappear once a result is reported. In clinical settings, it must be stored, governed and retrievable, often for decades. Many healthcare providers are already struggling with this reality. In digital pathology alone, image archives routinely run into petabytes, representing a growing, largely additive infrastructure cost. Genomics compounds this challenge further, with raw and processed sequencing files substantially larger and generated at increasing frequency.

As sequencing volumes rise and per-genome costs continue to fall, storage rapidly becomes an issue for customers. What was manageable in research settings becomes materially more complex in clinical care, where regulatory, governance and retention requirements are stricter and more visible to procurement teams. Decisions around on-premise versus cloud architectures, long-term data retention and secondary use of genomic data all carry direct cost implications for providers.

While cloud infrastructure providers such as AWS are already embedded partners for many genomics vendors, biobanks and research programmes, this alone does not resolve the economic challenge for healthcare systems. Clinical buyers increasingly expect software vendors to play an active role in mitigating storage cost growth, rather than simply passing it through. This shifts the focus from redundancy and raw capacity towards strategies such as intelligent data compression, tiered storage, lifecycle management and defensible data deletion policies aligned with clinical and regulatory requirements.

For genomics IT vendors, storage strategy therefore directly influences pricing models, margin structure and perceived total cost of ownership. In contrast, vendors that can clearly articulate how their architecture controls storage growth, supports compliance and reduces long-term cost are better positioned to build trust with clinical and procurement stakeholders.

Ultimately, storage decisions affect commercial adoption, not just infrastructure planning. If genomic data management introduces unpredictable cost escalation or operational risk, routine clinical use becomes harder to justify. Vendors that treat data lifecycle management as a core component of their clinical value proposition, rather than an afterthought, will be better aligned with the economic realities of scaling genomics in healthcare.

Why execution, not innovation, will define success in clinical genomics

Taken together, these three dynamics highlight a central truth facing genomics IT vendors in 2026. Clinical adoption is not driven by innovation alone, but by how well software integrates into complex healthcare IT environments, delivers credible and near-term return on investment, and scales sustainably as data volumes grow. Each of these factors is tightly interlinked. Decisions made around integration partners influence cost and adoption, ROI narratives are shaped by where sequencing occurs and who controls budgets, and storage strategy increasingly determines long-term viability rather than just technical feasibility.

What complicates this further is that none of these challenges play out uniformly across regions or care settings. Market structure, procurement behaviour, reimbursement models and IT maturity vary significantly between the United States, Western Europe and emerging markets. As a result, assumptions that hold in research or early clinical pilots often break down at scale.

Vendors that succeed will be those that move beyond generic clinical narratives and make highly informed, market-specific choices about partners, pricing, deployment models and target customers. Achieving this requires a clear understanding of how genomics is actually being adopted today, where budget authority sits, how infrastructure constraints shape buyer behaviour across different healthcare systems, and how these factors translate into realistic adoption timelines and sustainable business models.

Signify Research’s Genomics IT World Market Research Report addresses key questions shaping the market today, including:

• How is the balance between PCR and NGS expected to evolve as sequencing costs continue to decline?
• How did NGS hardware and analysis software vendors perform in 2024?
• What features are customers demanding from NGS analysis software?
• How are genomics platforms integrating into wider healthcare and industry IT ecosystems? Where do partnership opportunities with EHR and LIS vendors genuinely exist?
• What commercial and operational factors influence laboratory investment decisions?

As genomics moves decisively into the clinic, understanding these dynamics is the difference between experimenting at the margins and building a sustainable presence in clinical care.

About Signify Research

Signify Research provides healthtech market intelligence powered by data that you can trust. We blend insights collected from in-depth interviews with technology vendors and healthcare professionals with sales data reported to us by leading vendors to provide a complete and balanced view of the market trends. Our coverage areas are Medical Imaging, Clinical Care, Digital Health, Digital Laboratory & Lifesciences, Healthcare IT and AI in Healthcare.

Clients worldwide rely on direct access to our expert Analysts for their opinions on the latest market trends and developments. Our market analysis reports and subscriptions provide data-driven insights which business leaders use to guide strategic decisions. We also offer custom research services for clients who need information that can’t be obtained from our off-the-shelf research products or who require market intelligence tailored to their specific needs.

About Imogen Fitt

Imogen joined Signify in 2018 as part of the Healthcare IT team. She holds a 1st class Biomedical Sciences degree from the University of Warwick. Since joining the team Imogen has studied various healthcare markets and is now expanding Signify Research’s coverage in Digital Laboratory and Lifesciences markets. She has published reports on Breast Imaging, General Radiography, AI in Drug Development and Clinical Trials, LIS/LIMS, Digital Pathology, oncology IT, and Real-World Data.

About the Digital Laboratory & Lifesciences Team

The Digital Laboratory & Lifesciences team provides market intelligence and detailed insights on the multiple healthcare technology markets where the clinical world intersects with the preclinical. Our areas of coverage include digital pathology, laboratory information systems, clinical Real-World Data (cRWD) platforms, oncology information systems, tumour board software, oncology decision support software and radiotherapy IT. Each report provides a data-centric and global outlook of its markets with granular country-level insights. Our research process blends primary data collected from in-depth interviews with healthcare professionals and technology vendors, to provide a balanced and objective view of the market.