In the age of AI-fuelled promises and digital transformation, SOPHiA GENETICS stands apart, not by chasing trends but by quietly reshaping how healthcare systems use data to deliver more precise, equitable, and timely care. From enabling cloud-native genomics in hospitals worldwide to advancing decentralised liquid biopsy, the company is building an interconnected ecosystem of shared intelligence. But as CEO Jurgi Camblong argues, the true potential of precision medicine will only be unlocked when diagnostics receive the investment they deserve.
How would you characterise SOPHiA GENETICS’ position and mission in today’s precision medicine landscape?
SOPHiA GENETICS has been a pioneer in data-driven medicine since 2011, long before the term gained widespread currency. While precision medicine encompasses a broad spectrum, from the development of RNA-based therapies to advanced diagnostics, our contribution lies in enabling better clinical decisions through the application of data science, not the production of compounds. This focus on data as a driver of precision care defines our mission and the model we have been refining over more than a decade.
Today, we are a global organisation active in over 70 countries, supporting more than 800 institutions, including half of the world’s top 100 cancer centres. Our core offering, the SOPHiA DDM platform, is a cloud-native, AI-powered solution that analyses genomic and clinical data to support physicians in managing cancer and rare hereditary conditions. To date, the platform has been used to analyse more than two million profiles.
Since its commercial launch in 2015, our platform has evolved beyond academic hospitals to include central laboratories with greater capacity for genomic data generation, an essential modality in modern precision medicine. More recently, we have also expanded our engagement with the pharmaceutical sector. This trajectory reflects our continued commitment to equipping healthcare providers with the analytical tools needed to make faster, more accurate, and ultimately more impactful decisions for their patients.
What have been the most significant recent advancements at SOPHiA GENETICS?
Two key milestones have shaped our progress over the past few years. The first is the growing clinical validation and decentralisation of liquid biopsy. Once considered a promising innovation, liquid biopsy has now become a dependable tool for tracking cancer evolution in real time. A recent example is AstraZeneca’s SERENA-6 trial, presented at the ASCO (American Society of Clinical Oncology) Annual Meeting, which confirmed the value of longitudinal liquid biopsy in enabling earlier and more effective therapy adaptation.
In this context, a major step forward for us in 2025 was the successful decentralisation of MSK-ACCESS, a highly advanced assay developed by Memorial Sloan Kettering Cancer Centre (MSK). We have now embedded it into our SOPHiA DDM platform, making it accessible to over 40 hospitals across multiple continents, including leading institutions in the Middle East such as M42 in Abu Dhabi and others in Qatar. Enabling hospitals globally to adopt such sophisticated tools represents a significant leap, not only for patients and providers, but also for pharmaceutical companies, which increasingly depend on precise and timely patient identification.
Closely linked to this is our integration of a large-scale, de-identified clinical-genomic dataset, also in collaboration with MSK. Comprising approximately 130,000 patient cases, the dataset includes detailed molecular profiles, treatment records, and outcomes. This has been incorporated into SOPHiA CarePath, a new module within our platform designed to support contextual clinical decision-making. Through “digital twin” exploration – patients with similar genomic signatures – clinicians can gain actionable insights based on real-world data. While not intended as a diagnostic tool, it adds an important layer of intelligence to accelerate research, strengthen therapeutic discussions, and enhance overall care.
Together, these developments reflect our broader ambition to build a collaborative, data-driven intelligence network in oncology, one that connects insights across institutions, systems, and geographies. Achieving this, however, depends on infrastructure. In many countries, including Switzerland, the absence of cloud enablement in hospitals remains a substantial barrier. Without cloud access, institutions are excluded from secure, scalable, and collaborative ecosystems.
How do you approach data privacy and build trust with hospital partners across diverse global regulatory environments?
While data privacy regulations differ across jurisdictions, the European Union’s General Data Protection Regulation (GDPR) remains the most robust and clearly defined. It establishes transparent roles: the patient as the data subject, the hospital as the data controller, and SOPHiA GENETICS as the processor. This clarity provides a consistent foundation for structuring trusted partnerships.
Yet regulatory compliance alone is not enough. From the outset, we designed our platform around a privacy-first architecture, recognising that earning the trust of hospitals and clinicians demands both transparency and demonstrable clinical value. Across all markets, we define strict boundaries in our contracts: we compute data, refine our algorithms, and generate insights, always under the direction of the hospital. Data is never sold or shared without explicit, informed authorisation. Ultimately, trust is built not only through adherence to legal frameworks but through a consistent, accountable approach to data stewardship. Hospitals need to feel confident that their data is secure, their role is respected, and the tools they use truly advance patient care. That principle guides every decision we make.
What are the main drivers of hospital adoption of the SOPHiA DDM platform, and what measurable impact are you seeing?
The adoption of SOPHiA DDM is driven by a consistent set of benefits that extend across clinical, operational, and strategic dimensions. Hospitals come to us seeking improved diagnostic accuracy, faster turnaround times, lower costs, and the ability to scale precision medicine capabilities without increasing complexity. In that respect, the value we offer is both immediate and sustained.
For example, Tata Memorial Hospital in India once relied on six-week overseas workflows for genomic testing, incurring significant cost and time delays. By adopting SOPHiA DDM, they now perform these analyses in-house within five days, at one-fifth the cost, while simultaneously developing their internal expertise. Similarly, a community hospital in Florida reduced the time from 65 days to just 32 by integrating SOPHiA’s cloud-based capabilities. These are not isolated gains, but replicable outcomes rooted in strong analytics and technical adaptability.
Our platform is designed to grow with its users. Institutions performing tissue-based testing can add modules such as liquid biopsy in a matter of weeks. In the US, onboarding new applications may require CLIA and CAP certification, typically extending timelines to three to six months, but the infrastructure is in place, and we support every step. Cost efficiencies are also substantial: one customer at our recent Innovation Summit reported a 45 percent reduction in hands-on lab time and a 30 percent saving in data production costs, due to smarter compute and streamlined workflows.
Equally important is data access. When hospitals outsource testing, they often receive only static reports, limiting their ability to learn or reanalyse. With SOPHiA DDM, data remains accessible, enabling hospitals to deepen their insights and contribute to a broader ecosystem of shared intelligence. As one customer put it, “With SOPHiA, you do not just look through a window, you can step through it.”
That principle, of collective intelligence, has guided us from the beginning. Artificial intelligence, as we see it, is not an end in itself, but a set of tools that support clinical judgment. Whether through machine learning or statistical modelling, the goal is always to provide context, not conclusions. In regions like the Middle East, where hereditary and rare conditions may present differently, access to broader, anonymised datasets helps clinicians make more informed choices while preserving patient privacy. The more institutions that participate, the more valuable the network becomes, for every stakeholder involved.
How do you see artificial intelligence contributing meaningfully to clinical decision-making, beyond the current hype?
In a space crowded with claims around artificial intelligence, what sets SOPHiA GENETICS apart is a disciplined, engineering-led approach. As Jensen Huang of NVIDIA often points out, AI is not magic, it is the product of decades of deep technical work and collaboration. True breakthroughs are built incrementally, not overnight. Since launching our platform in 2015, we have remained focused on refining performance step by step, identifying where the signal lies in complex biological data and understanding what truly brings value to clinicians. AI, in our view, is a toolbox, not a solution in itself. Its effectiveness depends entirely on how well it is applied to the right problems.
There is growing hype around large language models (LLMs) and so-called “foundational models,” but the reality is that not all of these tools are suited to clinical settings. Foundational models, for instance, require transformer-based architectures. We experiment with them, but we do not use them in routine applications, as they currently offer limited added value for our use cases. What matters is pragmatism: using the right tool, not the newest one. The same principle applies to omics data. No single modality – genomics, transcriptomics, or others – is universally superior. The most appropriate input depends on the disease and clinical context. While our platform does not yet integrate every omics layer, we focus on those that offer the clearest benefit.
What differentiates SOPHiA GENETICS is not just technological capability, but our consistent, measured focus on delivering utility, ensuring each step we take leads to practical, high-impact adoption across hospitals and health systems.
Looking ahead, what are the strategic priorities guiding SOPHiA GENETICS’ scale-up and platform evolution?
Our model is built on incremental progress, a deliberate long-term approach. As outlined in our IPO documentation, we estimate our total addressable market at around USD 40 billion globally, spanning precision medicine and biopharma applications. In 2024, we generated approximately USD 65 million in revenue, which reflects both the magnitude of the opportunity ahead and the early phase we are still navigating. But the trajectory is clear.
If you step back, this is similar to the evolution of Epic, the dominant electronic health record (EHR) system in the US. It took years for Epic to reach that position, steadily embedding itself into hospital infrastructures by consistently delivering value. SOPHiA GENETICS follows the same philosophy, not aiming for quick wins, but for lasting, foundational integration into healthcare systems.
Internally, we function like a technology company. With a team of around 400, we set strategic priorities annually, asking ourselves whether the focus should be on landing new clients or expanding within existing accounts. The answer shifts depending on market dynamics and clinical needs. This year, our priority is expansion – deepening partnerships and supporting adoption – with the exception of liquid biopsy, where we are still very much in the “landing” phase.
We are highly disciplined in our scope. We focus exclusively on oncology and rare inherited disorders. In oncology, that means supporting hospitals with comprehensive genomic profiling across tissue (up to 500 genes), liquid biopsy, and MRD (Minimal Residual Disease) testing. Currently, we apply MRD only within immuno-oncology, where the clinical relevance is strongest. While we have the capability to extend into other indications, we believe in going where adoption will translate into real-world impact today.
In the rare disease space, we provide enhanced exome sequencing, targeting all coding regions of the genome, with a precision that reflects our Swiss roots. This allows clinicians to analyse a broader set of genes while maintaining analytical rigour.
On the R&D side, we are investing in multi-omics capabilities, particularly transcriptomics and DNA methylation, which we believe will become central to MRD. As the field evolves, MRD will increasingly guide treatment decisions in non-metastatic cases following surgery or adjuvant therapy. Patients who are MRD-negative – meaning no circulating tumour DNA is detected – may avoid unnecessary or overly aggressive interventions. This is a rapidly advancing space, and the future will not rest on one data layer alone. It will rely on integrating multiple omics, adapted to each cancer type and clinical context.
How do you define and maintain strategic focus across your markets, clinical applications, and commercial model?
Strategic focus, for us, means staying disciplined across three key dimensions: geography, clinical content, and go-to-market execution. From a geographic standpoint, we align with where the most impactful opportunities lie, primarily the US, Europe, Japan, Brazil, and Australia. These are the core markets that matter most for pharma, but our vision of democratising data-driven medicine extends far beyond them. We have customers in places like Guatemala, and while the route to market may vary – through direct teams or partners – the fundamental logic remains consistent: land and expand.
Where focus becomes most critical is in the clinical content. We carefully prioritise the applications we choose to support and sequence their deployment based on relevance and potential impact. This cadence is reassessed each year, reflecting the evolving needs of the market and the pace of technological progress. We operate with the mindset of a tech company, lean, responsive, and selective.
On the commercial side, our business model is usage-based. We opted against subscription because we anticipate significant volume growth over time, and locking ourselves into fixed pricing would be limiting. Today, we serve approximately 800 hospital clients, most of whom are still early in their adoption journey. If we reach 2,000 hospitals and penetrate each to 50 percent of potential, we estimate that alone could represent USD 4 billion in revenue. That figure excludes pharma, a space where we already collaborate with major players like AstraZeneca. But the hospital ecosystem remains the core engine we are building, and the opportunity it presents is vast and sustainable.
How has the healthcare ecosystem’s readiness for your platform evolved over time, and what is the current level of receptivity among hospitals?
Adoption has become significantly easier over time. When we introduced SOPHiA DDM back in 2015, many hospitals were only beginning to explore digital solutions, and the concept of data-driven medicine was still emerging. Today, the landscape has matured, and we are witnessing growing openness and engagement. In fact, if we look at the trajectory of Epic, the dominant EHR provider in the US, it took them over four decades to become fully embedded across the system. In comparison, we are progressing much faster, and I believe for good reason.
We have never approached healthcare as something to disrupt. Our philosophy has always been to work closely with hospitals and clinicians, helping them to understand the value of our platform through practical, hands-on experience. This takes time, but once they engage, the benefits become clear: greater diagnostic accuracy, faster delivery of results, lower costs, quicker deployment of new clinical applications, and full control over their data.
Some hospitals, of course, are still at an earlier stage of digital maturity, lacking even basic cloud infrastructure, which limits their ability to leverage our platform. But for those who are ready, the impact is tangible. And importantly, our solution not only enhances clinical capabilities but often leads to cost savings as well. That combination is increasingly compelling.
What impact has SOPHiA GENETICS’ IPO had on your strategy, and how do you reflect on the experience of leading a public company?
We listed in the final week of July 2021, just before the markets began to shift. While it was an important milestone, it did not fundamentally change our strategy. That said, I personally appreciate the discipline and transparency that come with being a public company. One of our reasons for going public was precisely to enhance visibility, to ensure that stakeholders had a clear view of who we are and where we are headed. I believe strongly in transparency and accountability, and public markets demand both. They raise the bar, and I welcome that.
Having to report regularly and respond to investor questions can be a constructive process. Much like engaging with customers in product development, being exposed to a broader set of perspectives, even if you cannot satisfy them all, helps you refine your thinking and sharpen your focus. It forces you to test your assumptions and, ultimately, make better decisions.
What enables SOPHiA GENETICS to sustain a competitive edge in such a fast-moving and complex field?
While the strength of our technology platform is essential, it is ultimately our people, our code, and our network that form the true foundation of SOPHiA GENETICS. I have encountered investors, especially those coming from large tech companies, who underestimate the complexity of integrating AI into healthcare. They often fail to grasp that success in this space requires more than just data and algorithms, it demands a deep understanding of biology, rigorous engineering, and continuous exposure to diverse real-world datasets.
What we have built cannot simply be replicated. Our proprietary code has been shaped by years of collaboration with hospitals and researchers, evolving in tandem with their clinical needs. This direct access to frontline healthcare challenges enables us to refine our platform in meaningful ways. But code alone is not enough. It is our people who translate needs into innovation, who understand both the scientific underpinnings and the technical capabilities to respond to them effectively. And our network of global partners gives us the insight to anticipate what comes next.
As for how we attract talent, it starts with being authentic. Our mission — to democratise data-driven medicine and apply AI for good — resonates deeply with passionate individuals from both biology and computer science. Many join us from leading institutions such as EPFL, ETH Zurich, École Polytechnique, and Harvard. Personally, I studied at a smaller university (UPPA), which highlights that while we are proud of the impressive backgrounds in our team, what truly matters at SOPHiA GENETICS is passion, hard work, and the desire to make an impact — regardless of where you studied.
What would you like the pharmaceutical industry to consider when it comes to the future of diagnostics?
There is a clear imbalance between the significant value placed on therapies and the comparatively limited investment in diagnostics. This gap is not only problematic for healthcare systems, but also counterproductive for pharmaceutical companies themselves. If testing remains underfunded, the ability to identify eligible patients diminishes, which in turn restricts access to innovative treatments and limits impact.
Pharma needs to recognise that scaling treatment requires scaling diagnostics. I am not advocating direct payments that would raise regulatory concerns, but there must be a structural solution that allows part of the value created by therapies to be reinvested into the broader healthcare ecosystem, particularly hospital testing infrastructure.
This is not a criticism of pharma profitability. Rather, it is a call for alignment. If companies want to reach more patients, accelerate diagnosis, and ensure better outcomes, then diagnostics cannot be left behind. Funding them is not just a societal good, it is also in pharma’s own strategic interest.
