How does a doctor know what drug to prescribe a patient? After all, we are all different in our genetic makeup and our lives, which influences how we metabolize various drugs and respond to specific treatments. What’s more, doctors worldwide have different tools at their disposal to make these judgments. What if there was a way to peer into a medical magic mirror and see clinical outcomes for people of all shapes and sizes, no matter where they come from and with the clinical tools available?
SOPHiA Genetics—the name comes from the Greek word for wisdom—is the creator of a global data pooling and knowledge-sharing platform that advances data-driven medicine, working with customers from more than 780 institutions in more than 70 countries. The goal of this data-driven medicinal network is to improve health outcomes and economics worldwide. By applying their technology to diseases like cancer and inherited disorders and combining genomic and phenotypic information, SOPHiA Genetics supports medical discovery, treatment decisions, and drug development efforts.
The venture-funded pharmacogenetics company has international operations across the U.S., Switzerland, and France. On July 22, SOPHiA Genetics announced the pricing of its initial public offering (Nasdaq: SOPH) of 13 million ordinary shares at $18 per share.
GEN Edge spoke with CEO Jurgi Camblong, PhD, co-founder with Pierre Hutter, PhD, and Lars Steinmetz, PhD, to discuss how SOPHiA Genetics is developing data-driven multi-modal diagnostics to democratize healthcare.
GEN Edge: What was the founding mission and vision for SOPHiA Genetics?
Camblong: When we started in 2011, we saw new technologies such as genomics and new companies building technology solutions that we thought would make a big difference in our ability to do good research and understand what is driving disease. In our opinion, adopting these kinds of technologies would create a vast amount of data in the healthcare sector. With that in mind, we thought of an approach to break the silos across the hospitals and labs producing the data as well as across instruments and modalities.
We created a collective intelligence to deliver smart insights to clinicians and scientists around the world. We started building our technology in 2011 around these principles in the cloud and delivered them to the market in 2014. The traction has been amazing because this is sensitive data. We created something new, and we didn’t know if it would work or whether hospitals would agree to produce data and put the data into SOPHiA’s cloud.
Today, we’re about halfway through our mission of connecting 780 hospitals around the world in 72 countries. This speaks to our view of the world and on the democratization of these approaches. We have supported data computing of over 770,000 clinical genomics data sets since 2014.
Where we are headed is beyond genomics, adding additional data layers. For example, in immuno-oncology, we’re looking at imaging data capabilities. With tumor profiling of patients, you can understand what is driving the cancer. But if you really want to follow the patients, you need to look at images. The beauty is that when you combine the two, you have information to predict how the next patient will respond to a treatment based on similar patients that have been treated.
This is the world we’re building. The most significant milestone will be when, for the first time, an oncologist decides to give a patient treatment, considering how a patient compares to other patients who have been receiving specific treatments.
GEN Edge: How is SOPHiA Genetics organized as a company?
Camblong: We approach our company with a tech mindset. We knew that our platform would eventually need to have deeper data science capabilities. But we didn’t pretend like we knew what type of technologies would benefit from this data-driven medicine because this requires clinical utility. So, our approach is very much about listening to the market and speaking with different doctors to understand their needs and pain points. We tried to understand how our technological capabilities with our deep understanding of science could build smart solutions to help them. Even though we work in the health sector, we very much operate like a tech company in addressing healthcare needs around the world.
GEN Edge: Why is SOPHiA Genetics choosing to go public?
Camblong: For multiple reasons. With greater visibility, we can eventually sign larger and longer-term contracts with more extensive integrated systems in the U.S., like academic centers and the biopharma industry. Partnering with a public data analytics company is safer for a biopharma company developing a drug, which can take ten years. It will also help us attract talent.
In terms of development, it’s about continuously expanding our customers’ network because the broader the network, the greater the diversity of the data. I think that’s something that is often misunderstood. Diversity is very important in any data game. The greater the diversity and volume of data you can get, the better you can build algorithms because you’re exposed to more challenges and solve more problems for the users. The use of the proceeds is really about expanding the size of the network.
We also want to build upon our platform to move beyond genomics and radiology and look at other data modalities. We want to look at proteomics data eventually. We want to move into diagnostics. But we have to make sure that we can do everything ourselves. We want to build APIs to leverage what others have done in the industry and be in the heart of an ecosystem to bring better and better solutions to our customers.
We want to contribute to the standardization and regulation of the industry eventually. We believe that the more standardized we can make data-driven medicine, the greater the impact will be. Academic centers are early adopters, but we want to go into community hospitals as well. This is where it’s important to have regulated proven technologies in the market.
GEN Edge: How do you balance partnerships and clients? Are they the same?
Camblong: For us, hospitals are very much partners, but in the end, they are clients because they pay us. It’s a win-win deal. The better we deliver, the more capabilities we give a hospital, the more they will use the platform. But if we fail, eventually, they will stop using the platform. It’s a healthy tension that we have and makes our company work on the needs of the hospitals.
We also partner a lot with industry players. GE is one of our investors. GE has imaging devices in the market. Having SOPHiA on top of these imaging systems and combining genomics data with this imaging data, clinicians can make better informed decisions.
GEN Edge: How many employees and centers does SOPHiA Genetics have around the world?
Camblong: We are at about 470 employees and growing fast. We should be at about 500 before the end of the year. We have multiple centers. We started in Switzerland close to a very high-level university hospital called The École polytechnique fédérale de Lausanne (EPFL). It’s like the MIT of Europe. A lot of students go to the EPFL to change the world. Many of them have projects on robotics or sustainable energy. We started that in this ecosystem and benefited from recruiting brilliant data scientists.
Then we’ve been building capabilities in the U.S. in Boston. We’re growing there and recruiting software engineers and data scientists. We’re also recruiting in the southwest of France, close to an excellent engineering school, which trains unique computer scientists. We always like to set our places, if possible, where there is a very good life balance because we tend to recruit very passionate and dedicated people. They tend to work very hard. If they can go out and be in nature and relax after work, they will stay fresh!
GEN Edge: Is your solution limited by the quality of the hospital equipment and instruments?
Camblong: This was hard to deal with but is what gave us a competitive advantage. When you are supporting the decentralized world, you face hospitals using different instruments and consumables, some of which are not as good as others. But we must deliver them insights so that they can leverage this data. So, this diversity has enabled us to face more adversity, diversity, and challenges than one would get under a controlled environment. This is what has enabled us to see what will be signal and noise. With our algorithms, we can standardize them. After the data is produced, our first job is about homogenizing and standardizing the data so that the data of any hospital will look similar. Some sequencers are better than others. Some consumables are better than others. Some genetic regions are very challenging. Some mutations are challenging to find.
This is why we are good. We understand data better than any instrument or consumable player because we have embraced this world of diversity. By doing so, we’ve seen so many things, and we know the statistical power of the data. We can maximize and improve the way people produce data, given the challenges. The better the data, the more they’re going to use our platform.
How we won our network was by doing exactly what we just discussed. The first step was about making those data standard and enabling those hospitals to use clinical-grade next-gen sequencing. In the multi-modal world, we are now launching what we call prospective observational clinical studies. There is one on non-small cell lung cancer where we already have predictive analytic capabilities that enable us to have a very high sensitivity in identifying non-responders to immunotherapy. This can be a game-changer because it means that an oncologist will give the drug that works. On top of that, the patient will not have to deal with toxic effects.
We want to deliver to the market cool stuff with deep science behind it as a multi-modal player but never taking the decision from and replacing the oncologist or the pathologist. We want to bring them higher quality data so that they have a better perspective.
GEN Edge: What impact will SOPHiA Genetics’ work have on the economics of healthcare?
Camblong: It’s not about pushing for smaller budgets. It’s about making the best use of the existing budget. I’m not in favor of globalization for everything, to be honest. I think we should produce our fruits and vegetables close to us. But I think there are a few things where globalization is helpful, such as sharing data-driven medicine. Everyone should have the same information, perspective, and ability to make the right decisions. Otherwise, someone in a rural region will not be optimally treated because there was no means to do so and because the information was not there. This is the beauty of the movement we’re launching.