MediSapiens creates cutting-edge solutions for transforming biomedical data from different source into knowledge, insight, and value. In this interview, VP of Sales Hans Garritzen discusses the shift from reactive, generic healthcare into proactive, personalized healthcare, and the advantages for data owners.
Please describe the story behind the company: What sparked the idea, and how has it evolved so far?
MediSapiens started in Helsinki in 2009 as a spin-off of the Institute for Molecular Medicine in Finland (FIMM). Several researchers there were doing a project that got the attention of One Pharma, which has been a long-term client of ours. Since then, MediSapiens has been providing software solutions and services to make the best possible use of biomedical data and has grown towards a specialization in genomics. We have a daughter company in the US, which is mostly focused on sales, and many global partners as well. In January, we celebrated our 12th anniversary.
What kind of organizations do you typically work with, and what is the value that you provide them with?
Most of our clients are data owners that pharma companies may be interested in because of the data they possess, or pharma clients using data from different sources such as biobanks, university hospitals, healthcare providers, life science companies, and CROs.
Our value is twofold. We give users the capability to integrate genomic data as part of their operations, and ensure that they can combine different data sources, whether that’s genomic-based data, clinical or other omics data.
This has been an ever-growing business. As full genomic DNA testing is becoming cheaper, more and more data is being generated. We make sure our clients have the infrastructure to integrate that data, manage it, and more importantly, combine it with other data sources.
Genomic data alone can already provide a lot, but if you combine it with clinical data and other omics data, the value grows even further.
What kind of insights can MediSapiens produce?
It depends on the client. For example, we are working with the largest private health care providers in Finland, which is already integrating genomics as far as cooperation with pharma in clinical trials goes. They have a huge biobank with millions of patients. By adding genomic data, they expand their attractiveness in the lucrative pharma sector.
In drug development, for instance, adding genomics is becoming increasingly important for making informed decisions and discoveries, based not just on clinical observations but also on the genomic profile of the patient. This personalization trend within drug development and the genomic aspect of it is, of course, very important.
We expand the range of data that our clients can use, whether it’s a public data set such as the UK Biobank or FinnGen, the Finnish equivalent, or patient-specific information that they get from their trials. This way, they get a much wider view of their possibilities, making their drug discovery much more specific.
Can you give an example?
We have been working with a Dutch company called Innatoss, which provides consistent testing of Q fever, Lyme disease, and now COVID-19 antibodies.
We made sure that their data streams were digitized and aligned together. One of their biggest problems previously was that they did everything manually using Excel, which is, of course, cumbersome, takes a lot of time, and imposes risks.
With the solution we built for them, everything is fully automated and works much faster. They are now able to make customized reports for their clients with a much faster turnaround.
Their business model is that they do regular tests for the diseases I mentioned. On average, a Dutch general practitioner will have up to three patients a year with Lyme disease symptoms. They only have about ten minutes for each patient, so they don’t have much knowledge about the disease, because there are very few cases per year, and they have very little time to make a treatment plan with the patient.
We gave them a solution where they could make reports based on the data that they generate, which immediately make it clear for both the doctor and the patient what kind of treatment plan should be made with regards to, for instance, the use of antibiotics.
Currently, if a doctor is not familiar with a disease, they just prescribe an average dose of antibiotics and continue with their day, but we all know that antibiotics can be very dangerous because it can decrease long-term resistance. With our solution, they have all the information in front of them to decide whether to increase or decrease the amount of antibiotics.
This is how our solution helps Innatoss to support doctors. We take away their workload and offer automated decision-making that helps them to work out better treatment plans in the short time that they have with the patient.
One of the challenges that we continuously see in the healthcare sector is that they often have databases with hundreds of thousands if not millions of patients, mostly of working age, but they have difficulties finding and understanding the information they’re holding.
Before we came in, if they needed to build a cohort of, for example, 20 to 35-year-old, Covid-positive male patients that have given their consent for post-COVID research; previously, it would take them 30 to 45 days to create that cohort. Now, with our solution, they can do it in a matter of minutes.
This is also a huge sales advantage for them, as Pharma companies are interested in the data and use it to find out if it’s feasible to start working together. They too can have an initial idea of the available cohorts within minutes.
While some providers offer complex, “sciency” reports, others oversimplify the results. How do you balance this equation?
Our main focus is on the back-end of things. We want to provide our clients with capabilities, but each client has their own expectations and data sets. Often, researchers come with their own favorite tools. Some may do command-line interface work, others may prefer a visualization tool.
We try to make our solution as inclusive as possible, so that users are not just dependent on the interface we provide, but can also integrate it with tools they might have developed themselves or acquired from a third party. We provide them with an architecture that fits within their existing operations and can be adapted to their specific needs without depending on our service.
What do you do to secure data stored on your platform?
Data security is very important to us. Ever since the beginning, we have worked with Bayer AG, a German pharma data company that is known to be very strict with their data security.
Our solution is cloud-based, but we make sure it loads from a nearby cloud location. We also make sure that access is strictly regulated, according to different solutions such as specific IP addresses and restricted user access. We can also allocate different access groups within the data. A key user may see all the data, while a regular researcher may only see a specific part of it.
We can also allocate different users to different data sets. For instance, Finnish data may only be seen by Finnish researchers, or in more detail, a foreign researcher can only see the data on a meta-level. Additionally, we are currently looking at anonymization processes, which are also becoming increasingly important because regulation is strict.
Everything we do is according to local regulation and GDPR. We recently had a security audit with one of our clients, and everything was according to specification.
Which trends or technologies do you find to be particularly interesting these days around your line of work?
Wearable medical devices and the Internet of Things, in general, are getting stronger, especially in the US but also in Europe. I envision a future where genomic information will become an integral part of personalized healthcare. It’s going to be very interesting to see how far it can go.
Another very interesting development is animal genomics, especially companion animals like dogs, cats, and horses. The fun part is knowing, for example, what percentage of your dog’s genome is German Shepherd and what percentage is Poodle. On the more serious side of things, dog breeders are using genomics to prevent inherited diseases. Bulldogs, for instance, tend to suffer from breathing difficulties that can be prevented. We created the largest pure-breed dog and cat genomic testing service in the world.
As more and more genomic data becomes available, both from individuals and through the healthcare systems, the need for scalable solutions is growing as well. It’s also important to combine that data with other available data sources such as patients’ clinical data because genomic data alone is not enough. Mediaspiens is here to help organizations make that leap into the future.