Biomage: Making Single-Cell Sequencing Data Accessible to Research Biologists
Biomage is a computational biology company with a unique software that allows scientists to explore the multiverse of human cells through single-cell sequencing. We spoke with CEO Adam Kurkiewicz about the ability to turn every biologist into a bioinformatician. Watch and read an abbreviated version of the conversation below.
How is single-cell transcriptomics changing biomedicine?
Single-cell transcriptomics, or single-cell sequencing, is a relatively recently discovered method, and is used to really understand what’s happening inside living organisms at the level of individual cells. This is something I like to compare to the invention of the light microscope when scientists were for the first time able to look at individual cells. Single-cell sequencing gives us the ability to look at individual cells, from the inside. It’s a unique capability that has only emerged in the past couple of years.
This technology is not specific to just one type of biomedical researcher, but is used throughout many fields of biology, including prominently cancer research, cardiovascular research, and developmental biology.
What problem in bioinformatics is Biomage solving for researchers?
One of the biggest challenges in applying single-cell transcriptomics is that it will be difficult to scale the technology to every biologist who wants to use it. At Biomage, we make it possible for every biologist to analyze a single-cell dataset without having to develop the really, really elite expertise that has been required so far to carry out such analysis.
We do this by effectively removing a step: the process where the files created from analysis of a sample of tissue are normally first worked on by a research bioinformatician. We remove that step entirely by automating the research bioinformatician and making it possible for biologists to become the bioinformatician themselves. This benefits not just the cost efficiency, but it’s also quicker: quicker to iterate, quicker to test the hypothesis directly. It also removes the potential issues with miscommunication and knowledge transfer between 2 different fields, biology and bioinformatics.
What are the benefits of empowering biologists to analyze single-cell transcriptomics?
We are significantly cutting down the amount of time required to carry out such analysis. Typical single-cell analysis using a bioinformatician working part-time takes between 3–6 months to deliver the level of insight that is required for a publication in a high-profile journal. Our aim as a company is to bring that process down to a week or two of hand-on analysis by the biologist directly with the software.
The bulk of the cost savings is specifically eliminating reliance on a consulting service or partnership with a qualified bioinformatician. There is some additional cost reduction in how we handle the data and how we can process the data by a close integration with the core facilities where the sequencing actually happens to make it more cost effective to process the data and carry out the computational aspects of the analysis as well.
Scientists need excellent software. It’s often treated as an afterthought or something that is only a small part of research grants.
Who will your initial customers be, and will this change as you iterate the product?
We’ll work first with core facilities. Those at core facilities are happy to partner with us because working together, we can actually deliver the biggest value to their customers: the researchers. We can free the core facilities staff for work on the truly creative and difficult aspects of the field. In a core facility, there are typically bioinformaticians who are taking care of as many as 50 projects; they really need the ability to cope with the analytical needs of that many projects efficiently. By bringing the time down to 1–2 weeks, we make it possible for bioinformaticians to effectively do their job, so they’re very happy to partner with us.
On both sides of the Atlantic, both in the U.K. and in the U.S., the core facilities have been overwhelmingly positive and we expect these partnerships to further expand into other core facilities and to grow stronger by closely integrating together.
The bulk of the users and the real impact of the software that we’re building is going to most likely come from other sectors, including pharmaceutical research and biotechs. Our plan is to initially target the academic customers as a way to validate our technology and get an initial beachhead and enter into this space. For the next stage, we’re going to target biotech and pharmaceutical companies-they’re the next customer.
What provided you with unique insight into this problem?
My journey started on the other side of programming, computer programming and mathematics. I worked a short time in Skyscanner, a software company where I understood what social engineering is like and understood how software can be used to solve real-life issues and help people to accomplish major tasks.
The biological side came a bit later. To have a really impactful professional life, I wanted to come at it closer to human health and so I enrolled in a Ph.D. program at the University of Glasgow, where I ended up doing bioinformatics. I managed to find a way to merge my scientific interests with my software engineering interests! While a Ph.D. student, I realized that there was a really big need for bioinformaticians among biologists I worked with, so I started offering such analysis as a consulting service.
With my co-founders Marcel and Iva, we quickly realized that it would be impossible for us to cope with the demands. The most impactful way to allocate our efforts would actually be to build a software solution to solve the difficult problem of the alignment biologists to understand single-cell data.
Scientists need excellent software. It’s often treated as an afterthought or something that is only a small part of research grants. Through conversations with senior colleagues and in academia, I realized the best way to realize the mission of building really great software that can help was by creating a company.
What does the future hold in store for Biomage?
We would like everybody to be able to use Biomage as their solution of choice for single-cell data analytics and expand into other technologies such as spatial transcriptomics. We hope to dominate the landscape for single-cell data analytics.
Learn more about Biomage and all of IndieBio New York Class 1 companies at Demo Day on October 27. A single registration will grant you access to both IndieBio NY and SF Demo Days
Originally published at https://indiebio.co on October 20, 2020.