It’s not every day that biology gets to share in the global spotlight, but these are not ordinary days. With the spread of COVID-19, people all around the world have been focused on developing better diagnostics, effective treatments, and vaccines for the virus. The crisis caused by this pandemic has triggered a collaboration between the technological and the medical worlds to expedite the search for a solution.

At Viola, we’ve been interested in the cross-section of biology and tech for quite some time. We dipped our toes into the field by investing in a fund called Tech.Bio in 2019, which allowed us to learn and gain access to promising computational biology companies. And we’re now proud to announce our recent investment in Immunai – a company that is decoding the immune system to improve health. They’re building the largest proprietary data set in the world for clinical immunological data and mining translational and clinical insights that would benefit us all – and they’re coming out of stealth mode today with a $20M seed round.

Biology, through the lens of AI

But what does a VC known for tech investments have to do with decoding the immune system? Our interest in computational biology actually stems from our strong belief in the power of AI to transform and disrupt traditional industries. By applying AI to process and analyze significant amounts of data, companies can provide deeper and more accurate insights to solve complex problems related to specific industries, and at a faster pace. This is true for many traditional spaces such as agriculture, legal, e-commerce, construction, finance, and, yes, also life sciences.

The volume of data generated through modern biological research is growing exponentially, and companies that can organize and analyze that data faster will be better equipped to reach breakthroughs that have never been achieved before.

Digitizing a world of biological data

There have been two major changes that have occurred in the industry over recent years. First, there has been a precipitous decline in the cost of genome sequencing, which has led to a proliferation of sequencing data in different shapes and forms. More and more, companies and academic institutions generate genomic sequencing data and analyze it for a variety of biological applications. Second, there has been a decline in the amount of time needed to receive FDA approval for new treatments.

The above, on top of the application of AI, is setting the stage for massive innovation in biology that can transform the way we develop therapeutics and the speed at which we bring them to market. As a result, the 5 major steps in the innovation process can become more efficient and require less resources:

1) Wet lab – Allowing researchers to narrow down the scope of the testing.

2) Identification of the problem – Leveraging bioinformatic tools to identify the source of the problem more quickly by using a smaller sample size.

3) Identification of the solution – Using bioinformatic tools to automatically analyze and suggest insights, expediting the discovery of a solution.

4) Clinical trials – Better defining the treatment groups and their order.

5) Elimination of side effects – Selecting a higher granularity of population parameters and proving the efficacy of treatment on a wide spectrum of characteristics.

The digitization of the biology space won’t just enhance the development of new solutions – it has the potential to lead to new innovations and insights through personalized medicine, such as customized treatments to the individual’s unique auto-immune system and biology.

Immunai: 1st to fully map and decode the immune system

One company that is taking a significant step towards personalized medicine is Immunai. This company is leveraging single-cell technologies and machine learning algorithms to chart millions of immune cells and their functions, building the largest proprietary data set in the world for clinical immunological data.

Founded by a stellar team of Harvard, Stanford, and MIT scientists and engineers, Immunai set its sights on using machine learning, mathematical and biological excellence to fully map and decode the immune system.

Immunai founders Luis Voloch (CTO) and Noam Solomon (CEO)

In line with our thesis on vertical AI, the Immunai technology includes:

• A full stack platform – Immunai has a full-stack end-to-end platform, from biological sample collection to immune profiling and immunological insights.

• It fits into industry-specific workflows – It can be integrated into the pharmaceutical development, diagnostic, and treatment processes.

• It combines subject matter (immunology) and technical (AI) expertise – The multidisciplinary expertise is on full display at Immunai , with top AI talent from Harvard, MIT, Facebook and Palantir, combined leaders in immunology from Stanford, Berkeley, and the Parker Institute.

• It generates precious and unique data – Integrating multiple single-cell assays (including single-cell RNA sequencing data), enabling pharmaceutical companies to identify more subtle nuances in cell types and states. This data also allows them to create robust and granular immune profiles by highlighting differentiated elements. Having access to this data is like seeing the full spectrum and dimensionality of colors after years of seeing only black and white.

• It utilizes AI that delivers core value – Accelerated immunotherapy development and customization, using fewer resources, at lower cost.

• It is defensible – The more complex it is to build the solution, the more defensible the business.

Increased accuracy, better personalization, faster go-to-market.

The company is seeing traction on both the clinical and commercial sides. It has already established partnerships with over 10 medical centers and academic institutions, and has multiple business partnerships with biopharma and biotech companies.

Similar to Israel’s success in building a $15B autonomous mobility company, Mobileye, which brought leading academic professors together with mobility and AI stars, we strongly believe this can also happen in the life sciences space. This will be possible with globally renowned academic institutions like Weizmann, and computer science excellence from ex-military intelligence units who are trained in this multidisciplinary thinking, like Immunai’s founders.

Our interest in computational biology is rapidly expanding, and we’re on the lookout for new, innovative companies attempting to disrupt the sector. If that’s you, ping me at