GenomeMiner wants to transform Global Biotech Industry

GenomeMiner, led by American CEO and co-founder Eli Lyons, has been developing automated platforms for genomics analysis. Since launching full-scale operations in 2017, the company has been advancing collaborative research with major corporations, while actively expanding into Indonesian and US markets.

Lyons brings an unconventional background to the role. He came to Japan in 2011 as a PhD student at the University of Tokyo, later joining a Japanese startup as co-founder, applying next-generation sequencing and machine learning to drug discovery. After returning to complete his doctoral research and publish papers, he co-founded his current company—an interesting career path that bridges academia and industry.

The company’s innovative cloud-based analysis platform serves applications ranging from stem cell research to agricultural biotechnology, contributing to enhancing the international competitiveness of Japan’s biotech industry.

Quest for Genomics Scalability

Traditional academia and DeepTech companies have historically relied on high-performance computing clusters and on-site servers during their startup processes. In contrast, the pharmaceutical industry has been migrating to cloud infrastructure globally. Examples include Chugai Pharmaceutical and Sanofi’s adoption of Google Cloud, and Takeda Pharmaceutical, Pfizer, and AstraZeneca’s adoption of AWS (Amazon Web Services).

This cloud migration trend has created favorable conditions for GenomeMiner, which develops and provides cloud-based analysis platforms.

Lyons explains,

Our platform operates on Google Cloud as its foundation. We spin up servers on demand, run them only during data processing, and shut them down after completion. We can execute multiple analyses in parallel, enabling efficient processing of large volumes of data.

The need for automated bioinformatics platforms is clear. This type of automation is becoming increasingly routine, and especially in the machine learning era, we need to collect massive amounts of data at scale.”

However, Lyons identifies this very concept of “scale” as the biggest challenge in the Japanese market.

The word ‘scale’ in DeepTech may not convey the same impression in Japanese as it does in English, or it may not be properly translated. This contrasts with IT and software fields, where the value of scale is clearly understood.

This may be because while Japan has experience with large-scale manufacturing, it has had fewer cultural opportunities to experience the importance of scalability in IT and software.

Scale is crucial in genomics, just as in IT and software, because it relates to throughput and resource allocation. GenomeMiner’s platform achieves processing speeds and efficiency levels impossible with traditional approaches through parallel processing that efficiently handles large volumes of data.

Strategic Pivot

The company’s platform currently automates quality assessment of stem cells in research, analyzing epigenetic markers and gene expression to determine characteristics of cellular youth or aging. This enables client companies to optimize their internal R&D processes and advance the development of good manufacturing practices.

However, creating scalable products was challenging in the early days.

Lyons recalls,

Within the first year of starting the company, we acquired customers including lab-grown meat companies, but we faced two challenges. First, responding to the specific needs of individual companies made it difficult to develop scalable products applicable to diverse bioinformatics applications. Second, many companies lacked clear bioinformatics strategies or roadmaps.

Against this backdrop, the company made a crucial decision. They pivoted away from contract services for initial customers and launched their own proprietary R&D project. This internal project involved collecting and screening microorganisms with commercial value from Okinawan soil, using this data to build a new genomics platform.

A significant turning point in GenomeMiner’s technological development was the shift in data types being processed. Initially, technical constraints limited them to processing very small microbial data, but in recent years they have begun increasing their processing of human data. This means GenomeMiner will likely be better positioned to contribute to therapeutic development for humans in the future.

As the business model evolves, GenomeMiner considers US expansion almost essential from fundraising and business development perspectives.

In Japan, DeepTech investors tend to prefer investing in university spin-outs with professors who have extensive experience—academic bias. But having many published papers doesn’t prove the commercial viability of research-based ventures. If that were the case, such university-based startups would be much more successful.

Japan generally has very high-level scientific and technical staff with strong technical know-how. However, when conducting the types of experiments and work I envision, budget constraints prevent achieving the most advanced outcomes. To solve this problem, more institutions need shared core facilities and deeper collaboration in resource allocation, including personnel.

Leapfrog Phenomenon

A key turning point in GenomeMiner’s growth strategy was the collaboration with a Japanese publicly listed chemical company. Through the aforementioned Okinawan soil project, they identified several antimicrobial candidates for agricultural applications, one of which continues in feasibility studies with the chemical giant.

Lyons notes,

What made the collaboration excellent was our ability to set very clear goals when discussing the partnership. For example, we could select targets for our company to screen microorganisms against specific applications they requested. This created an ideal collaboration,” Lyons notes.

For global expansion, GenomeMiner targets Indonesia and the US. This represents strategic decision-making based on market characteristics. Indonesia particularly offers an environment enabling flexibility unconstrained by existing systems and rapid decision-making.

For example, when talking to a company in Japan that develops fermentation products using microorganisms, they might already have two IT members, one bioinformatics person, and internal servers. In such cases, there’s resistance to adopting new cloud-based solutions.

In contrast, Indonesian companies don’t have existing systems in place, freeing them from such constraints and enabling them to focus on developing new products that generate revenue. Top-down decision-making from management allows for fast decisions. These market characteristics work advantageously for startups like ours.

This exemplifies the “leapfrog phenomenon,” where developing countries skip traditional technological stages to adopt cutting-edge technologies. Indonesia, with over 280 million people, represents a large market with significant potential, including developing medical tourism and wealthy demographics capable of purchasing stem cell products. In fact, one of Indonesia’s largest companies uses their platform on a limited basis, with active discussions underway with hospitals and pharmaceutical companies.

Meanwhile, in the US, people are very open to automation and genomic solutions, which suits GenomeMiner well. As an American, Lyons brings natural advantages, and from fundraising and business development perspectives, the US market is unavoidable for scaling GenomeMiner’s business. The company received substantial support from JETRO (Japan External Trade Organization) for the US market expansion.

Lyons maintains clear and specific vision regarding the partnerships GenomeMiner seeks. He particularly values relationships enabling open dialogue.

We seek collaboration with companies that definitely want scaling and digital transformation. These movements will become increasingly important in coming years, and companies that don’t pursue them will face difficulties.

We welcome initial outreach for open discussions about how to implement digital transformation, how to incorporate more genomics into our work, and whether that would improve our products.