Startup Genome launched the first cohort of the Global Hypergrowth Tokyo late-stage scaling program in March 2024 in partnership with the Tokyo Metropolitan Government. The initiative aims to propel the best Tokyo tech companies into successful global commercialization and expansion into international target markets.

The program addresses a significant support gap for fast-growing startups, recognizing them as drivers of economic growth and competitiveness, and creators of sustainable jobs and societal wellbeing. In its inaugural cohort, Hypergrowth provides 21 companies from Tokyo with access to global mentors, expert scaling advice from leading executives, go-to market support, and connections to potential new customers and investors.

The companies selected represent a variety of sub-sectors, including Deep Tech, Life Sciences, and AI, and have raised close to $100 million in total funding as they look to expand overseas.

In this article series, Startup Genome introduces the cohort companies, exploring the groundbreaking technologies each startup is developing to make a positive impact on the world.

Introducing Pharmaceutical Manufacturing Startup Auxilart

By leveraging an innovative approach that requires less than 1% of the data typically needed by conventional AI, Auxilart reduces experimental costs and accelerates development timelines, replacing much of the trial-and-error experiments with digital simulations. To date, Auxilart has secured contracts with leading pharmaceutical companies both domestically and globally. A recent project with a major Japanese company demonstrated its impact, saving over $1.5 million and cutting project timelines by six months.

Q&A with Auxilart CEO Junu Kim

Startup Genome spoke to Auxilart for a look into its groundbreaking technology, biggest challenges, and future innovations.

Junu Kim (JK): Our mission is to accelerate R&D processes through digital innovation. Specifically, the pharmaceutical industry has the highest ratio of R&D investment to profit. Operating with a vision of "Harnessing digital transformation to enhance health and wellbeing," our company provides advanced digital simulation services designed to reduce the cost of pharmaceutical manufacturing process development.

JK: The pharmaceutical manufacturing process bridges drug discovery and mass production, requiring optimization of multiple variables, including materials, methods, and equipment. This creates millions of options, making the process highly complex. Pharmaceutical companies typically conduct thousands of experiments, spending up to $100 million and six years on the optimization. Our simulation technology, which uses the "Mechanistic model," enables high-precision simulations with minimal data, reducing costs by up to 90%.

JK: Our key differentiator is our unique simulation technology. Generally, there are two main approaches to digital simulation: "data-driven model” (such as AI and Machine learning) and "Mechanistic model". The data-driven model performs better with large datasets, even without knowledge of the underlying phenomena. But that is limited in cases where data is scarce and the internal working processes are often opaque. In the pharmaceutical industry, the opacity poses risks because the lack of explainability makes it difficult to trust outcomes, comply with regulatory requirements, detect errors, and ensure safety and efficacy.

In the case of the mechanistic model, the first step is to represent the phenomenon through differential equations, followed by the development of the simulation. While this approach requires specific knowledge about the phenomena, it needs significantly less data and offers more transparent working processes compared to the data-driven model. There are companies that use the data-driven model, as well as those with “hybrid model” where data-driven approaches are primary and the mechanistic model is used to some extent. However, very few companies globally specialize in mechanistic models as their core technology, and this gives us a significant competitive advantage.

JK: Our business primarily targets pharmaceutical companies, and only two of the top 20 by revenue are Japanese, with the rest being global. This makes acquiring overseas clients essential for us, though it’s challenging. Through Startup Genome/Hypergrowth, we’ve been able to connect with global potential clients, thanks to mentors who facilitated these introductions. We also appreciate the valuable insights we’ve gained into key global conferences that are beneficial for expanding our business.

JK: Throughout history, cutting-edge technology has improved our lives, and R&D efforts in both industry and academia have driven these advancements. Our mechanistic model-based simulation technology isn’t limited to pharmaceutical manufacturing; it is applicable to R&D processes in diverse industries. Currently, we offer tailored services to meet individual client needs, but in the future, we plan to expand into cloud-based services. This will reduce delivery costs and allow us to extend our technology beyond pharmaceutical manufacturing, accelerating R&D processes in various industries.