Established 77 years ago, Mitsui & Co stays vibrant by building businesses and ecosystems with new technologies like generative AI and confidential computing.
Digital transformation takes many forms at the Tokyo-based conglomerate with 16 divisions. In one case, it’s an autonomous trucking service, in another it’s a geospatial analysis platform. Mitsui even collaborates with a partner at the leading edge of quantum computing.
One new subsidiary, Xeureka, aims to accelerate R&D in healthcare, where it can take more than a billion dollars spent over a decade to bring to market a new drug.
In Pursuit of Big Data
Though only three years old, Xeureka already completed a proof of concept addressing one of drug discovery’s biggest problems — getting enough data.
Speeding drug discovery requires powerful AI models built with datasets larger than most pharmaceutical companies have on hand. Until recently, sharing across companies has been unthinkable because data often contains private patient information as well as chemical formulas proprietary to the drug company.
A Proof of Concept for Privacy
To validate that confidential computing would allow its customers to safely share data, Xeureka created two imaginary companies, each with a thousand drug candidates. Each company’s dataset was used separately to train an AI model to predict the chemicals’ toxicity levels. Then the data was combined to train a similar, but larger AI model.
Xeureka ran its test on NVIDIA H100 Tensor Core GPUs using security management software from Fortanix, one of the first startups to support confidential computing.
Up to 74% Higher Accuracy
The results were impressive. The larger model’s predictions were 65-74% more accurate, thanks to use of the combined datasets.
The models created by a single company’s data showed instability and bias issues that were not present with the larger model, Ito said.
An AI Supercomputing Ecosystem
Now, Xeureka is exploring broad applications of this technology in drug discovery research, in collaboration with the community behind Tokyo-1, its GPU-accelerated AI supercomputer. Announced in February, Tokyo-1 aims to enhance the efficiency of pharmaceutical companies in Japan and beyond.
Initial projects may include collaborations to predict protein structures, screen ligand-base pairs and accelerate molecular dynamics simulations with trusted services. Tokyo-1 users can harness large language models for chemistry, protein, DNA and RNA data formats through the NVIDIA BioNeMo drug discovery microservices and framework.
Conclusion
Xeureka’s innovative approach to confidential computing and AI has the potential to revolutionize the pharmaceutical industry. By leveraging NVIDIA H100 Tensor Core GPUs and Fortanix security management software, Xeureka has demonstrated the ability to improve model accuracy while maintaining data privacy.
This breakthrough has far-reaching implications for the development of new treatments and therapies, and Xeureka is poised to play a leading role in shaping the future of healthcare.
FAQs
Q: What is Xeureka?
A: Xeureka is a new subsidiary of Mitsui & Co that aims to accelerate R&D in healthcare using new technologies like generative AI and confidential computing.
Q: What is confidential computing?
A: Confidential computing is a way of processing data in a protected part of a GPU or CPU that acts like a black box for an organization’s most important secrets.
Q: How does Xeureka use confidential computing?
A: Xeureka uses confidential computing to allow its customers to safely share data, ensuring that private patient information and chemical formulas remain protected.
Q: What are the benefits of Xeureka’s approach?
A: Xeureka’s approach has the potential to improve model accuracy by up to 74%, while maintaining data privacy. This breakthrough has far-reaching implications for the development of new treatments and therapies.
