Clinical research forms the foundation for integrating genomics into clinical care. This article provides a brief overview of the clinical research bioinformatics market in Japan, with a focus on oncology and rare disease applications. Please refer to the “DNA Sequencing for Non‑Biologists” article for any unclear terms.
What is Clinical Research Bioinformatics
The scope of clinical research bioinformatics in this article will be around finding disease‑causing variants from genomic data, in the oncology and rare disease context, for the purpose of generating scientific knowledge. Clinical research is not to be confused with clinical care, as clinical research focuses on scientific knowledge generation, whereas clinical care focuses on patient care. Japanese regulation practically allows only IVD‑approved products for clinical care usage, thus the difference between clinical research and clinical care can be considered as whether we are dealing with RUO or IVD products. I will discuss the bioinformatics of clinical research in three sections: secondary analysis, tertiary analysis, and data management.
Secondary Analysis Market Overview
Secondary analysis converts raw sequencing read data into more interpretable variant data through the process of mapping and variant calling. The secondary analysis market can be divided into two parts: open‑source and commercial.
Open‑source tools are favored by academic labs and hospitals with bioinformaticians running small panels and exomes. Labs with existing bioinformatics capability are generally reluctant to make additional investment. Small gene panels and exomes also produce relatively small data sizes, so large computing and storage resources are not necessary.
Commercial tools are sometimes used by larger labs, such as national research centers and commercial facilities that run whole‑genome sequencing, for scalability and ease of use. Most labs are not equipped to run whole‑genome sequencing (WGS) at scale. WGS data is massive and can take hours to process a single sample. Commercial tools address this through hardware acceleration (GPU, FPGA), which speeds up the analysis, and the use of cloud. Cloud platforms provide computing and storage resources on demand, removing the need for onsite infrastructure and physical space. Commercial solutions are also generally easier for non‑bioinformaticians to use, with built‑in features such as graphical user interfaces, version management, and user management.
Tertiary Analysis Market Overview
Tertiary analysis tries to find the disease‑causing variant by annotating these variants with interpretive information, filtering these variants, and then sometimes reporting the findings.
Between oncology and rare disease, oncology is the larger market. In Japan, approximately 1.0 million new cancer patients are diagnosed each year, and there are about 1.1 million rare‑disease patients in total at the 2025 timepoint. Cancer is fundamentally a genetic disease that benefits from genetic testing, whereas not all rare diseases are genetic.
Commercial tools are used more often for tertiary analysis than for secondary analysis. This is because tertiary analysis is an interpretation task performed by genomic scientists and doctors, and these end users value intuitive user interfaces and clear report design, something bioinformaticians do not generally optimize. Some companies offer a single tool that supports both oncology and rare‑disease interpretation, given the overall similarity of the workflows. However, others develop separate tools for each application, or focus exclusively on one, because the databases used for annotation and the variant‑filtering strategies differ substantially between oncology and rare disease.
On Compliance Surrounding Genomic Data Management
Genomic data is personal information, so careful handling is necessary. Genomic data can be stored either on‑premise or in the cloud. Keeping genomic data on‑premise is generally easier from a compliance standpoint, as companies traditionally managed sensitive information within their own infrastructure. Moving data to the cloud means uploading it to an external server, which introduces perceived confidentiality risks. However, due to the size of genomic datasets, especially WGS, cloud will likely become the natural option going forward.
Putting genomic data in the cloud requires careful compliance with data security and privacy standards. Some countries allow the use of cloud solutions certified under international standards such as ISO 27001 and ISO 27701, which define requirements for information security and privacy. However, Japan has its own guidelines for handling genomic information. “Two Guidelines from Three Ministries” (2G3M) is the most relevant data‑handling guideline in the genomic context. 2G3M was established by the Japanese government to ensure the safe management and privacy of electronic medical records and health data. These guidelines require cloud service providers to prepare and maintain documentation demonstrating that their systems conform to the standards defined by the government. As a result, global healthcare‑related cloud providers operating in Japan need to consider allocating additional resources to meet these standards.
Summary
Clinical research bioinformatics in Japan is shaped by the growing scale of genomic data and the country’s unique regulatory environment. Clinical research bioinformatics spans secondary analysis, tertiary interpretation, and genomic data management. Smaller labs with bioinformatic capability running panels and exomes often rely on open‑source secondary analysis, while larger institutions running WGS sometimes adopt commercial solutions for scalability and usability. Commercial tools are used more often for tertiary analysis, reflecting end users’ need for intuitive and simple solutions. Underpinning all segments is secure data management, with Japan having its own standard. I hope you find something useful.