Donovan Anderson
- Name of university
- Hirosaki University
- Belongs
- Institute of Radiation Emergency Medicine
- Position
- Assistant Professor
- Platform
- Life and Environments
Research Fields
Radiation Biology and Biological Dosimetry
Research Keywords
Radiation Biology and Biological Dosimetry
Cytogenetics
Radiation Biology
Research Subject
Development of Scalable and Standardized Biodosimetry Platforms for Emergency and Public Health Applications
Research Outline
Radiological and nuclear emergencies require rapid and accurate assessment of individual radiation exposure to guide medical treatment and emergency response. Cytogenetic biodosimetry provides the international gold standard for biological dose estimation, but current methods are often limited by lengthy cell culture procedures and inconsistent lymphocyte growth, reducing their effectiveness during large-scale emergencies.
My research aims to develop high-efficiency lymphocyte culture systems using serum-free and chemically defined media to improve cell proliferation and increase the mitotic index while maintaining the accuracy of chromosome aberration analysis. By improving the reliability and scalability of these techniques, the project seeks to establish standardized biodosimetry platforms suitable for both emergency response and routine public health applications. International collaboration will support validation across multiple laboratories and populations, while emerging artificial intelligence approaches will be explored to improve image analysis and standardization.
My research aims to develop high-efficiency lymphocyte culture systems using serum-free and chemically defined media to improve cell proliferation and increase the mitotic index while maintaining the accuracy of chromosome aberration analysis. By improving the reliability and scalability of these techniques, the project seeks to establish standardized biodosimetry platforms suitable for both emergency response and routine public health applications. International collaboration will support validation across multiple laboratories and populations, while emerging artificial intelligence approaches will be explored to improve image analysis and standardization.