Analysis methodology and development of a statistical tool for biodistribution data from internal contamination with...

Area of Science:

• Radiological Sciences
• Computational Biology
• Toxicology

Background:

• Biodistribution data from internal contamination experiments are crucial for understanding contaminant behavior.
• Analyzing diverse and large datasets poses significant challenges.
• Existing methods often lack efficiency and standardization.

Purpose of the Study:

• To develop a computational tool for statistical analysis of biodistribution data.
• To facilitate handling and comparison of data from various experimental conditions.
• To improve the understanding of actinide biokinetics and inform medical countermeasures.

Main Methods:

• Development of functional modules using the R programming language.
• Implementation of descriptive statistics, visual comparison, curve fitting, and biokinetic modeling.
• Harmonization of dataset structures and automated generation of graphical outputs.

Main Results:

• A user-friendly computational tool integrating multiple statistical analyses was created.
• The tool streamlines data handling, analysis, and comparison.
• Generated outputs include text files, harmonized data tables, and graphical representations.

Conclusions:

• The developed tool significantly enhances the efficiency and reproducibility of biodistribution data analysis.
• It facilitates re-analysis of archival data and comparison across different experimental sources.
• This work aids in understanding contamination characteristics' influence on actinide biokinetics, supporting optimized treatment protocols.