| Molybdenum (Mo) is an essential trace element for humans and animalsand is required for the function of four enzymes found in humans.Molybdenum-99 is among the most important radionuclidesin radiological protection because it decays with a 66-hour half-life by isobaric decay emitting a negatron. But, more importantly it is the decay precursor of metastable Technicium-99 which arguably is among the most important radionuclides used for diagnostic nuclear medicine. Molybdenum-99has the potentialto be released in the environment in large amounts as a result of accidents in nuclear power plants, nuclear medical installations or in transportation accidents, consequently it is considered a potential occupational orpublic health concern. The goal of this study was to develop a physiologically based methodology for describing the metabolic behavior of molybdenum within the human body from occupational, environmental, and medical exposure. Current internal dosimetry biokinetic models describe the distribution, clearance, and organ retention of internalized radioactive materials. These models are most frequently developed using bioassay data. Parameter are added to these models to enhance fits to measured bioassay parameters. However, physiologically based pharmacokinetic (PBPK) modeling was used in this study to understand the behavior of molybdenum within the human body.PBPK models seek to fundamentally measure and understand organ kinetics. This approach could enhance understanding of organ retention and excretion and ultimately improve the predictive capability of current internal dosimetry biokinetic models. The International Commission on Radiological Protection’s (ICRP) molybdenum model and the Giussani molybdenum model were reconstructed in the SAAM IIsoftware. Eight and six compartmental PBPK models (model-A, and model-B) were proposed in this project. To test the validity of the purposed models, model-A and model-B
xiiwere developed in a format compatible with the SAAM II software. The Akaike Information Criterion (AIC) statistic was used to quantitatively evaluate the quality of the models. The AIC values were obtained from the software and were used to find the best fits. Based on the AIC values, it was concluded that the ICRP model wasthe least favorable model, and that model-A was more favorable model.KeyWords:Molybdenum, Compartmental model, Internal Dosimetry, PBPK,biokinetic model, AIC, SAAM II. |