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COMPUTATIONAL TOXICOLOGY: AN IN SILLICO DOSIMETRY MODEL FOR THE ASSESSMENT OF AIR POLLUTANTS
Citation:
Martonen, T B. AND K K. Isaacs. COMPUTATIONAL TOXICOLOGY: AN IN SILLICO DOSIMETRY MODEL FOR THE ASSESSMENT OF AIR POLLUTANTS. Presented at 12th International Conf. on Modelling, Monitoring, and Management of Air Pollution, Rhodes, Greece, June 28-July 2, 2004.
Description:
To accurately assess the threat to human health presented by airborne contaminants, it is necessary to know the deposition patterns of particulate matter (PM) within the respiratory system. To provide a foundation for computational toxicology, we have developed an in silico model which describes the behavior and fate of inhaled PM. It is intended to be employed in a complementary manner with human subject experiments. The key components of the model are algorithms defining the morphology of the respiratory system, breathing conditions, and PM characteristics. The model gives spatial deposition patterns within human lungs, moreover local doses delivered to airways are calculated per unit surface area. This is of special importance because natural PM removal (i.e., clearance) processes vary with locations within lungs. For example, in tracheobronchial (TB) airways PM is cleared within about 24 hours by the mucociliary mechanism but PM deposited in pulmonary (P) airways may not be removed by macrophage action for several days. The salient point to be made is that the toxicity of air pollutants can be directly related to sites of initial deposition and local doses within human lungs. The PM in silico dosimetry model defined herein will permit air pollution risk assessment protocols to be put on a scientific basis, and will provide a solid foundation for the determination of ambient air quality standards.