DEVELOPING COMPUTATIONAL METHODS TOPREDICT THE FATE OF INHALED PARTICLES IN THELUNG

The respiratory system can be targeted by many different types of diseases, for example asthmaand cancer. The drug delivery method by inhaling substances for treating diseases only started in the 1950s with the treating of asthma, considered also for many other diseases. Mathematical dosimetry models are used in drug development to predict the deposition of particles in the lungs. This prediction is not easily achieved experimentally, and therefore these mathematically models are of high importance. Monkeys are often used in the late stages of drug development due to their resemblance in humans. A good model for predicting the deposition pattern in monkeys is therefore useful in the development of drugs. However, there is at the moment no developed deposition mode lfor monkeys. In this thesis both a static model and the first dynamic deposition model was developed sing the data on the breathing pattern from respiratory inductance plethysmography (RIP) bands. This dynamic model provides regional and time resolved information on the particle deposition in the lungs of monkeys and can be used to get a deeper understanding of the fate of inhaled particles. This model can also determine inter-animals differences which have not been achieved before. An extensive implementation of these time resolved deposition models could be used to increase understanding about deposition in a variety of species and help the field to move forward