Computer modeling of airway deposition distribution of Foster(®) NEXThaler(®) and Seretide(®) Diskus(®) dry powder combination drugs.

Asthma is a serious global health problem with rising prevalence and treatment costs. Due to the growing number of different types of inhalation devices and aerosol drugs, physicians often face difficulties in choosing the right medication for their patients. The main objectives of this study are (i) to elucidate the possibility and the advantages of the application of numerical modeling techniques in aerosol drug and device selection, and (ii) to demonstrate the possibility of the optimization of inhalation modes in asthma therapy with a numerical lung model by simulating patient-specific drug deposition distributions. In this study we measured inhalation parameter values of 25 healthy adult volunteers when using Foster(®) NEXThaler(®) and Seretide(®) Diskus(®). Relationships between emitted doses and patient-specific inhalation flow rates were established. Furthermore, individualized emitted particle size distributions were determined applying size distributions at measured flow rates. Based on the measured breathing parameter values, we calculated patient-specific drug deposition distributions for the active components (steroid and bronchodilator) of both drugs by the help of a validated aerosol lung deposition model adapted to therapeutic aerosols. Deposited dose fractions and deposition densities have been computed in the entire respiratory tract, in distinct anatomical regions of the airways and at the level of airway generations. We found that Foster(®) NEXThaler(®) deposits more efficiently in the lungs (average deposited steroid dose: 42.32±5.76% of the nominal emitted dose) than Seretide(®) Diskus(®) (average deposited steroid dose: 24.33±2.83% of the nominal emitted dose), but the variance of the deposition values of different individuals in the lung is significant. In addition, there are differences in the required minimal flow rates, therefore at certain patients Seretide(®) Diskus(®) or pMDIs could be a better choice. Our results show that validated computer deposition models could be useful tools in providing valuable deposition data and assisting health professionals in the personalized drug selection and delivery optimization. Patient-specific modeling could open a new horizon in the treatment of asthma towards a more effective personalized medicine in the future.