In silico investigation of inhalation condition impacts on hygroscopic growth and deposition of salbutamol sulphate in human airways.

The objective of this study is to explore the transport, size growth, and deposition of Salbutamol Sulphate (SS) using Computational Fluid Dynamics (CFD). A CT-based realistic model of human airways from the oral cavity to the 5th generation of the lung was utilized as the computational domain. Four Test Cases (TC) with varying temperature and relative humidity (RH) under two inspiratory waveforms were considered to completely evaluate the impact of inhalation conditions on particle growth. Salbutamol Sulphate (SS) is a ß2-adrenergic agonist and has been extensively used for asthma treatment. A monodispersed distribution of SS particles with an initial diameter of 167 nm was considered at the mouth inlet based on pharmaceutical data. Results indicated that inhalation of saturated/supersaturated air (RH>100%) leads to significant hygroscopic growth of SS particles with a factor of 10. In addition, the deposition efficiency of SS particles under the Quick and Deep (QD) inhalation profile was enhanced as the flow temperature and humidity increased. However, the implementation of Slow and Deep (SD) inspiratory waveform revealed that the same particle size growth is achieved in the respiratory system with lower deposition efficiency in the mouth-throat (less than 3%) and tracheobronchial airway (less than 2.18%). For the escaped particles form the right lung, in the SD waveform under TC 3, the maximum particle size distribution was for 600 nm particles with 25% probability. In the left lung, 30% of the particles were increased up to 950 nm in size. For the QD waveform in TC 3 and TC4, the most frequent particles were 800 nm with 36% probability. This holds practical significance in the context of deep lung delivery for asthmatic patients with enhanced deposition efficiency and large particle size. The findings of the present study can contribute to the development of targeted drug delivery strategies for the treatment of pulmonary diseases using hygroscopic dry powder formulations.

Numerical analysis of an obstacle motion in the human ureter using the dynamic mesh approach.

Peristalsis is a common motion in various biological systems, especially the upper urinary tract, where it plays a pivotal role in conveying urine from the kidneys to the bladder. Using computational fluid dynamics, this study aims to investigate the effect of various peristaltic parameters on the motion of an obstacle through a two-dimensional ureter. Methodologically, Incompressible Navier-Stokes equations were utilized as the fluid domain's governing equations, and the Dynamic Mesh method (DM) was employed to simulate the peristaltic and obstacle motion. The peristaltic motion was modeled by a sinusoidal contraction wave propagating alongside the ureter at the physiological speed, and the motion of the obstruction through the ureter, which is caused by the fluid forces applied on its surface, was explored using the equation of Newton's second law. Various test cases of different shapes and sizes were supposed as kidney stones to understand the influence of the peristalsis properties on the stone removal process. The results show that the motion of the kidney stone is highly influenced by the gradient pressure force applied to its surface in the fluid domain. Moreover, investigating the effects of the peristaltic physical properties on the obstacle's motion indicates that the stone's motion is dependent on these parameters. Furthermore, this analysis provides insight into the peristaltic motion effects, assisting physicians in developing new medicines to facilitate the kidney stone removal process based on its shape and size.