BACKGROUND: The aim of this work is to use an experimental design approach to identify and study influential formulation and delivery device properties, which can be controlled by final product manufacturer, to establish design space, within which desired in vitro performance can be reached. METHODS: Combining three factors, viscosity of suspension, nozzle orifice diameter (OD), and shot weight (SW), at three levels resulted in D-optimal experimental design with 20 runs. Responses within this study were droplet size distribution (DSD) and spray pattern (SP) in vitro tests. In addition, the amount of mechanical work needed for actuation was integrated from force profiles and used as a response. Results were fit to quadratic model by regression, which allowed also for determination of second-order and interaction effects between factors. Models were further optimized by keeping significant terms only. Optimized models were used to create response surfaces and design space with confidence levels. RESULTS: Viscosity has a dominant effect on DSD and modest effect on SP, with lower viscosities related to generation of smaller DSD and larger SP. Orifice diameter was found to have the highest impact on SP, with larger diameter resulting in larger SP. This effect was additionally confirmed by results of Plume Geometry in vitro test. Shot weight factor exerts significant influence on all tested metrics. Work, however, did not vary greatly with suspension viscosity or orifice diameter. Shot weight is the most dominant factor for work and important for DSD having a positive effect on both responses. In the case of SP, its relationship with shot weight is described by second-order polynomial fit. Inspection of raw data revealed that density of droplets within SP area is different for different shot weights. CONCLUSION: Presented study elucidated an inherent relationship between factors and responses and established mathematical models (response surfaces) for predictive purposes to target specific in vitro performance of nasal sprays by appropriate specification of factors, taking into account control space with included risk and uncertainty analysis.
BACKGROUND: The aim of this work is to use an experimental design approach to identify and study influential formulation and delivery device properties, which can be controlled by final product manufacturer, to establish design space, within which desired in vitro performance can be reached. METHODS: Combining three factors, viscosity of suspension, nozzle orifice diameter (OD), and shot weight (SW), at three levels resulted in D-optimal experimental design with 20 runs. Responses within this study were droplet size distribution (DSD) and spray pattern (SP) in vitro tests. In addition, the amount of mechanical work needed for actuation was integrated from force profiles and used as a response. Results were fit to quadratic model by regression, which allowed also for determination of second-order and interaction effects between factors. Models were further optimized by keeping significant terms only. Optimized models were used to create response surfaces and design space with confidence levels. RESULTS: Viscosity has a dominant effect on DSD and modest effect on SP, with lower viscosities related to generation of smaller DSD and larger SP. Orifice diameter was found to have the highest impact on SP, with larger diameter resulting in larger SP. This effect was additionally confirmed by results of Plume Geometry in vitro test. Shot weight factor exerts significant influence on all tested metrics. Work, however, did not vary greatly with suspension viscosity or orifice diameter. Shot weight is the most dominant factor for work and important for DSD having a positive effect on both responses. In the case of SP, its relationship with shot weight is described by second-order polynomial fit. Inspection of raw data revealed that density of droplets within SP area is different for different shot weights. CONCLUSION: Presented study elucidated an inherent relationship between factors and responses and established mathematical models (response surfaces) for predictive purposes to target specific in vitro performance of nasal sprays by appropriate specification of factors, taking into account control space with included risk and uncertainty analysis.
Authors: Sherryl Baxter; Ben Myatt; Stephen Stein; Adrian Parkinson; Frank Chambers; Bill Doub; Jernej Grmas; Julie Suman; Keith Miller; Biswadip Sinha; Linda Liao; Ian Carter; Dino Farina; Segolene Sarrailh; Manfred Fischer; Declan Walsh; Lee Nagao Journal: AAPS PharmSciTech Date: 2022-05-18 Impact factor: 3.246