Analytical Challenges of Spray Pattern Method Development for Purposes of Bioequivalence Testing in the Case of a Nasal Spray Product.

A spray pattern (SP) test is one of the most challenging tests for nasal spray products (NSPs) associated with a high degree of variation. The total results variation observed in such studies should be in major part representative of product performance to assure high confidence when making conclusions based on obtained results. Analytical methods should be developed in a way to minimize variation contribution of random factors. A systematic statistical assessment of sources of variation is encouraged to be performed during any method development. This study includes the development of a product-shaking procedure, definition of relevant actuation parameters, and the development of a robust SP method considering NSP behavior. The final SP method is tested on different days and in different laboratories to evaluate the contribution of individual factors and interactions to the observed variance in SP using a gauge repeatability and reproducibility (GRR) model. It was found that the time lag between consecutive actuations significantly influences the variability of the SP area, suggesting the importance of determining a recovery period. Factor analyst was not found to be important. Factor day was found to have the potential to impact results, mostly through interactions with other factors, suggesting that one should pay attention when performing any comparative studies within the same laboratory on different days. Significant differences were observed when the same product was tested in different laboratories. Key random factors, which significantly contribute to total variation, were identified using a GRR approach. By applying an appropriate control strategy over these factors, one can assure that assessed total variation can be representative of product performance. The same general approach is not only applicable to development of SP method for NSP but to all types of analytical testing as well.