Spray Pattern and Plume Geometry Testing and Methodology: An IPAC-RS Working Group Overview.

Plume characterization for orally inhaled and nasal drug products (OINDP) provides valuable information during OINDP development. Spray pattern and plume geometry techniques, methods, and technology have evolved over the past 20 years since the publication of the original 1998 FDA MDI DPI draft guidance. The International Pharmaceutical Aerosol Consortium on Regulation and Science (IPAC-RS) discusses the historical context and background to plume geometry and spray pattern characterization studies; provides an analysis of the current regulatory context; addresses results from its industry surveys on application and value of such testing; and presents case studies and best practices-seeking to provide insights to regulatory bodies and other stakeholders. Assessment and consideration of published studies and industry experience note the value of plume geometry and spray pattern in development, and that further data is needed regarding their use in assessing formulation characteristics. Continued dialogue between industry and regulatory bodies is needed to establish the optimum use of these techniques.

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

Background: A spray pattern (SP) test is one of the most challenging in vitro 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. Methods: This study includes the development of a product-shaking procedure, definition of in vivo 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. Results: 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. Conclusion: 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.

A Novel Simulation-Based Approach for Comparing the Population Against Average Bioequivalence Statistical Test for the Evaluation of Nasal Spray Products on Spray Pattern and Droplet Size Distribution Parameters.

The aim of this work is to evaluate average bioequivalence (ABE) and population bioequivalence (PBE) statistical approaches so as to identify which approach is most suitable for in vitro bioequivalence (IVBE) testing of nasal spray products. For droplet size distribution (DSD) and spray pattern (SP), in vitro data were collected using a well-established nasal spray on the market (Nasonex®, manufactured by Merck Sharp & Dohme Limited). Simulations were performed using in vitro data to comparatively investigate ABE and PBE tests. For highly variable parameters such as SP area, this study clearly demonstrates that the level of agreement between ABE and PBE test conclusions is much smaller as compared with that of DSD Dv(50), which was found to have moderate variability. PBE approach dictates equivalence for both means and variances, and was found to handle both SP and DSD parameters with similar passing rates compared to the passing rates from the ABE approach. However, pronounced asymmetric behavior of PBE empirical power curves for highly variable SP area was observed. A modified PBE statistical approach is proposed for DSD span and Dv(50) in vitro parameters, where acceptance criteria would be based on comparison of reference/branded product to itself as part of "pre-IVBE study" via innovative statistical bootstrap simulations. Due to inherent high variability of the SP area parameter driving pronounced asymmetric behavior of PBE power curves, and due to unclear in vivo relevance for SP area and ovality, authors propose that SP parameters be used as development and quality control tools rather than for demonstration of IVBE.

Elucidation of Formulation and Delivery Device-Related Effects on In Vitro Performance of Nasal Spray with Implication to Rational Product Specification Identification.

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.

Using different experimental designs in drug-excipient compatibility studies during the preformulation development of a stable solid dosage formulation.

Different types of factorial experimental designs can be used in compatibility studies of drug development, where many different factors and their interactions should be evaluated to predict their effects on the degradation of the drug substance under study. All possible main and interaction effects of different potential excipients that can constitute the drug product should be evaluated in order to select the best combination of excipients that give the lowest possible degradation, i.e., the most stable drug product. Statistical experimental designs enable the user to obtain the maximum amount of information, i.e., the degradation effects of excipients and their interactions on the stability of the drug substance, on the basis of the smallest possible number of experiments. The use of full and two different fractional factorial designs is described using a real example where the excipients that stabilize the drug substance or cause as little degradation as possible are selected for a solid dosage formulation. It was shown that the type and the sequence of design used during the studies are also important to get reliable and valuable results. A thorough explanation of the statistical evaluation of data and different presentations of final solutions are given.