Recently, a customer called our Technical Support team about a Design of Experiment he was performing in Minitab Statistical Software. After they helped to answer his question, the researcher pointed our team to an interesting DOE he and his colleagues conducted that involved using nasal casts to predict the drug delivery of nasal spray.
The study has already been published, and you can read more about it here, but I wanted to highlight this use of the DOE tools in Minitab in this blog post.
Using Nasal Casts to Predict Nasal Spray Drug Delivery
The nose is a convenient route of administration for delivering drugs that treat respiratory ailments. For example, nasal sprays target and deliver drugs to regions of the nasal cavity that become irritated by allergens such as pollen and pet dander. But evaluating the ability of new nasal delivery technologies to accurately target specific regions in the nasal cavity is complicated, and clinical trials that do so can be expensive, time-consuming, and offer only qualitative findings.
Alternatively, researchers can predict regional deposition using nasal casts. The casts mimic the anatomy of human nasal passages and can be tested under controlled conditions. Nasal casts provide a cost-effective and simpler way to test and optimize device and formulation factors that affect drug delivery. Nasal casts also have the potential to let researchers precisely measure how much of a nasal spray reaches a given region of the nose, which could allow for more efficient treatment of diseases in the nasal cavity and fewer side effects.
Here’s an image of the various sections of a nasal cast:
For a nasal cast to be effective at predicting deposition, and for use in optimizing new nasal spray devices, it needs to be set up to mimic human deposition. As an “in-vitro,” or simulation, tool, there were many settings to consider.
How Minitab Helped
To evaluate different settings on the nasal cast that would be most predictive of human deposition, the research team developed success criteria from several published nasal spray deposition studies conducted on humans. These studies gave them an understanding of the different regions of the cast where they could expect to see drug deposition, as well as insight into the total percentage of the drug that was being deposited into the various nasal regions after the spray was used. Their goal was to adjust the settings on the cast to get a deposition pattern of the drug that was similar to what you would see in humans. They wanted the settings to be repeatable, in order to prove that nasal casts could be used as a cost-effective way to compare new device and formulation technologies for nasal drug delivery.
The nasal cast the team used, which was made of nylon, was created based on 3D computer images of the nasal cavities of healthy humans. The cast was made up of five regions that mimic the human nasal cavity, which were coated with a special solution to simulate the mucus in human nasal passages. After assembling and orienting the cast, a model nasal spray formulation was sprayed into it. To analyze the spray’s deposition, the cast was disassembled and the amount of drug that reached each region was measured using a technique known as an HPLC, or high-pressure liquid chromatography.
To identify which factors were significant, and to reduce the number of factors they needed to optimize, the team used Minitab’s DOE tools to collect information on the ranges of factors influencing the deposition of spray droplets throughout the nasal cast.
With a designed experiment, researchers can change more than one factor at a time, and then use statistics to determine which factors have significant effects on an outcome. Using a DOE reduces the number of experimental runs needed to gather reliable data, making studies less expensive and more efficient.
In situations where many factors or settings need to be considered, an exploratory or screening experiment can help researchers determine which to focus on. The team began with an exploratory DOE—a full factorial with five sets of spray angles, three airflow rates, and two speeds, but no repeats. Once the range was determined, they used a half-factorial design to screen the important factors identified in the exploratory experiments.
Main effects plots of the half factorial DOE showed how different levels of each factor affected the various nasal cast components.
The team conducted additional optimization experiments to examine the effect of different levels of the significant factors on deposition. They chose two factors—airflow time and tilt angle—for follow-up experiments because they appeared to affect deposition the most.
After collecting the additional data about these two factors, the team used Minitab’s Response Optimizer to identify the optimal settings for the airflow time and tilt angle. Using the optimized settings, two operators tested two nasal casts five times, and the team performed Gage R&R analysis in Minitab to determine if either the operator or cast were causing any variation in the process.
A Minitab Bar Chart of mean percent deposition in different regions of the nasal cast showed the team that deposition patterns from their experiments were meeting success criteria for predicting human deposition.
The studies showed that neither nasal cast nor operator had a significant effect on nasal deposition in any of the cast regions, and the Gage R&R analysis revealed that with optimal settings, the nasal cast provided a robust measurement system for deposition within the nasal cast.
A 'Cost-Effective' Cast
The optimized settings for the nasal cast produced repeatable results, and proved that the cast could be used to cost-effectively compare new nasal spray devices and formulations that target specific regions of the nasal cavity. Although a nasal cast cannot be used to predict clinical response, nasal casts could be used in combination with clinical studies to relate biological drug response to the drug deposition pattern in accord with nasal spray use.
Research discussed here was originally published in the Journal of Aerosol Medicine and Pulmonary Drug Delivery, March 2013: “Design of Experiments to Optimize an In Vitro Case to Predict Human Nasal Drug Deposition.”