Maximizing the Accuracy of NGI Results: A Focus on Resolving User-Based Limitations.

Abstract: The Next Generation Impactor (NGI) is a widely used cascade impactor for determining the aerodynamic particle size distribution of orally inhaled products like metered-dose inhalers and dry powder inhalers. While the NGI offers advantages over previous impactors, users can still encounter issues that affect the accuracy and reliability of the results. This article examines common user issues with the NGI, their potential impacts on aerodynamic particle size distribution (APSD) measurements and other outcomes, and strategies for investigating these issues through effective data analysis. Understanding and mitigating user issues is crucial for ensuring the NGI generates high-quality, reproducible data to support orally inhaled product development and quality control.

Introduction: Accurate determination of the APSD is a critical requirement for orally inhaled product development, as it governs the amount of drug that can reach the lungs for therapeutic effect. The NGI has emerged as an important tool due to its improved sizing capabilities and operating principles compared to previous cascade impactors.

However, the NGI is a complex apparatus involving many components, operating parameters, and procedural steps. This complexity creates opportunities for user errors and other issues to arise, which can compromise APSD measurements. Identifying and addressing these user issues is essential for generating reliable NGI data to make sound product development decisions.

Common User Issues:

1. Improper NGI setup and assembly Deviations from specified configurations for components like induction ports, cups, plates, and seals can create particle losses, air leaks, and re-entrainment of particles from one stage to another. This distorts the measured APSD.
2. Environmental condition deviations Temperature and humidity significantly influence NGI operating conditions like airflow rates. Deviations from specified environmental conditions can alter aerosol particle behavior and APSD measurements.
3. Inadequate flow rate control Inconsistent or inaccurate flow rates through the NGI disrupt its size separation principles, resulting in APSD measurement errors. Poor flow control may be caused by leaks, obstructions, or incorrect settings.
4. Handling errors Mishandling the NGI pre-test, mid-test, or post-test can lead to particle losses, re-entrainment events, or other unpredictable effects on the APSD.

Impact on Outcomes: Aerodynamic particle size distribution measurements...

Impact on Outcomes: Aerodynamic particle size distribution measurements are critical for ensuring an orally inhaled product can effectively deliver the therapeutic agent to the lungs. An inaccurate APSD may indicate the wrong fraction of particles in the respirable size range, potentially leading to underdosing or overdosing of patients. This could reduce or eliminate the product's therapeutic efficacy, or potentially cause adverse effects.

User issues with the NGI can also negatively impact in vitro dose delivery results, which are used to guide product formulation and design iterations. If NGI issues distort the measured dose delivery, developers may make misguided adjustments detrimental to the product's performance.

Taken together, user-related issues with the NGI hold the potential to misdirect costly product development activities and regulatory submissions if not promptly detected and addressed. This underscores the importance of rigorous NGI data investigation practices.

Analyzing NGI Data to Investigate Issues: While some user issues may be evident from visual inspection of the NGI apparatus itself, many are more subtle and can only be detected through careful analysis of the APSD and dose delivery data. This analysis should scrutinize key NGI metrics and benchmark them against prior data, expected values, and specified limits:

• Mass balance: Significant mass missing or gained across the NGI stages
• Size distribution shape: Unexpected distortions or discontinuities
• Inter-stage correlations: Deviations from typical cumulative mass vs. stage relationships
• Flow rate consistency: Fluctuations beyond expected variability
• Environmental monitoring: Excursions in temperature, humidity, etc.

Statistical process control methods and engineering first principles can support rigorous data interrogation to isolate root causes of deviations.