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Application of Analytical Measurement Uncertainty and Considerations toward Pharmaceutical Material Quality Control
Michael A Zompa1, Dolee Merai1, Paul Oram1
1Analytical Research and Development, MRL, Merck & Co., Inc., Rahway, New Jersey 07065, United States.
Analytical Chemistry
|December 29, 2025
Summary
This study presents a method to set acceptance limits for pharmaceutical testing, accounting for measurement uncertainty. This approach enhances confidence in material quality and supports integrated control strategies.
Area of Science:
- Pharmaceutical Science
- Analytical Chemistry
- Quality Control
Background:
- International Council for Harmonisation (ICH) Q14 and United States Pharmacopeia (USP) <1220> provide guidance on measurement uncertainty.
- Measurement uncertainty significantly impacts decisions in pharmaceutical material assessment.
- Existing methods may not fully integrate uncertainty into acceptance criteria.
Purpose of the Study:
- To demonstrate an approach for setting acceptance limits that incorporate analytical measurement uncertainty.
- To establish an integrated control strategy for pharmaceutical materials.
- To reinforce confidence in the quality of pharmaceutical materials through uncertainty-aware decision-making.
Main Methods:
- Utilized case studies to illustrate the proposed methodology.
- Developed a framework for setting acceptance limits considering measurement uncertainty.
- Integrated the uncertainty-aware limits into a broader control strategy.
Main Results:
- Successfully demonstrated the application of the approach in case studies.
- Showcased how to accommodate analytical measurement uncertainty in acceptance limits.
- Established a clear link between uncertainty management and enhanced material quality confidence.
Conclusions:
- The proposed approach effectively integrates analytical measurement uncertainty into acceptance limit setting.
- Implementing this method strengthens the overall control strategy for pharmaceutical materials.
- This approach provides a robust framework for improving decision-making and ensuring pharmaceutical quality.
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