# Metrological Evaluation of Metopimazine HPLC Assay: ISO-GUM and Monte Carlo Simulation Approaches

## TL;DR

This paper evaluates the uncertainty in an HPLC method for measuring Metopimazine using two approaches, showing that sample volume and calibration standards are the main sources of uncertainty.

## Contribution

The study demonstrates the agreement between ISO-GUM and Monte Carlo Simulation approaches in evaluating measurement uncertainty for Metopimazine HPLC assays.

## Key findings

- Sample volume and calibration standard accuracy contribute 76.1% of the total uncertainty.
- The expanded uncertainty was determined to be (99.41 ± 0.69)% at 95% confidence level.
- Both ISO-GUM and Monte Carlo Simulation approaches showed excellent agreement in uncertainty evaluation.

## Abstract

Background: Measurement uncertainty (MU) is a crucial parameter for ensuring the reliability of analytical methods and the validity of results, as required by ISO 17025:2017. Its estimation is particularly critical for quality control laboratories, where compliance decisions are based on a rigorous interpretation of uncertainties. Methods: In this study, we evaluated the uncertainty associated with an HPLC-UV method for the determination of Metopimazine (MPZ) in a pharmaceutical form, applying two complementary approaches: The ISO-GUM (Guide to the Expression of Uncertainty in Measurement) top-down approach and the Monte Carlo Simulation (MCS). Results: The results of both approaches showed excellent agreement, thus validating the robustness of the evaluation. The analysis of uncertainty sources revealed that the accuracy of the sample volume (VSample) and the calibration standard (Cx) were the dominant contributors, representing 39.9% and 36.2% of the total uncertainty, respectively. Combined, these two factors accounted for 76.1% of the variability, underscoring their critical impact on the assay’s precision. The expanded uncertainty (k = 2, 95% confidence level) was determined to be (99.41 ± 0.69)%, reflecting the method’s reproducibility. Conclusions: These results highlight the importance of rigorously controlling calibration standard preparation, sample volume, and repeatability conditions to optimize the reliability of the assay.