Measurement uncertainty evaluation of an analytical procedure for determination of terbinafine hydrochloride in creams by HPLC and optimization strategies using Analytical Quality by Design

Author(s)

Separovic, Luciana ; Lourenco, Felipe Rebello

• Document type: Journal article
• Source: Microchemical Journal; v. 178, p. 13-pg., 2022-07-01.

Abstract

The measurement uncertainty (MU) evaluation is important to ensure the analytical procedure performance, since the higher the uncertainty value the lower the reliability of the analytical result, leading to the risks of false decision in conformity assessment. Therefore, when an analytical procedure provides results with MU value above the recommended, it is necessary to adopt optimization strategies to improve the performance. Thus, this work aimed to evaluate the MU and the individual sources of uncertainty, as well as to propose optimization strategies using Analytical Quality by Design (AQbD) approach, considering an analytical procedure for the determination of terbinafine hydrochloride in creams by HPLC. Initially, the MU was estimated by top-down approach, based on trueness and precision data. Then, the MU was estimated by bottom-up approach, allowing the identification and quantification of the sources of uncertainty, which was used as a basis for the design of experiments, along with factors that influence the chromatographic responses. The regression models obtained were considered adequate and then were used to define the operable design region using Monte Carlo method. The optimized procedure was verified for performance, showing a significant reduction in MU (61.5%), risks of false decision (specific consumer risk by 100%, global consumer risk by 40%, global producer risk by 85%), and relative costs of decision-making in conformity assessment (27.4%). This work showed the importance of MU in the performance evaluation of analytical procedures and its impact on the risks of false decision in conformity assessment of medicines. Additionally, the proposed strategies to improve the performance proved to be effective, obtaining a robust procedure with reduced MU, ensuring results with greater reliability. (AU)

• FAPESP's process: 17/04539-2 - Using measurement uncertainty in performance evaluation of analytical methods
• Grantee: Felipe Rebello Lourenço
• Support Opportunities: Regular Research Grants