Maria Beatriz da Silva Santos¹, Simão Pedro Jacinto Nogueira Neto¹, Suelen Carneiro de Medeiros², Bárbara Cibelle Soares Farias Quintela¹, Anna Carolina Machado Marinho¹

Mass spectrometry (MS) has become a powerful tool in developing healthcare-related products. Sample preparation for MS analysis is a critical step that directly impacts data quality. The Quality by Design (QbD) approach - which focuses on building quality into the production process - can be effectively applied to analytical method development as a risk-mitigation tool, thereby enhancing method reproducibility. In proteomic studies, inconsistent sample preparation remains a major source of variability that can compromise the reliability of protein identification and quantification. Proper optimization of sample preparation protocols is particularly crucial in proteomics, where inconsistent digestion can significantly affect protein identification and quantification. Implement QbD principles in optimizing sample preparation protocols for bottom-up proteomic analysis using tryptic hydrolysis coupled with liquid chromatography-mass spectrometry (LC-MS). An initial brainstorming session was conducted to define the target analytical profile of the methodology. Risk assessment of the method steps was then performed using Ishikawa (fishbone) diagrams and Failure Mode and Effects Analysis (FMEA). Identified risks were classified as: high risk (scores 49-100), medium risk (25-48), or low risk (1-24) based on the analysis. The risk assessment revealed that critical parameters requiring optimization included trypsin hydrolysis temperature and duration, as well as enzyme type and storage conditions. Consequently, an experimental design was proposed to evaluate hydrolysis time (3h, 6h, 16h, and 24h incubation periods) as a key variable affecting enzymatic performance in the selected method. Risk analysis tools combined with experimental design show significant promise for improving and better understanding sample preparation methods in tryptic hydrolysis-based proteomic analysis. This systematic approach enables more robust method development and optimization.

Agradecimentos: Fiocruz - SUS - PROVOC - Escola Eusébio de Queiroz - Escola Politécnica Joaquim José Venâncio