{"title":"A Holistic Approach for Filling Volume Variability Evaluation and Control with Statistical Tool.","authors":"Mingyang Hei, Qingqing She, Quanmin Chen, Zhaowei Jin, Chunmeng Sun, Jiasheng Tu, Jeremy Guo","doi":"10.5731/pdajpst.2023.012867","DOIUrl":null,"url":null,"abstract":"<p><p>Vial and syringe filling by peristaltic pump has been widely implemented by contract manufacturing organizations and biopharmaceutical companies. Filling volume is commonly considered a critical quality attribute related to the aseptic filling process, and the variation needs to be well controlled to guarantee the safety, efficacy, and consistency of drug products. However, the criteria for justifying the filling variation and underlying mechanisms that affect the variability are not fully revealed quantitatively in the literatures. This study selected filling accuracy, filling process capability, and filling precision as three criteria for evaluating the filling process performance with four statistical indexes: Relative Error Mean, Critical Control Limit (Cpk ≥ 1.33), Relative Standard Deviation, and Relative Moving Range Mean. The impact of liquid properties, pump tubing sizes, and pump settings on these indexes was investigated using a bench-top system with a peristatic pump and a high-precision balance. The results showed that the viscosity, target filling volume, pump tubing size, pump speed, acceleration/deceleration rate, and suck-back had a statistically significant influence on the filling volume variability. Definitive Screening Design was further applied to clarify and visualize the priorities and interaction impact of these factors on filling volume variability. A stepwise approach for filling volume variability optimization and control based on predictive models was established and verified for drug product solution with viscosity between 1-23 cp and target filling volume between 0.2-2.0 mL.</p>","PeriodicalId":19986,"journal":{"name":"PDA Journal of Pharmaceutical Science and Technology","volume":" ","pages":"157-169"},"PeriodicalIF":0.0000,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"PDA Journal of Pharmaceutical Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5731/pdajpst.2023.012867","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0
Abstract
Vial and syringe filling by peristaltic pump has been widely implemented by contract manufacturing organizations and biopharmaceutical companies. Filling volume is commonly considered a critical quality attribute related to the aseptic filling process, and the variation needs to be well controlled to guarantee the safety, efficacy, and consistency of drug products. However, the criteria for justifying the filling variation and underlying mechanisms that affect the variability are not fully revealed quantitatively in the literatures. This study selected filling accuracy, filling process capability, and filling precision as three criteria for evaluating the filling process performance with four statistical indexes: Relative Error Mean, Critical Control Limit (Cpk ≥ 1.33), Relative Standard Deviation, and Relative Moving Range Mean. The impact of liquid properties, pump tubing sizes, and pump settings on these indexes was investigated using a bench-top system with a peristatic pump and a high-precision balance. The results showed that the viscosity, target filling volume, pump tubing size, pump speed, acceleration/deceleration rate, and suck-back had a statistically significant influence on the filling volume variability. Definitive Screening Design was further applied to clarify and visualize the priorities and interaction impact of these factors on filling volume variability. A stepwise approach for filling volume variability optimization and control based on predictive models was established and verified for drug product solution with viscosity between 1-23 cp and target filling volume between 0.2-2.0 mL.