{"title":"Modernizing Growth Promotion Testing using APAS<sup>®</sup> Independence: Poster Presented at PDA Week 2026.","authors":"Chris Ramsey, Albert Phan, Steven Giglio","doi":"10.5731/pdajpst.2026.26425","DOIUrl":null,"url":null,"abstract":"<p><p>Agar-based methods remain a cornerstone of environmental monitoring in cleanroom environments due to their unmatched ability to detect viable microorganisms. The Growth Promotion Test (GPT) remains a regulatory requirement to verify the performance of each new batch of culture media. While the use of freeze-dried organism pellets has improved inoculation accuracy, colony enumeration is still largely performed manually, introducing variability and potential for human error. This presentation explores how the APAS Independence system leverages artificial intelligence (AI) and advanced imaging techniques to streamline GPT workflows. By mitigating common sources of counting inaccuracy such as lighting, plate markings, and user fatigue, APAS technology delivers consistent, auditable results that integrate directly with laboratory information management systems (LIMS) for compliance with 21 CFR Part 11. Beyond improving accuracy and efficiency, the system enhances traceability and supports long-term performance trending, making it a valuable tool for modernizing GPT without disrupting existing procedures.</p>","PeriodicalId":19986,"journal":{"name":"PDA Journal of Pharmaceutical Science and Technology","volume":"80 4","pages":"502-503"},"PeriodicalIF":0.0000,"publicationDate":"2026-08-07","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.2026.26425","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
Agar-based methods remain a cornerstone of environmental monitoring in cleanroom environments due to their unmatched ability to detect viable microorganisms. The Growth Promotion Test (GPT) remains a regulatory requirement to verify the performance of each new batch of culture media. While the use of freeze-dried organism pellets has improved inoculation accuracy, colony enumeration is still largely performed manually, introducing variability and potential for human error. This presentation explores how the APAS Independence system leverages artificial intelligence (AI) and advanced imaging techniques to streamline GPT workflows. By mitigating common sources of counting inaccuracy such as lighting, plate markings, and user fatigue, APAS technology delivers consistent, auditable results that integrate directly with laboratory information management systems (LIMS) for compliance with 21 CFR Part 11. Beyond improving accuracy and efficiency, the system enhances traceability and supports long-term performance trending, making it a valuable tool for modernizing GPT without disrupting existing procedures.
基于琼脂的方法仍然是洁净室环境监测的基石,因为它们具有无与伦比的检测活微生物的能力。生长促进试验(GPT)仍然是一项监管要求,用于验证每批新培养基的性能。虽然冻干生物颗粒的使用提高了接种的准确性,但菌落计数仍然主要是手工进行的,引入了可变性和人为错误的可能性。本报告探讨了APAS独立系统如何利用人工智能(AI)和先进的成像技术来简化GPT工作流程。通过减轻常见的计数不准确的来源,如照明、板标记和用户疲劳,APAS技术提供了一致的、可审计的结果,这些结果直接与实验室信息管理系统(LIMS)集成,符合21 CFR Part 11。除了提高准确性和效率之外,该系统还增强了可追溯性,并支持长期性能趋势,使其成为在不中断现有程序的情况下实现GPT现代化的有价值工具。