分析开发中的清洁验证:当前的挑战和未来的展望

B. R. Jena, Pharmaceutical Analysis, S. Swain, D. Pradhan, D. Ghose
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引用次数: 0

摘要

清洁验证是一种突出和理想的实践,用于工业方面,为开发药物产品提供最大的屏蔽,以便清洁实践去除颗粒物质,化学物质以及污染病原体,这些病原体存在于已生产或正在制造的器械中药物产品的活性成分中。清洁验证是一种卓越的流程,可确保制药设备和制造产品的效率、安全性和一致性。原料药生产过程中最大限度的清洁实践提供了适当的操作人员安全措施,有组织的校准,描述和设备的常规监测,采样程序,验收标准和分析方法的检测限。这也导致系统的数据分析,以估计产品批次中可能的传染。清洗失败可能会导致源自前批次的掺假产品,清洗剂或其他在方法中产生的多余材料。因此,为了避免有害的污染源,从监管和稳定的角度出发,强烈建议采取清洁的安全措施。目前的审查加强了当前的挑战,基本机制和清洁验证在各种分析开发公司和研究组织的未来意义。©2020由创新出版社出版。这是一篇基于CC BY-NC许可的开放获取文章(https://creativecommons.org/licenses/by-nc/4.0/)
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cleaning validation in analytical development: Current challenges and future prospectives
Cleaning validation is a prominent and ideal practice which is employed in industrial aspects to provide utmost shielding to develop drug products, so that a cleaning practice removes the particulate matters, chemicals, as well as the contaminant pathogens reside in active ingredients of drug product in a piece of apparatus, which are produced or being manufactured. The cleaning validation is established as the pre-eminent process that ensures the efficiency, safety, consistency of pharmaceutical equipment and manufactured product of assured quality. The utmost cleaning practice during manufacturing of drug substances affords the appropriate operator safety measures, organized calibration, description and routine monitoring of equipments, Sampling procedures, acceptance criteria’s and detection limits of analytical methods. This also lead to systematic data analysis for estimating of probable contagions in product batches builds up. Abortive cleaning may lead to adulterated product that may be originated from preceding batches, clean-up agents or other superfluous materials produced during methodology. Hence to avoid the harmful contamination, sources, safety measures clean-in-practice is highly recommended as per regulatory and stability point of view. The present review intensifies the current challenges, basic mechanisms and future implication of cleaning validation in various analytical development firms and research organizations. © 2020 Published by Innovative Publication. This is an open access article under the CC BY-NC license (https://creativecommons.org/licenses/by-nc/4.0/)
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