■本研究创新性地建立了无菌药物生产过程中微生物鉴定和污染调查的综合策略,主要基于MALDI-TOFMS进行鉴定,辅以测序技术对菌株进行分型。
■用于监测无菌药物制造设施的细菌污染,包括其细菌分布特征和规律。三个月后,收集了二百九十二份样品,涵盖了原材料的多个关键成分,人员,环境,和生产用水。
■根据我们的战略,确定了整个生产过程中的细菌谱:获得了241/292个细菌身份,和葡萄球菌属。(40.25%),微球菌属。(11.20%),芽孢杆菌。(8.30%),放线菌(5.81%),和类芽孢杆菌。(4.56%)被证明是最主要的微生物污染物。具有75.8%的物种水平和95.4%的属水平识别能力,MALDI-TOFMS有望成为环境监测常规的一线工具。此外,为了确定最常见的cohnii葡萄球菌的来源,这证明了整个过程中的广泛存在,为了追踪传播途径,我们开发了一种更具鉴别力的cohnii全基因组SNP分型方法.基于SNP结果的系统发育分析表明,在这种情况下,关键的环境污染与人员流动高度相关。应变分型结果为以下风险评估步骤提供了可靠和准确的信息,并支持有效的预防和纠正措施。
■一般来说,本研究提出的战略将促进制药业改进生产和环境控制过程的发展,并提供有关如何为其控制程序的优化提供更可靠和可靠的证据的见解。
UNASSIGNED: A comprehensive strategy for microbial identification and contamination investigation during sterile drug manufacturing was innovatively established in this study, mainly based on MALDI-TOF MS for the identification and complemented by sequencing technology on strain typing.
UNASSIGNED: It was implemented to monitor the bacterial contamination of a sterile drug manufacturing facility, including its bacterial distribution features and patterns. In three months, two hundred ninety-two samples were collected covering multiple critical components of raw materials, personnel, environment, and production water.
UNASSIGNED: Based on our strategy, the bacterial profile across the production process was determined: 241/292 bacterial identities were obtained, and Staphylococcus spp. (40.25%), Micrococcus spp.(11.20%), Bacillus spp. (8.30%), Actinobacteria (5.81%), and Paenibacillus spp. (4.56%) are shown to be the most dominant microbial contaminants. With 75.8% species-level and 95.4% genus-level identification capability, MALDI-TOF MS was promising to be a first-line tool for environmental monitoring routine. Furthermore, to determine the source of the most frequently occurring Staphylococcus cohnii, which evidenced a widespread presence in the entire process, a more discriminating S. cohnii whole-genome SNP typing method was developed to track the transmission routes. Phylogenetic analysis based on SNP results indicated critical environment contamination is highly relevant to personnel flow in this case. The strain typing results provide robust and accurate information for the following risk assessment step and support effective preventive and corrective measures.
UNASSIGNED: In general, the strategy presented in this research will facilitate the development of improved production and environmental control processes for the pharmaceutical industry, and give insights about how to provide more sound and reliable evidence for the optimization of its control program.