Microbiological monitoring of clean areas in healthcare establishments : trend analysis according to USP <1116>
6 October 2017C. Nassar 1, A. Venet1, S. Crauste-Manciet1,2 1 Pharmaceutical Technology Department - University Hospital of Bordeaux (CHU de Bordeaux)
2 ARNA Laboratory, team ChemBioPharm, U1212 INSERM - UMR 5320 CNRS - Bordeaux University
The control of the environment within pharmacys of healthcare establishments ensuring the production of sterile medicines is essential to guarantee the maintenance of the aseptic process.
It goes through environmental microbiological controls. In France, the Good Practices of Preparation (BPP) are opposable: in clean areas of class A, the number of CFU must be less than 1.
The USP <1116> presents a new perspective, based on a rate of incidents: the analysis must consider the frequency at which the contamination is detected rather than the absolute number of CFUs detected in a sample. Implementation of the regulations was carried out at two sites in our hospital.
The recommendations of the PIC / S guidelines have been implemented and a daily microbiological monitoring in class A has been instituted.
The results of the samples taken during five months were analyzed according to the French Good Practices and according to the recommendations of USP <1116>.
For site 1, equipped with three isolators, 8 out of 1,232 samples show microbiological growth. _ For site 2, equipped with 2 laminar flow cabinets, 8 out of 468 samples are positive. The majority of the values obtained being equal to zero, it is difficult to carry out a trend analysis without any calculation method. The Most Probable Number is applied. It shows that the rate of contamination per enclosure is less than 0.1% in class A, in accordance with USP <1116>.
The results of the five-month sampling showed that the working conditions were in line with the regulations. The establishment of a daily environmental monitoring allows the very early detection of microbial contamination. Trend analysis allows to follow and anticipate an anomaly, whether technical, human or material.