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Microbial risk assessment in pharmaceutical cleanrooms
The microbial risk to aseptically manufactured products in pharmaceutical cleanrooms can be
assessed by the use of fundamental equations that model the dispersion, transfer and deposition of
microbial contamination, and the use of numerical values or risk descriptors. This can be done in
two-stages, with the first stage used to assess the transfer of contamination from all of the sources
within the cleanroom suite and the second stage used to assess both air and surface contact
contamination within critical production areas. These two methods can be used to assess and reduce
microbial risk at the preliminary design stage of the cleanroom and associated manufacturing
process or, retrospectively, for an established manufacturing operation
A cleanroom contamination control system
Analytical methods for hazard and risk analysis are being considered for controlling contamination
in pharmaceutical cleanrooms. The most suitable method appears to be the HACCP system that has
been developed for the food industry, but this requires some reinterpretation for use in
pharmaceutical manufacturing. This paper suggests a possible system.
To control contamination effectively, it is necessary to have a good appreciation of the routes and
sources of contamination, and the means of controlling them. An overview of these is given
Microbiological contamination models for use in risk assessment during pharmaceutical production
This paper describes the fundamental mechanisms of microbial contamination during manufacture
of pharmaceutical products. Models are derived that describe air and surface contact contamination.
These models can be used to develop and improve methods of microbial risk assessment. The use of
the FMEA (FMECA) method of risk assessment is discussed and, when used with the correct risk
factors, its use endorsed
Assessment of degree of risk from sources of microbial contamination in cleanrooms; 3: Overall application
A method of calculating the degree of risk of sources of microbial contamination to products
manufactured in cleanrooms has been described in two previous articles. The degree of risk was
ascertained by calculating the number of microbes deposited (NMD) onto, or into, a product from
each source of contamination. The first article considered airborne sources, the second article
considered surface and liquid sources, and this final article considers all three sources. The NMD
method can be applied to various manufacturing methods and designs of cleanrooms but was
illustrated by a vial-filling process in a unidirectional airflow (UDAF) workstation located in a non-
UDAF cleanroom. The same example was used in this article to demonstrate how to control the
microbial risk, and included the use of a restricted access barrier system.
The risk to a patient is not only dependent on microbial contamination of pharmaceutical
products during manufacture in cleanrooms and controlled zones but the chance that any microbes
deposited in the product will survive and multiply during its shelf life, and this aspect of patient risk
is considered
Assessment of degree of risk from sources of microbial contamination in cleanrooms; 2: surfaces and liquids
The degree of risk from microbial contamination of manufactured products in healthcare
cleanrooms has been assessed in a series of three articles. The first article discussed airborne sources,
and this second article considers surface contact and liquid sources. A final article will consider all
sources and give further information on the application of the risk method.
The degree of risk to products from micro-organisms transferred from sources by surface
contact, or by liquids, has been assessed by the means of fundamental equations used to calculate the
likely number of microbes deposited (NMD) onto, or into, a product. The method calculates the likely
product contamination rate from each source and gives a more accurate risk assessment than those
presently available. It also allows a direct comparison to be made between microbial transfer by
different routes, i.e. surface, liquid and air
Deposition velocities of airborne microbe-carrying particles
The deposition velocity of airborne microbe-carrying particles (MCPs) falling towards surfaces was
obtained experimentally in operating theatres and cleanrooms. The airborne concentrations of
MCPs, and their deposition rate onto surfaces, are related by the deposition velocity, and
measurements made by a microbial air sampler and settle plates allowed deposition velocities to be
calculated. The deposition velocity of MCPs was found to vary with the airborne concentration, with
higher deposition rates occurring at lower airborne concentrations. Knowledge of the deposition
velocity allows the deposition on surfaces, such as product or settle plates, by a known airborne
concentration of MCPs to be predicted, as well as the airborne concentration that should not be
exceeded for a specified product contamination rate. The relationship of airborne concentration and
settle plate counts of MCPs used in Annex 1 of the EU Guidelines to Good Manufacturing Practice to
specify grades of pharmaceutical cleanrooms was reassessed, and improvements suggested
Assessment of degree of risk from sources of microbial contamination in cleanrooms; 1: Airborne
The degree of risk from microbial contamination of manufactured products by sources of
contamination in healthcare cleanrooms has been assessed in a series of three articles. This first
article considers airborne sources, and a second article will consider surface contact and liquid
sources. A final article will consider all sources and the application of the risk method to a variety of
cleanroom designs and manufacturing methods.
The assessment of the degree of risk from airborne sources of microbial contamination has been
carried out by calculating the number of microbes deposited from the air (NMDA) onto, or into, a
product from various sources. A fundamental equation was used that utilises the following variables
(risk factors): concentration of source microbes; surface area of product exposed to microbial
deposition; ease of microbial dispersion, transmission and deposition from source to product; and
time available for deposition. This approach gives an accurate risk assessment, although it is
dependent on the quality of the input data. It is a particularly useful method as it calculates the likely
rate of product microbial contamination from the various sources of airborne contamination
Microbial transfer by surface contact in cleanrooms
Experiments were carried out to ascertain the proportion of microbes that would be transferred from
a contaminated surface to a receiving surface in a cleanroom. To simulate transfers, microbe-carrying
particles (MCPs) were sampled from the skin onto donating sterile surfaces, which were latex gloves,
stainless steel and clothing fabric. A contact was made between these surfaces and a sterile receiving
surface of stainless steel, and the proportion of MCPs transferred ascertained. The proportion of
MCPs transferred, i.e. the transfer coefficient, was 0.19 for gloves, 0.10 for stainless steel, and 0.06 for
clothing fabric. These transfer coefficients would vary in different conditions and the reasons are
discussed
Equations for predicting airborne cleanliness in non-unidirectional airflow cleanrooms
Equations are derived in this paper for predicting the airborne concentration of particles and
microbe-carrying particles in non-unidirectional airflow cleanrooms during manufacturing. The
equations are obtained for a variety of ventilation systems with different configurations for mixing
fresh and recirculated air, air filter placements, and number and efficiency of air filters. The
variables in the equations are air supply rate, airborne dispersion rate of contamination from
machinery and people, surface deposition of particles from air, particle concentration in fresh makeup
air, proportion of make-up air, and air filter efficiencies. The equations are amenable to relatively
simple modification for the study of different cleanroom ventilation systems. The use of these
equations to investigate the effect of different configurations of ventilation systems and the relative
importance of the equation variables on airborne concentrations will be reported in a further paper
Airborne microbial monitoring in an operational cleanroom using an instantaneous detection system and high efficiency microbial samplers
The airborne microbial contamination in a non-unidirectional airflow cleanroom, occupied by personnel wearing either full cleanroom attire or only cleanroom undergarments was simultaneously determined using an instantaneous microbial detection (IMD) system and efficient microbial air samplers that detected both aerobic and anaerobic microbes. Depending on the type of cleanroom clothing, the IMD system recorded between 7 to 94 times more ‘biological’ particles than microbe carrying particles (MCPs) recovered by the air samplers. Change in the airborne concentration of ‘biological’ particles due to the different clothing was not consistent with the change in the concentration of MCPs. The median size of the ‘biological’ particles was smaller than the MCPs and the associated particle size distributions were considerably different. A number of sterile materials in the cleanroom were shown to disperse substantial quantities of ‘biological’ particles and it was concluded that the number of particles of microbiological origin, and the relationship between the counts of ‘biological’ particles to MCPs, were masked by non-microbial fluorescent particles dispersed from these materials. Consequently, adequate monitoring of this type of cleanroom operation to confirm appropriate airborne microbiological contamination control, using only an IMD system of the type used for this programme of work, is considered to be unfeasible. However, if the IMD system could be improved to more accurately differentiate between micro-organisms and non-microbial fluorescent particles, or if the dispersion of fluorescent particles from nonmicrobiological cleanroom materials could be reduced, then this system should provide an effective cleanroom airborne monitoring method
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