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; 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; 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; 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

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

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