Whytes Analyses

Throughout the 1980s and 1990s William Whyte and his co-workers attempted a more ambitious model of contamination than the experimentally based views on deposition published by Bradley et al. (1991).

In 1986 Whyte listed five mechanisms by which airborne particles can be deposited on surfaces. He analyzed in some detail the significance of each of these mechanisms to contamination in practice in pharmaceutical clean rooms.

Whyte's analysis is based on common sense, observation and experience, coupled with some practical experimentation.

Whyte's five mechanisms are:

1. Brownian Motion. As this factor is only applicable to particles of 0.5 ^m or smaller, Whyte concluded that it would be of no practical significance in pharmaceutical clean rooms. This would have been about the size of the discrete microorganisms used in the experimental system of Bradley et al. (1991). Whyte argues that airborne microorganisms are actually carried on much larger particles and references 14 ^m for the typical size of airborne particles from hospitals (Noble et al., 1963), 20 ^m for the median size of skin flakes (Macintosh et al., 1978), and 7, 10, 11 and 17 ^m (varying according to garments worn) for bacteria-carrying particles shed by workers in pharmaceutical clean rooms (Whyte, 1984, 1986).

2. Inertial Impaction. In 1981 Whyte presented mathematical and experimental evidence concerning the effects of particulate contamination of bottles through their open necks as a consequence of gravity and inertial impaction. These are quite different according to whether the air stream around the open neck of the bottle is at right angles, or parallel to the neck. Impaction made a greater contribution to contamination when the air stream is parallel to the neck. Mathematical models presented in this publication predicted that contamination by inertial impaction should be of similar importance that by gravitational settling for microorganisms and for nonviable particles in the size range of 5 to 20 ^m.

In 1986 Whyte contended that he had previously overstated the importance of impaction in order to present a worst-case scenario, and that in actuality it would be less significant than gravitational settling.

Conversely, it is possible that inertial impaction could account for the significant effects of laminar air flow protection (on or off) on the position (but not the general form) of the relationship between the concentration of airborne microorganisms and the frequency of contaminated blow-fill-seal ampoules reported by Bradley et al. (1991).

Some factoring for inertial impaction merits inclusion in an expansion of Roark's (1972) term X(t), the deposition rate. Whyte's (1981) expression for the number of particles impacted in time T is probably as good a basis as any.

Number of particles impacted = C. A . V. P. t, where

C = the concentration of airborne microorganisms.

A = the surface area exposed to contamination. Whyte (1981) presented this as the diameter of the open neck of a bottle, but it could equally apply to the surface area of a rubber vial stopper, etc. V = the velocity of the air carrying the microorganisms or particles. Impaction has its greatest influence on rapidly moving particles. P = an inertial parameter defined by the shape of the item upon which impaction may take place,e.g., cylindrical, spherical, etc. t = the elapsed time in which the item is exposed to the potential of contamination.

3. Direct Interception. Van der Waal's force attracts particles onto surfaces when the two are very close together. Whyte (1986) discounted any significant contribution from these forces of direct interception to contamination of air flow-protected surfaces in clean rooms. It is difficult to see how they could have a major effect in environments of continuously turbulent or faststreaming air, with only low concentrations of contaminants present.

4. Electrostatic Attraction. These forces can operate at much greater distances than can the forces of direct interception. They depend on the electrostatic charges present on materials. Glass containers are likely to have very little charge and have less electrostatic attractiveness than more highly-charged plastic containers. The fabric of clean room operators' garments should be chosen carefully to ensure that electrostatic charges do not build up until the operator becomes a "magnet" for airborne particles, which he may then transfer by direct contact to the product or to product contact components (e.g., vial stoppers). The choice of materials used in clean rooms and for clean room clothing and furnishings virtually eliminates electrostatic forces causing a real problem.

5. Gravitational Settling. This reflects Whyte's 1986 thesis, and relies on gravitational settling being the principle means of deposition of microorganisms in clean rooms. This thesis presented a model to approximated deposition by means of Stokes Law in which the settling velocity of particles in fluids are described by the following equation:

Vs= settling velocity of particles in a fluid p = the density of the particle. The density of skin flakes and similar particles which carry airborne bacteria (this can be taken to be equal to one). g = the acceleration due to gravity.

d = the diameter of the particle(s) in the air. Whyte (1986) used a diameter of 12 ^m in subsequent predictive calculations. This is an approximation: there is sufficient experimental evidence to indicate that there may be quite a range of sizes of particles carrying microorganisms in air. Y = the viscosity of the fluid within which the particles are settling. Air can be assumed to have a viscosity of 1.7 x 10-4 poise.

From this equation and the assumption that microorganism-carrying particles are of 12-^m equivalent diameter, Whyte (1986) concluded that their settling rate in air is 0.462 cm/sec. Sykes (1970) alleged that the settling rate in air calculated by Stokes Law for particles of 5-^m equivalent diameter is about 0.07 cm/sec, some six or seven times slower than Whyte's (1986) figures. The difference is probably due to different assumptions within the application of Stokes Law. Whyte (1986) contended that measurable contamination rates can be predicted by Stokes Law, because gravitational settling is the principle cause of contamination in clean rooms. Sykes (1970) contended that the greatest risk of contamination in clean rooms comes from "moving air carrying microorganisms in the direction of, or onto, the sterile surface," in other words inertial impaction.

Undoubtedly gravitational settling must play some part in deposition, and Stokes

Law should take its place alongside the equation describing inertial impaction in any expansion of Roark's (1972) term y(t), the deposition rate. There is no experimental evidence to substantiate the balance of the two factors and how they may be affected by physical conditions.

Whyte et al. (1982) conducted a series of practical experiments in two semi-automated aseptic filling rooms to obtain four different contamination rates for hand-stoppered, TSB-filled vials under four different conditions of airborne contamination. The actual contamination rates obtained in these experiments were compared (Whyte, 1986) with theoretical contamination rates derived from the Stokes Law thesis on gravitational settling using measures of airborne contaminated from settle-plate data, and from volumetric air sampling. Corellations were not good, seven of the eight predicted rates were higher than the actual rates of contamination. Whyte (1986) contended that the predictions were good estimates, erring on the conservative side.

It is possible to conclude that Whyte overemphasized the importance of gravitational settling.

Deposition has dominated the interest in contamination modelling. In modern, well-controlled clean rooms it is probably a very minor component in product contamination, especially when compared to contamination by contact.

However, contact is an even more difficult concept. Bernuzzi et al. (1997) used the term "outliers" to describe incidences of contact contamination. Contact contamination is likely to be an intermittent factor, and may not be confined to point of fill, or to the time frame in which a filling operation is conducted. For instance, it is possible for rubber vial closures to be contaminated when they are unloaded from the autoclave one day and filled on another.

Later it is possible for that contamination to be redistributed among the closures when they are transferred to the hopper, eventually to randomly contaminate product units when the closures are pushed home.

The potential importance of contact contamination (hand-carriage contamination and the protective effects of clean-room clothing) was illustrated by Whyte et al. (1982) and by Whyte and Bailey (1985). There was a ten-fold difference in contamination rates of TSB-filled, hand-stoppered vials between operators wearing isopropyl alcohol-disinfected gloves and those with unwashed bare hands.

Roark's (1972) factor ^(i) describing the removal rate of microbial contaminants through physical means or death has only been addressed in terms of microbial death. The general form of microbial death is known to follow an exponential form (Fredrickson, 1966). Whyte et al. (1989) showed with a wide range of parenteral products that most were unable to support the growth or survival of any microorganisms, except for a few Gram-negative types in mainly unpreserved products. Physical removal is a largely undocumented topic.

In conclusion, contamination modeling as it applies to aseptic pharmaceutical manufacture in clean rooms is still in its infancy. The mechanisms are clearly complex and probably unique to each facility and filling operation, and to their airflow protection, manning, clean-room garments and disciplines.

Experimental data are difficult to generate, and the assumptions supporting particular models may not be transferable from one situation to another. Contamination as measured by growth in nutrient media should not be considered synonymous with the assurance of sterility (SAL) for particular pharmaceutical products; at best it is a worst-case, but grossly inaccurate, estimate of SAL.


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