QUALIFICATION OF THE SCALE-DOWN MODEL
The general approach to scale-down model qualification is to run all operating parameters at the center of the operating range
of the manufacturing process. Compare the specific performance (output) parameters and process control sensitivity at both
scales. Establish the acceptance criteria prior to the scale-down runs, which can be based on statistical analysis of historical
large-scale data.
Culture growth is a critical performance parameter for qualifying the scale-down model. The assessment measures are culture
optical density, percent solids accumulation, and wet and dry cell-weights. Evaluate culture growth both qualitatively, based
on a comparison of growth profiles (log and linear plots), and quantitatively, through a direct comparison of specific growth
rates. The equipment and procedures used for these measurements should be identical to those used in the current manufacturing
process. In a good qualification, the overall specific growth rate and final cell yield will approximate the large-scale process.
Oxygen consumption is another important performance parameter for scale-down qualification. Similar trends in dissolved oxygen
profiles, and oxygen and airflow rates represent comparability in oxygen usage by the cultures at each scale. In addition,
by using a mass spectrophotometer, specific oxygen uptake rates (OUR) can be calculated and compared across scales through
an analysis of off-gas oxygen levels.
A key comparison involves final product titer and quality, at a speific rate of production, which is defined as the amount
of product expressed per unit biomass weight (wet or dry). The analytical assays and methodologies used to measure product
titer should be identical between scales. Product quality may be difficult to assess, because it requires the development
of a representative downstream scale-down model, including any harvest procedures, which are challenging to replicate at the
small scale. Data from large-scale runs should be collected and analyzed in order to understand the inherent variability in
the analytical assays before using the assays for scale-down model qualification.
Measure the rates of consumption of nutrients (such as glucose) and accumulation of specific metabolites (ammonia, lactate,
acetate) at both scales to demonstrate process similarity. Once again, due to the variability in measurements of these components,
the equipment and procedures employed for calculating the rates must be identical to those used in the manufacturing process.
Since cellular metabolism can be influenced by slight shifts in culture conditions, the exact metabolite levels may vary across
scales. However, the specific rates of consumption and accumulation for each component should be similar.
Process-control sensitivity for dissolved oxygen, pH, temperature, agitation, and feed delivery must be verified at the small-scale.
For example, feed delivery data must be collected and analyzed to ensure the flow controller accurately delivers the feed
at the specified target rate. If equipment limitations cause a change in feed rate, the performance of the scale-down model
will not be representative of the large-scale process.
Other process control issues to consider are maintenance of equivalent heat transfer rates during in-process temperature shifts,
differences in heat transfer and generation at different scales, and overall PID control loop response times. The process
control profiles do not need to be identical to one another, with respect to the fluctuations around a given setpoint, although
the trends in the profiles for all the control parameters should be comparable.
Additions of acid and base for pH control should also be measured and compared at each scale. However, it is important to
note that the additions of each component may not scale linearly. In some cases, the base that is used may also be a nitrogen
source for the culture. Therefore, its usage is related to the growth of the culture, as well as pH control. In addition,
slight shifts in cellular metabolism (e.g. lactate production and consumption), which are not easily predicted or controlled,
can result in changes in acid and base delivery, in order to maintain culture pH. In any case, variations in acid or base
delivery will affect process volumes and media composition. As a result, it is important to evaluate the differences in acid
and base addition at each scale for any impact on cell growth or production.
Table 2. Comparison of Performance of Fermentation Scale-down Model with Large-scale Fermentation Process
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In general, perform at least three small-scale runs in order to demonstrate reproducibility and to determine the inherent
variability in the process. Since the scale-down models may also be used to evaluate process deviations, further qualification
of the scale-down model — which would include fermentation trials at the edges of the operating parameter ranges — may need
to be performed and compared to similar process data acquired in the large-scale process.
Figure 2. Comparison of Culture Growth Profiles in Small- and Large-scale Fermentations
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Table 2 summarizes different performance attributes for small and large-scale fermentations including a comparison of product
titer, percent solids accumulation, and specific growth rate.
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