Modeling of Biopharmaceutical Processes—Part 1: Microbial and Mammalian Unit Operations - Process-modeling tools can ensure smooth technology transfer of microbial and mammalian processes from b

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Modeling of Biopharmaceutical Processes—Part 1: Microbial and Mammalian Unit Operations
Process-modeling tools can ensure smooth technology transfer of microbial and mammalian processes from bench to commercial scale.


BioPharm International
Volume 21, Issue 6

A solution to minimize pH gradients and prevent over-addition of titrant is to improve bulk mixing times by increasing the agitation speed in view of the cell sensitivities to hydrodynamic shear and foaming. Another best practice is to direct base addition to a well-mixed bioreactor location, ideally subsurface (adjacent to impellers) In large bioreactors, the distance between the online control probe (typically located in the impeller region) and base addition location (typically at liquid surface) can lead to differences in measured and actual pH values at the titrant addition. Optimization of the titrant addition strategy (pulse frequency and volume) with respect to bulk mix times may also be required. Finally, the pH control strategy in relation to pH "dead band" or "controller dead zone" implementation may require fine-tuning to prevent acid-base cycling. Some other important considerations with pH control are sample handling, offline pH measurement, and probe standardization. Inconsistent practices with scale-up and process transfer may contribute to differences in pH control and process performance.

Impact of Mixing on Oxygen Distribution

Although dissolved oxygen (DO) generally is kept constant between scales, attention to DO probe zero and span calibration are required to fully represent process conditions. The relationship between DO saturation (%) and partial pressure (mm Hg) should be taken into account between sites and scales. The impact of bioreactor hydrostatic pressure at large scale also needs to be considered on dissolved gasses (DO and pCO2). Depending on the mixing characteristics, liquid height, and location of the controlling DO probe, the actual DO (and pCO2) experienced by the cells will vary depending on their location in the bioreactor. In combination with agitation power input per unit volume (P/V), the superficial gas velocity will influence the oxygen mass transfer rate (kLa). At typical agitation speeds with nonclumping mammalian cells, cell culture processes are considered more sensitive to interfacial shear by bubble bursting events than bulk hydrodynamic shear or microscale turbulence (Kolmogorov eddy size). Superficial gas velocities should be modeled to provide sufficient kLa at the selected agitation speed but not so overly aggressive as to incur cell damage, excessive gas stripping, or foaming.

For high cell density microbial processes, additional concerns exist around oxygen consumption and heat removal. Oxygen uptake rate (OUR) has a strong correlation with the heat generation rate and carbon evolution rate (CER). This is because of the relationship between cellular respiration and metabolism in aerobic microorganisms and the high cell densities that allows these values to be accurately determined. These data are important whenever a process is transferred into a new facility or increased in scale so that the process requirements (peak OUR, peak heat generation rate) can be assessed against the facility capabilities (maximum oxygen transfer rate, maximum heat removal rate).

Calculation of Agitation Speed

As mentioned above, selection of appropriate mass transfer conditions is important to achieve consistent cell culture and fermentation performance across sites and scales. During scale-up, for most situations the tank geometry and hardware (impellers, sparger, baffles, etc.) are not subject to change. Therefore, the focus is on defining appropriate agitation and sparge gassing conditions to achieve consistent performance across sites and scales.4–6

For industrial-scale cell culture bioreactors, mixing times are typically on the order of three minutes or less. Mixing times of this order of magnitude have been sufficient to achieve consistent performance across scales for many industrial cell culture fed-batch processes. They have historically been estimated from impeller discharge rates using an equation such as7,8





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