The Art of Bioreactor/Fermenter Scale-Up (or Scale-Down)

by Dr. Deb Quick

Effective bioreactor or fermenter scale-up/down is essential for successful bioprocessing. During development, small scale systems are employed to quickly evaluate and optimize the process, but larger scale systems are necessary for producing commercial quantities at a reasonable cost. But how does one effectively transfer the process between scales so that the process performs the same?

In an ideal world, the physiological microenvironment within the cells/microorganisms will be conserved at the different scales, but with no direct measure of that microenvironment the scientist identifies relevant macroproperties to measure and control to ensure comparability. There are many macroproperties and operating parameters that define the process at each scale, and while the goal is to keep as many of those parameters constant between the scales, it simply isn’t possible to keep them all the same.

When using the same operating parameters at small and large scale is impractical, there are several correlations that are commonly used: mass transfer coefficient (kLa [the volumetric transfer coefficient, 1/hr] or OTR [oxygen transfer rate, mmol/hr]; volumetric power consumption (P/V, agitation power per unit volume); agitator tip speed; and mixing time.

Matching the kLa at different scales is generally considered the most important factor in scaling cell culture and microbial processes. The second most common approach is to match the power consumption. For both of these correlations, there are often multiple combinations of operating parameters that provide the same kLa or the same power consumption at the different scale. And herein lies the art of bioreactor and fermenter scale-up/down. Selecting the best combination of parameters to match process performance at different scales is an art. There is no magic combination that works best for all cell types and products.

To establish comparability at different scales, you’ll make your life significantly easier if you start with the same vessel design at the different scales, but this luxury is rarely reality. More often, the development lab has significantly different equipment than the manufacturing facility. But even with different reactor designs, comparable performance can be obtained at different scales through appropriate experimentation.

• First, you’ll need to understand your equipment at all scales: measure the kLa and P/V of the different scales over a wide range of air flows, agitation rates, working volumes, and backpressures. It’s best to perform the testing in your process media, if possible. If you can find the time, it’s useful to evaluate different mixing schemes at small scale - different impeller styles and positions, baffles, and sparger styles and positions (particularly valuable if you already know the differences in these features between small and large scale systems available to you).
• Second, you’ll need to understand how your product responds to the different operating parameters. Those dreaded statistically designed experiments (DoE) are particularly useful for understanding the effects and interactions of the many parameters that can be changed. Performing DoE experiments at small scale with your product to evaluate the effects of aeration, agitation, and volume will not only help you with scale-up, but will also provide useful information for setting acceptable ranges for the operating parameters at large scale. As with the kLa studies, it’s useful to study different mixing schemes at small scale if time allows. One set of experiments that is highly useful but rarely performed is the evaluation of the process performance at the same kLa (or P/V) obtained using different operating parameters.

Understanding your equipment and how your product responds to various operating conditions is the key to effective process scale-up and scale-down. Despite the historical and ongoing need for scaling bioprocesses up and down, there is no strategy that works in all situations. The art of successful scale-up lies in thoughtful experimental design and thorough data analysis in order to obtain the information that allows equivalent performance at all scales.

The Good Buffer

By Scott Rudge

“A Good Buffer” has a number of connotations in biochemistry and biochemical engineering. A “good buffer” would be one that has good buffering capacity at the desired pH. The best buffering capacity is at the pK of the buffer of course, although it seems buffer salts are rarely used at their pK.

Second, a good buffer would be one matched to the application. Or maybe that’s first. For example, the buffering ion in an ion exchange chromatography step should be the same charge as the resin (so as not to bind and take up resin capacity). For example, phosphate ion (negative) is a good choice for cation exchange resins (also negatively charged) like S and CM resins.

Another meaning of a “Good” buffer is a buffer described by Dr. Norman Good and colleagues in 1966 (N. E. Good, G. D. Winget, W. Winter, T. N. Connolly, S. Izawa and R. M. M. Singh (1966). "Hydrogen Ion Buffers for Biological Research". Biochemistry 5 (2): 467–477.). These twelve buffers have pK’s spanning the range 6.15 to 8.35, and are a mixture of organic acids, organic bases and zwitterions (having both an acidic and basic site). All twelve of Good’s buffers have pK’s that are fairly strongly temperature dependent, meaning that, in addition to the temperature correction required for the activity of hydrogen ion, there is an actual shift in pH that is temperature dependent. So, while a buffer can be matched to the desired pH approximately every 0.2 pH units across pH 7 ± 1, the buffers are expensive and not entirely suited to manufacturing applications.

In our view, a good buffer is one that is well understood and is designed for its intended purpose. To be designed for its intended purpose, it should be well matched to provide adequate buffering capacity at the desired pH and desired temperature. As shown in the figure, the buffering capacity of a buffer with a pK of 8 is nearly exhausted below pH 7 and above pH 9.

It’s easy to overshoot the desired pH at these “extremes”, but just such a mismatch between buffering ion and desired pH is often specified. Furthermore, buffers are frequently made by titrating to the desired pH from the pK of the base or the acid. This leads to batch to batch variation in the amount of titrant used, because of overshooting and retracing. In addition, the temperature dependence of the pK is not taken into account when specifying the temperature of the buffer. Tris has a pK of 8.06 at 20°C, so a Tris buffer used at pH 7.0 is already not a good idea at 20°C. The pK of Tris changes by -0.03 pH units for every 1°C in positive temperature change. So if the temperature specified for the pH 7.0 buffer is 5°C, the pK will have shifted to 8.51. Tris has 3% of its buffering capacity available at pH 7.0, 5°C, it’s not well matched at all.

A good buffer will have a known mass transfer rate in water, so that its mixing time can be predicted. Precise amounts of buffering acid or base and cosalt are added to give the exact pH required at the exact temperature specified. This actually reduces our reliance on measurements like pH and conductivity that can be inexact. Good buffers can be made with much more precision than ± 0.2 pH units and ± 10% of nominal conductivity, and when you start to make buffers this way, you will rely more on your balance and understanding of appropriate storage conditions for your raw materials, than making adjustments in the field with titrants, time consuming mixing and guessing whether variation in conductivity is going to upset the process.