Filter Clogging Issues in Sterile Filtration - - BioPharm International


Filter Clogging Issues in Sterile Filtration

BioPharm International
Volume 21, Issue 4


A MAb product was used in this study. The protein concentration in the feed material was 150 g/L. The starting material was filtered through a 0.2-μm filter before starting the investigation and also after every concentration operation. The pH of the feed was adjusted as necessary using glacial acetic acid. The protein was concentrated using a ProFlux M12 tangential flow filtration system and Pellicon 2 mini filters (Cat#: P2C010C01) from Millipore Corporation (Billerica, MA). Filtration experiments were performed with Durapore type GV filters (Cat#: GVWP04700) from Millipore Corporation. A Beckman DU-600 spectrometer from Beckman Coulter (Fullerton, CA) was used to measure protein concentration. A pH meter Model 720A from Orion was used to measure the pH of the solution during titration. JMP software version 6 from SAS Institute (Cary, NC) was used to perform the statistical analysis.

In a typical experiment, the protein concentration in the feed was adjusted to the desired value by either concentration or dilution with the formulation buffer. Test solutions were mixed during hold times and processing. All experiments were performed at room temperature. A flow rate of 1,000 LMH was chosen as the model flow rate for the Pmax tests. The material was filtered until either the feed was exhausted or the pressure differential reached 30 psig. The operating parameters tested were hold temperature, protein concentration, hold time, and pH. An operating range of 4–22 C, 40–100 g/L, and 0–72 hours was chosen for the hold temperature, protein concentration, and hold time, respectively.


Figure 1
Figure 1 illustrates a typical pressure response curve for these filtration experiments. As is evident, the data points fit very well with the curve generated using Equation 4. For the case illustrated here, the pressure drop threshold of 30 psi was reached. In some of the experiments, the pressure drop threshold was not reached. For those cases, Equation 5 was used to calculate the theoretical maximum throughput. Curves for all the experiments yielded an R2 value >0.95 demonstrating the validity of the model used.

Figure 2
JMP analysis was performed on the dependence of initial pressure on the various experimental conditions under consideration. The results shown in Figure 2, indicate that concentration and pH are the two factors that have statistically significant effects (p < 0.05). Concentration also has an effect that is significant in magnitude. This is expected because the concentration of the protein has a direct impact on the initial pore plugging on the membrane surface. Although temperature is expected to affect the initial pressure by its impact on viscosity, the effect seems negligible in Figure 2 because of the noise in the data and a ten-fold larger effect of concentration.

Figure 3
JMP analysis of data showing dependence of theoretical maximum throughput on the various experimental conditions under consideration is presented in Figure 3. The hold time is the only parameter that has a statistically significant effect. The effect is also most significant in its magnitude. This is further confirmed by calculating the clogging coefficient using Equation 4 and plotting it with respect to the hold time. As shown in Figure 4, the data fit the exponential curve from the equation very well (R2 = 0.9957).

Figure 4
The significant effect of the hold time on the clogging coefficient and the throughput occurs because conditions that lead to filter fouling are similar to conditions that foster molecular aggregation. In sterile filtration, aggregation is the most likely cause of clogging. The intermediate law states that each molecule can deposit on any part of the membrane surface and completely plug the pore.12 This is consistent with the protein monolayer theory proposed by Kelly and Zydney.1,3 Molecules prone to aggregation because of shear deformation or free thiol groups form small aggregates. These particles then randomly deposit anywhere on the membrane surface and serve as nucleation sites for growing aggregates. Passing molecules may then become attached to the aggregates at these nucleation sites. As these sites grow in the pore, the pore clogs completely. When a protein solution is held for extended periods of time, aggregates can form and grow. When the filtering process commences, there are now more "seeds" to serve as nucleation sites for pore plugging.

Figure 5


Figure 5 illustrates the relationship between the theoretical maximum throughput and hold time under the chosen experimental conditions. The maximum throughput follows an exponential decay with increasing hold time. For a given product, concentration, pH, and temperature of processing are fixed. To ensure successful execution of the sterile filtration step, the focus should be on ensuring that adequate filter area is available at the time of processing. The required area depends on the change in the clogging coefficient with hold time. This relationship can be stated in the form of Equation 6:

Where, the constant of proportionality, δ is a decay constant (h-1) and (V/A)max,0 is the maximum throughput at a hold time of 0 h.

This relationship can be used to prevent filter clogging and avoid the resulting delays during manufacturing. For every new product, it is recommended that Pmax tests be performed at hold times of zero and a maximum allowable hold time that may be required during manufacturing. If the filterability of the product is not affected by hold time, the data can be used for filter sizing. For cases where hold time has a significant impact on the filterability of the product stream, it is recommended that a third Pmax experiment be performed at an intermediate hold time value. With three data points, the clogging coefficient can be determined using Equation 6 along with the relationship between theoretical maximum throughput and hold time. The exponential fit can be used to generate the filter area that would be required to process a known amount of material for a given hold time.

There may be cases in which other operating conditions such as pH and temperature have a more critical impact than they did in our application. For those cases, a different model would need to be generated and implemented. In either case, the systematic approach presented here can be effective in avoiding filter clogging and the resulting deterioration of product quality and/or longer processing times and, thus, loss of plant capacity. Also, the same filtration curves may be obtained through completely different fouling mechanisms. However, the intermediate blocking law that is presented here is a reasonable approach toward interpreting the fouling effect on pressure drop, as well as quantifying.

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