Process Analytical Technology-Based In-Line Buffer Dilution In Downstream Bioprocessing

Published on: 
Pharmaceutical Technology, Pharmaceutical Technology-10-01-2010, Volume 2010 Supplement, Issue 5

The authors describe the operational requirements and design of a process-ready PAT-based IBD system.

Chromatography is an integral step in downstream bioprocessing, and buffered mobile-phase properties such as ionic strength and pH are often critical process parameters for protein purification. The interactions between the mobile and stationary phases can affect chromatographic performance, and thus the separation profile between product and impurities. Product recovery, purity, and throughput are often marred by the variability in buffer preparation during production-scale bioprocessing. The popular approach to biological production typically relies on postchromatographic adjustments (e.g., fractionation controlled by ultraviolet (UV) signal and segregation of out-of-specification product through quality-control testing) to achieve the desired product quality. Although the US Food and Drug Administration accepts this traditional practice, this post-process approach to quality control is time-consuming, increases production cost, and does not provide the process understanding and control from the quality-by-design (QbD) approach that FDA promotes.

Process analytical technology

In accordance with FDA's Pharmaceutical CGMPs for the 21st Century initiatives, companies should employ process monitoring and control strategies to streamline biopharmaceutical manufacturing. Real-time process knowledge can help manufacturers avoid excessive rework and discarded product. To achieve this standard of quality, FDA highly recommends the implementation of process analytical technology (PAT) to facilitate a QbD approach. According to FDA, the working definition of PAT is "a system for designing, analyzing, and controlling manufacturing through timely measurements (i.e., during process) of critical quality and performance attributes of raw and in-process materials and processes with the goal of ensuring final product quality" (1).

Many modern technniques for process analysis such as pH measurement, near-infrared spectroscopy, Raman spectroscopy, refractive-index changes, humidity movement, UV monitoring, conductivity detection, and dissolved-oxygen analysis are commercially available for different applications. These analytical tools can measure physical and chemical properties of raw materials directly in real time, in contrast with techniques such as flow-meter monitoring, which only makes indirect measurements.

Applications of PAT in downstream bioprocessing

In the past 10 years, protein-expression titers have increased 1000 times from mg/L to g/L. As upstream yields continue to increase, downstream bioprocessing involving buffer preparations and delivery also must increase proportionally to keep pace with demand. Therefore, conventional practices of preparing and delivering buffers have to be modified or replaced with new manufacturing sciences (see Figure 1). This principle is especially true for industrial-scale quantities of buffers that must be reproducibile and meet tight specifications. Scientists at Genentech (South San Francisco, CA) proposed using mass-flow meters to dilute buffers from concentrates, which is a great improvement (2). The scientists described the dilution of concentrated acetone, which could be monitored by an in-line optical-density meter. Additional monitoring through feedback control of conductivity and pH can complement the design and reduce the variability of buffer feedstock, preparation, and delivery frequently encountered in bioprocessing.

Figure 1: Conventional system for buffer preparation and delivery. CGMP is current good manufacturing practices, CIP is clean-in-place, and QC is quality control. (ALL IMAGES ARE COURTESY OF THE AUTHORS)

PAT-based in-line buffer dilution

This article examines the operational requirements and design of a process-ready PAT-based in-line buffer-dilution (IBD) system, which is capable of making reproducible and accurate in-line buffer dilutions in concentrations as high as 100 × of the product using conductivity or pH feedback control. The technology can be used within stand-alone packaged equipment or engineered into a process-scale liquid chromatography skid. In the latter option, mobile phases are made on demand and sent directly to a process column for a sequence of chromatography steps in a purification regime. The comparison of a PAT-based and a mass-flow control system includes conductivity gradients, which are typical for biochromatographic processes, and the generation of linear pH gradients with good acidity control.

Figure 2: A process analytical technology-based in-line buffer-dilution skid equipped with conductivity and pH process analyzers linked with a process feedback-control loop.

The literature includes several examples of diluting buffers from concentrates in processes consistent with QbD (3). Some biopharmaceutical companies currently use a patented PAT-based IBD skid for buffer preparation and dilution (see Figure 2). To understand how IBD assists the QbD paradigm recommended by FDA, one should examine the basic technology platform. Figure 3 shows a sample piping and instrumentation diagram (P&ID) from the process-control screen of an IBD system.

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Figure 3: Piping and instrumentation diagram screen of a process analytical technology-based in-line buffer-dilution system.

A typical PAT-based IBD skid consists of three pumps labeled P001, P002, and P102. Deionized water for injection (WFI) is connected to P001, and buffer at concentrations as high as 100 × of the product is connected to P002. WFI and buffer concentrate are pumped into a blending loop, where the buffer concentrate is diluted to 1 × the product. The diluted buffer has a specific conductivity that can be analyzed by an in-line process conductivity sensor linked to a process-control feedback loop. The sensor continuously analyzes the conductivity of the buffer blend in the loop and sends an output signal to the process-control feedback loop. The loop then compares the current process conductivity value with a user-defined conductivity target set point for the buffer diluted to 1 × the product. Based on the feedback signal, the concentrate pump speeds can be increased or decreased. Whenever the acidity of the buffer solution must be adjusted, alkali or acid can be delivered from P102. In this instance, a pH probe would be installed in the blending loop and linked with its own process-control feedback loop to adjust the solution's pH to meet the user's specifications.

To assess the ability of a PAT-based IBD system to monitor a process and to actively manipulate it to maintain a desired state, the authors performed experiments to compare simple mass-flow and PAT-based control blending, and to reveal the true benefits of directly measuring the quantity of raw materials present during runs. The first experiment was a buffer-preparation scenario in which errors in the formulation of the concentrate raw material can cause an out-of-specification buffer-dilution product. The second comparison was made in the context of producing a linear pH gradient with pH adjustment and control not commonly available in a mass-flow-based dilution system.

Materials

The conductivity and pH analyzers used in these experiments were standard components on a 5-L/min IBD skid from Asahi Kasei Bioprocess (Glenview, IL). The pH probe was an ABB Limit model #AP121 21000 electrolyte-filled glass electrode from ABB Instrumentation (Cary, NC). The conductivity sensor was an Optek CF60-45 with six electrodes and a Pt1000 platinum resistance-temperature device used for temperature measurement and compensation from Optek-Danulat (Germantown, WI).

Both probes were mounted in a 1-in. F40 Optek PEEK Flow cell with a PF12 pH electrode adapter. An Optek Control 200 controller was installed on the skid and used a dual-input electrochemical converter to monitor pH, conductivity, and temperature. Conductivity, pH, and temperature output signals from the electrochemical converter were processed and trended in a run chart using Proficy HMI/SCADA-iFIX, Proficy Historian Version 3.1a, and SP1 process-control software from GE Fanuc (Charlottesville, VA) on a personal computer housed in the skid. Oakton Instruments's (Vernon Hills, IL) pH and conductivity standards were used for sensor calibration.

One liter of sodium chloride (1 × the product) was carefully weighed out using a model JK-200 analytical digital balance from Chyo Balance (Komatsu, Japan) with ± 0.01 mg accuracy. Sodium chloride (~6 × the product) concentrate was weighed out using a model MK-2000B Petit balance (Komatsu) from Chyo Balance with ± 0.1 g accuracy and dissolved into deionized water in a polycarbonate drum. Acetic acid and ammonium hydroxide solution were diluted from their respective concentrations. Sodium chloride and glacial acetic acid were purchased from Amresco (Solon, OH), and ammonium hydroxide was obtained from Mallinckrodt Baker (Phillipsburg, NJ).

Comparison of mass-flow and PAT-based control blending

Conductivity control. The carefully prepared 1-L standard of 0.167 M sodium chloride gave a conductivity reading of 17.8 mS/cm, which was used as the programmed conductivity set point in the process-control software. Initially, the 1-M sodium-chloride concentrate delivered by the P002 pump was diluted in the blending loop by the WFI (P001) pump. Both pumps' frequencies were adjusted accordingly to obtain the programmed conductivity set point. The recorded WFI, concentrate, and blending-loop pump speeds were entered into a new method as pump preset start speeds. Starting from 1-M sodium-chloride concentrate, either mass-flow or PAT-based blending achieved the desired molarity with the targeted conductivity of 17.8 mS/cm (see Figure 4). Because of the presence of impurities, mixing inefficiency, and weighing errors, feedstock variability of 5% was expected.

Figure 4: Conductivity of final products from mass-flow and process analytical technology (PAT)-based in-line buffer-dilution blending.

To reveal the state of a process, the authors prepared a sodium-chloride concentrate ± 5% from the original 1-M solution. Using the same pump frequency and method of mass-flow measurement determined earlier, the conductivity of the final product was obtained. The average conductivity of the dilution of 0.95-M sodium-chloride concentrate was about 16.8 mS/cm, which was 1 mS/cm or 5.6% below the set point. For 1.05-M sodium-chloride concentrate, the average conductivity was 18.5 mS/cm, or 5% above the set point. Data indicated that the variability of the starting raw materials determined the outcome, and mass-flow measurement could not adjust to the desired set point. In contrast, the PAT-based IBD used the in-line conductivity sensor in the loop to measure and correct the variability of the incoming salt concentrate through the process-control feedback loop. Whether the starting salt concentrate was 5% above or below the original 1-M concentrate, the conductivity of the product was well within the range of 17.8 ± 0.082 mS/cm.

pH gradient. The titration curve between acid and alkali, whether strong or weak, is not linear (4). Therefore, protein chemists seldom use pH gradients during a chromatographic run to resolve proteins with similar pI, especially at production scale. To determine whether the PAT-based IBD system could produce a linear pH gradient, the authors blended a weak acid with a weak alkali. Two experiments, one based on mass-flow, and the other PAT-based, were performed.

Ammonium hydroxide (10 mM) was delivered from pump P001 to mix with acetic acid (20 mM) from pump P002. In mass-flow blending, the frequency of both pumps was tuned for the pH to start at around 5. A gradual increase of base over 30 min afforded a final pH of 10. Simply blending weak acid and weak base by mass-flow obtained a typical sigmoid curve (see Figure 5). The steep rise of pH from 6.5 to 9 in less than 2 min was typical of mass-flow control. The pH of the resulting solution followed the acid-and-base titration curve.

The goal for this experiment was to generate a linear pH gradient from 5 to 9. To control the sigmoid change in pH and to obtain a linear pH gradient, acidity adjustment and control through a PAT-based system is necessary. Accordingly, ammonium-hydroxide solution (100 mM) was delivered from pump P102. Initially, three pumps were properly tuned to start at a pH of approximately 5.0. The authors programmed the process-control software with a linear pH gradient from 5 to 9 over 30 min. During the run, the acidity of the resulting solution in the loop was constantly adjusted to meet the set point in accordance with the signal from the process-control feedback loop. As a result, a linear pH gradient was obtained (see Figure 5).

Figure 5: pH titration curve of 10 mM acetic acid and 10 mM ammonium hydroxide. PAT is process analytical technology.

Discussion

Pharmaceutical companies still suffer from excessive re-work and discarded product because of out-of-specification processes. PAT-based IBD has the potential to account for and to reduce the impact of raw-material variability when diluting concentrate solutions. Thus, IBD can reduce the amount of out-of-specification products that must be reprocessed or discarded. PAT-based control can be applied to chromatographic separations so that consistent and reproducible gradients are produced, regardless of the starting materials. Furthermore, PAT control also can enable the use of linear pH gradients for different applications normally not available from a mass-flow control system.

The ability of an IBD system to monitor and manipulate the state of a process and actively manipulate it to maintain a desired state was supported by both the conductivity and the linear pH gradient experiments (1). FDA's QbD initiative incorporates PAT as a crucial tool for designing and optimizing manufacturing processes. The PAT-based IBD system described in this article successfully implements the principles of this guidance and minimizes variability by adaptively correcting the quantity of raw materials around a set point.

Michael Li, PhD,* is manager of process sciences, Vivek Kamat is senior engineer, Hiroyuki Yabe is manager of science and technology, and Tomo Miyabayashi is vice-president of science and technology, all at Asahi Kasei Bioprocess, 1855 Elmdale Ave., Glenview, IL 60026, tel. 847.556.9716, fax 800.293.5059, michael.li@ak-bio.com. Shree Jariwala is an undergraduate student intern at Northwestern University.

*To whom all correspondence should be addressed.

References

1. FDA, PAT: A Framework for Innovative Pharmaceutical Development, Manufacturing and Quality Assurance (Rockville, MD, Sept. 2004).

2. T. Matthews et al., Pharm. Manuf. 8 (4), 36– 41 (2009), www.pharmamanufacturing.com/articles/2009/046.html accessed Sept. 21, 2010.

3. T. Malone and M. Li, Bioprocess Int. 8 (1), 40–44 (2010).

4. T. Brown, H. LeMay, Jr. ,and B. Bursten, Chemistry: The Central Science (Prentice Hall, Englewood Cliffs, NJ, 5th ed., 1991), pp. 607–615.