Optimization of a micro-scale, high throughput process development tool and the demonstration of comparable process performance and product quality with biopharmaceutical manufacturing processes

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Journal of Chromatography A journal homepage: www.elsevier.com/locate/chroma

Optimization of a micro-scale, high throughput process development tool and the demonstration of comparable process performance and product quality with biopharmaceutical manufacturing processes Steven T. Evans a , Kevin D. Stewart a , Chris Afdahl a , Rohan Patel b , Kelcy J. Newell a,∗ a b

Purification Process Sciences, MedImmune, One MedImmune Way, Gaithersburg, MD 20878, USA Cell Culture and Fermentation Sciences, MedImmune, One MedImmune Way, Gaithersburg, MD 20878, USA

a r t i c l e

i n f o

Article history: Received 23 January 2017 Received in revised form 15 May 2017 Accepted 16 May 2017 Available online xxx Keywords: Monoclonal antibody purification Automation High throughput process development Scale-down

a b s t r a c t In this paper, we discuss the optimization and implementation of a high throughput process development (HTPD) tool that utilizes commercially available micro-liter sized column technology for the purification of multiple clinically significant monoclonal antibodies. Chromatographic profiles generated using this optimized tool are shown to overlay with comparable profiles from the conventional bench-scale and clinical manufacturing scale. Further, all product quality attributes measured are comparable across scales for the mAb purifications. In addition to supporting chromatography process development efforts (e.g., optimization screening), comparable product quality results at all scales makes this tool is an appropriate scale model to enable purification and product quality comparisons of HTPD bioreactors conditions. The ability to perform up to 8 chromatography purifications in parallel with reduced material requirements per run creates opportunities for gathering more process knowledge in less time. © 2017 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

1. Introduction High throughput process development (HTPD) employs a rapidly growing set of parallel processing and automated tools that aid in bioprocess development. HTPD tools enable scientists to both increase the number of experiments that can be carried out and use significantly less material per experiment as compared to traditional scale-down models [1,2]. Contemporary HTPD tools incorporate automation to increase the precision of liquid handling and enable autonomous experimental operation [1–23]. This combination of increased throughput, reduced material needs, and decreased scientist hands-on time can result in the development of a more robust manufacturing process allowing scientists to have a more thorough understanding of processes and potentially decrease development timelines. In recent years, there has been an expansion of purification HTPD tool utilization that includes filter plates for batch binding experiments [3–13], micro-pipette chromatography tips for purifications, [14–16], and miniature columns for purifications [17–23]. Filter plate batch experiments allow for parallel screening to determine binding capacities, binding kinetics, and impurity clear-

∗ Corresponding author. E-mail address: [email protected] (K.J. Newell).

ance [1,2,10]. There are published examples of batch experiments directly translating into robust impurity clearing chromatography steps at larger scales [3–6,11,12]. However, quantitative prediction of column performance is not always straightforward, especially when the purification step relies on column packed bed characteristics (e.g., compression, plates, asymmetry, or unidirectional flow). For this reason, current practice frequently pairs filter plate screening with miniaturized chromatography columns [8,9,13]. Chromatography micro-pipette tips (e.g., PhyTips manufactured by Phynexus and AssayMAP) are routinely paired with automation to provide consistent liquid flow rates and offer the opportunity to provide additional predictive capabilities that cannot be achieved with batch experiments [1,2]. Micro-pipette tips produce similar trends in capacity, yield, and purity to benchtop systems. More recently the technology has been demonstrated to provide a high throughput titer determination [15], as well as predicting chromatographic effects of varying conditions for mixed mode chromatography [14,16]. The value of micro-pipette tips for the direct development of chromatography manufacturing processes has yet to be demonstrated or widely accepted. ® Miniaturized chromatography columns (e.g. MiniColumns and ® RoboColumns from Repligen) have been studied extensively to determine if they are a more appropriate HTPD tool for the development and optimization of chromatography manufacturing processes [1,2]. The cylindrical packed bed columns allow for

http://dx.doi.org/10.1016/j.chroma.2017.05.041 0021-9673/© 2017 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4. 0/).

Please cite this article in press as: S.T. Evans, et al., Optimization of a micro-scale, high throughput process development tool and the demonstration of comparable process performance and product quality with biopharmaceutical manufacturing processes, J. Chromatogr. A (2017), http://dx.doi.org/10.1016/j.chroma.2017.05.041

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experiments that better simulate conditions at larger scales including unidirectional flow, equivalent residence times, and equivalent protein loading capacities. There are challenges to performing side by side comparisons of the different scales. Miniaturized chromatography columns undergo intermittent flow during buffer and load application phases, require offline analysis of all column eluate fractions, and lack sufficient high throughput (HT) analytics that can provide equivalent results due to fraction volume limitations [1,2,17–23]. Even with these limitations, there are multiple examples that demonstrate equivalent product quality and chromatographic behavior for well characterized test proteins using multiple chromatographic media types [17–22]. Keller et al. have also recently demonstrated the suitability of automated miniaturized columns for the prediction of elution profiles obtained with the benchtop system, even though the experiments needed to use multi-step gradients to model the continuous gradients achieved at a larger scales [23]. There has been a significant amount of progress demonstrating the predictive power and high throughput capabilities of the Mini and RoboColumns on well characterized biologics in the academic setting. However, adoption of the technology across the biopharma industry has been slower than expected given the advantages provided. There are two major roadblocks to the integration of these technologies for the development of manufacturing processes including: (1) little documented evidence of the utility of HTPD tools for the development of purification processes of clinically relevant, molecules; and (2) a lack of data demonstrating the capability of HTPD methods to predict performance of manufacturing scales. Furthermore, there is a need for a significant level of automation expertise to operate equipment and generate automation scripts that appropriately account for residence time, enable chromatogram generation, and support product pooling. In this study, we present an Excel (Microsoft) based tool that captures RoboColumn experimental design and that simplifies experimental set-up and post-run data analysis. The integrated HTPD tool enables chromatogram generation based on fraction number or column volume. The generated chromatograms can then be easily compared against chromatograms at larger scales or used to predict qualitative process performance at larger scales. The HTPD tool also enables yield calculations and fractionation through an easy correlation between the fraction number (or column volume) with the collection plate. Product quality between multiple chromatography scales is assessed and demonstrates the feasibility of using this microliter scale model to develop manufacturing scale chromatography conditions.

2. Materials and methods 2.1. Materials and equipment Three different monoclonal antibodies (mAb1, mAb2, and mAb3) manufactured by MedImmune LLC were used as the protein source material for this study. The monoclonal antibodies were chosen to span IgG subclasses and a range of pI’s: mAb1 is an IgG4 with a pI near 6.0, mAb2 and mAb3 are IgG1’s with pI’s near 9.0 or greater. The molecular weight of the IgG’s were all near 150 kDa. Experiments were performed using either a EVO 150 (Tecan), ® a rotary pump system, a ÄKTA Explorer 100 (GE Healthcare), or a manufacturing scale chromatography skid. An assortment of chromatography resins including affinity, ion exchange and mixed mode media were either purchased prepacked in small scale columns, packed according to manufacturer’s recommendations for bench scale, or packed according to internal MedImmune procedures for manufacturing scale columns (Table 1).

Stationary phases varied for the mAb purifications that were studied. For mAb1 Protein A affinity capture was evaluated varying elution pH and load pH. For mAb 2 a mixed-mode MEP column was employed and for mAb3 a series of chromatography columns were evaluated (Protein A affinity capture followed by hydroxappetite and Super Q anion exchange). ® Fractions were collected using Costar 96-Well Microplates ® (Corning). Bio-One UV-Star 384-Well Microplates (Greiner) UV plates were used to analyze fractions for UV absorbance. Fractions were also analyzed for protein concentration, monomer, aggregate, and fragment using industry standard assays.

2.2. Procedures 2.2.1. RoboColumn-Tecan system Design of RoboColumn experiments was implemented utilizing an Excel based tool. The tool was designed to translate a purification process from the bench scale to the RoboColumn scale. Traditional scale-down models (bench scale) maintain a constant residence time with manufacturing scales by maintaining a constant bed height and linear velocity as the column diameter (and therefore column volume) are increased. The RoboColumn system utilizes much shorter column heights. A constant residence time is achieved by proportionately reducing the linear velocities as the column height is reduced. The tool calculates the volumetric flow rates required for the RoboColumn scale from the bench scale process description and facilitates the writing of EVOware (Tecan) ® scripts utilizing the TeChrom Wizard . The tool also calculated the solution volumes required for each experiment (load, buffers, and other solutions) to facilitate planning. An adjustable volumetric overage was also included that accounted for extra volumes consumed during Tecan operation (embedded in the liquid class used in the script). RoboColumn experiments on the Tecan instrument typically consisted of four separate automated procedures that included: (1) setup and chromatography operation, (2) transfer of a small quantity of the collected fractions from the sample collection 96well plates to a 384-well plate for chromatogram generation (plate stamping), (3) analysis of the 384-well plate by means of a UV plate reader (chromatogram generation), and (4) collection of the selected fractions into a single pool. Each of these steps is explained in further detail below.

2.2.1.1. Setup and chromatography operation. Eight 600 ␮L RoboColumns were installed on the TeChrom stage and the Tecan deck was loaded with the appropriate running buffers. During the execution of the procedure each of the eight RoboColumns had effluent fractions of approximately 200 ␮L collected in the rows of multiple 96-well plates. A typical Protein A chromatography RoboColumn Tecan run began with equilibrating the column with PBS (phosphate buffer solution) at a residence time of about 3.7 min which corresponds to a linear velocity of about 50 cm/hr or a volumetric flow rate of 2.7 ␮L/s. The flow rate remained constant over the course of the purification. After 5 CVs (column volumes) of PBS the RoboColumns were then loaded with protein to a loading capacity of about 30 g/L stationary phase. After loading the column is then washed with a 50 mM sodium acetate buffer at pH 5.5 (5 CVs) prior to be eluted off of the column using a sodium 50 mM acetate buffer at pH 3.6. The elution phase typically lasts 10–15 CVs to ensure a majority of the product is eluted in the absence of an on-line UV detector. After elution, the column is then cleaned, sanitized, and stored according to the manufacturer’s recommendations. For Protein A chromatography the cleaning and sanitization typically employ

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Table 1 Columns utilized during the study including dimensions and volume. Column Scale

Column Type (manufacturer)

Column Dimensions (Diameter × Height)

Column Volume

Small Scale Small Scale Small Scale Bench Scale Pilot and Manufacturing Scale

MediaScout and OPUS RoboColumns (Repligen) HiTrap (GE) HiTrap (GE) ® Vantage L Laboratory Column (EMD Millipore) ® Resolute Chromatography Columns (Pall Corporation)

5.0 mm × 30 mm 0.7 cm × 2.5 cm 1.6 cm × 2.5 cm 1.15 cm × 16.0–22.0 cm 20.0–80.0 cm × 20.0 cm

600 ␮L 1.0 mL 5.0 mL 16.6–22.9 mL >6 L

2–3 CVs of 0.1–0.5 M NaOH. The storage solution is typically either a 20% ethanol solution or a solution containing 2% benzyl alcohol. 2.2.1.2. Plate stamping. Chromatograms were generated through the UV-absorbance analysis of 20 ␮L from a collected fraction. The 20 ␮L volume from four 96-well plates was transferred in to one 384-well plate and centrifuged, as needed. Centrifugation was performed to remove potential air bubbles which can result in inaccurate concentration measurements and significant chromatogram noise. 2.2.1.3. Plate reading and data analysis. The 384-well plates were then read by a UV plate reader which measured UV absorbance at 280 and 340 nm. The plate reader data output was then exported to a Microsoft Excel file. The data was processed using an Excel visual basic macro (developed in-house) which generated a UV chromatogram. One chromatogram was generated for each of the Repligen RoboColumns. Chromatograms consisted of measured UV absorbance data for each column fraction represented as points that are connected with straight lines during plotting. For some data analysis, chromatograms generated by different purification systems were compared by overlaying the chromatogram. To better visualize the chromatography data from the various systems (the plate reader, an ÄKTA, and manufacturing scale skids) the absorbance data was normalized. The data normalization procedure involved determining the largest absorbance value observed from the entire data set and then using that value as the basis for the normalization. 2.2.1.4. Fraction pooling and neutralization. Fractions from the 96well plates were measured offline for pH using a Mettler Toledo pH meter with a pH electrode InLab Micro probe. Fractions were then selected and pooled using the generated chromatogram as a guide to determine mAb product elution pools. Product elution pools were measured for pH. If required for stability purposes, pooled fractions were then neutralized to a target pH ≥ 5.0 using an appropriate neutralization buffer. 2.2.2. Rotary pump system Eight parallel purifications using mAb1 as the load were performed with a rotary pump. The system tubing was primed with the appropriate buffers solutions and connected to eight HiTrap (GE) columns with column outlets connected to eight separate inline UV absorbance detectors. The data from the UV absorbance detectors was collected by a laptop to generate real-time chromatograms. The eluted mAb1 was collected to enable further analysis. Column flow rates were selected to match residence times with other scales. During the elution phase the effluent was directed to eight separate product collection vessels. 2.2.3. GE ÄKTA system Bench scale purifications were performed using the ÄKTA ® Explorer 100 (GE) platform with Vantage L Laboratory Columns (EMD Millipore) packed with the appropriate resins. The ÄKTA buffer lines were primed with the appropriate buffers and load material for each run. The system was run using the UNICORN TM

(GE) controls software according to the predetermined parameters that were implemented at the other purification scales while preserving residence times seen at other scales. Column effluents were collected in separate containers for each phase of chromatography (e.g. load/flow through, wash, product elution, and strip). Flow-through material was collection during loading and product elution based on UV collection criteria. 2.2.4. Manufacturing scale Pilot and manufacturing scale purification runs were conducted in pilot and commercial facilities. Purification runs were performed in a similar fashion to bench scale using commercially available chromatography skids and columns packed with the appropriate resins (20–80 cm inner diameter). 2.2.5. Analytical assays Purity levels in selected fractions were assessed by high performance size exclusion chromatography (HPSEC) and non-reducing gel electrophoresis (NRGE). Assaying fractions by HPSEC provided monomer and aggregate levels while NRGE provided fragment levels. 3. Results and discussion 3.1. Optimization of a high throughput purification system for purification process development Tecan robotic systems have been employed to carry out automated column chromatography purifications using RoboColumns. Obvious advantages include parallel throughput and decreased volume requirements for load, buffer, and solutions employed. A challenge to the implementation of this approach includes the prerequisite amount of automation knowledge required to write and edit scripts for experiments. We have designed an Excel based tool that addresses this knowledge gap, helping process development scientists to translate bench scale experimental designs into the outputs required to generate Tecan scripts using tools such as the ® TeChrom Wizard . The tool includes an experimental planning section that provides the scientist with information about the amount of load and buffer volumes required, the number of 96-well collection plates needed for the entire experiment and maps out location of eluate fractions in the collection plates. Published literature has described a method for chromatogram generation wherein a plate reader is used to measure A280 of column fractions in a 96 well UV/Vis plate (19). We found that the chromatograms generated using this methodology displays a high degree of variability in A280 measurement due to differences in fraction volumes, droplets on the walls of the plate, and optical scatter due to buffers with high concentrations of salt. The use of 96well UV/Vis collection plates has the added disadvantage of being a high cost consumable relative to the traditional polystyrene plate, and the flat bottom well represents a challenge to automating fraction pooling of the identified product peaks. We have optimized the chromatogram generation by implementing a plate stamping method of 20 ␮L from up to four 96-well plates into a single 384well UV/Vis transparent plate. This transfer limits both the material

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Fig. 1. Example chromatogram generated from the automated Tecan Robotic system using a Protein A RoboColumn for the purification of mAb 1.

required for the chromatogram generation and the total number of UV-transparent plates that are required (a 4 fold reduction is achieved as only one 384-well UV transparent plate is needed as compared to four 96-well UV transparent plates).We then centrifuge the 384-well plate to get a single column of liquid in the bottom of each well. We then quantify the amount of protein in each well by measuring A280 and by subtracting the A340 from the A280 signal to account for any light scattering in the sample. (data not shown). The resulting absorbance data is transformed into a chromatogram for each column run using a macro enabled

chromatogram generation tool that is included in the Excel experimental planning tool. Fig. 1 provides an example of a typical chromatogram that was generated using the optimized chromatogram generation method. The chromatogram is a Protein A affinity capture purification of a monoclonal antibody (mAb 1). In this figure, absorbance can be seen during the column loading/flow-through, during a post-load wash, during product elution, during column strip, and during column sanitization.

Fig. 2. Chromatograms for the Protein A affinity capture of mAb 1 using 8 RoboColumns with varying elution pH. Traces: Each color represents a separate column. (A) Overall chromatogram, (B) Expanded view of elution and strip phases.

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Fig. 3. Chromatograms for the mAb 1 Protein A affinity capture for 8 RoboColumns with varying load pH. Each color represents a separate column. (A) Overall chromatograms, (B) Expanded view of the breakthrough period.

Table 2 Recoveries for the varying Protein A elution pH study shown in Fig. 2. Column

Elution pH

Recovery (%)

Chromatogram Color

1 2 3 4 5 6 7 8

3.6 3.8 4.0 4.2 4.4 4.6 4.8 5.0

92 71 42 8 5 4 4 5

Red Orange Yellow Green Blue Purple Grey Black

The precision of the chromatograms generated using the tool was demonstrated in a study that varied the elution buffer pH for Protein A columns from 3.6 to 5.0. The resulting chromatograms are shown in Fig. 2. Recovery for each elution was calculated based on the absorbance data (Table 2). The macro for the recovery calculation tool is also included in the Excel based tool. Table 2 also provides a guide for the column number and color, elution buffer pH used, and recovery achieved for these purifications. Fig. 2 and Table 2 illustrate that as the elution buffer pH increased from 3.6 (column 1, red) to pH 3.8 (column 2, orange), to pH 4.0 (column 3, yellow) that the corresponding yields for these columns went down from 92%, 71%, and 42%, respectively. Elution buffer pH above pH 4.0 resulted in low recoveries (less than 10%) and minimal protein elution as illustrated by the chromatograms. Fig. 2 demonstrates that as the recoveries go down, the area under the curve for the elution phase drops and the area under the curve for the strip phase increases, as expected. The utility of this RoboColumn tool for the quick evaluation of the process performance robustness and even product quality evaluation of a

Table 3 Dynamic break-through capacities for the varying Protein A load pH study shown in Fig. 3. Load pH

DBC (mg mAb 1/mL Protein A resin) at 10% BT

Chromatogram Color

3.9 4.4 4.7 4.9 5.0 5.2 5.5

7 24 29 37 38 37 43

Red Yellow Green Blue Purple Grey Black

given step is apparent. Numerous purification process parameters can be quickly evaluated using less time and material. The tool was then used to evaluate column loading conditions in a similar manner to measure the effect on dynamic binding capacity. An experiment was performed varying the loading pH of the mAb 1 material for an affinity Protein A capture while conserving the residence time. The resulting chromatograms and tabulated dynamic binding capacities are shown in Fig. 3 and Table 3, respectively. The pH of the loading material was incrementally varied from pH 3.9 (red chromatogram, column 1) to pH 5.5 (black chromatogram, column 8) using pH titration. The dynamic binding capacity (DBC) of each of the conditions was measured by calculating the amount of protein loaded on to the column (mg protein/mL of column volume) at the time point in which breakthrough (BT) occurred (approximately 3.0 optical density units shown in Fig. 3a), defined as 10% of the maximum absorbance observed. As the loading pH was decreased to pH 3.9, the RoboColumn was unable to bind as much protein resulting in an earlier breakthrough and lower DBC. The DBCs presented in Table 3 were normalized

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Fig. 4. Comparison of mixed-mode polish chromatograms for mAb 2 across various purification scales. (A) An average of 8 RoboColumn chromatograms is shown along with 13 ÄKTA scale chromatograms and 4 manufacturing scale chromatograms, (B) for ease of viewing one representative chromatogram from each scale is shown.

with respect to the DBC when loading material was adjusted to pH 5.5. For this system significant process performance reduction (lower DBC) was observed for loading pH less than 4.9.

3.2. Chromatogram comparison of the RoboColumn system with bench-scale and manufacturing-scale systems Chromatograms generated using the RoboColumn system were compared against the commonly used bench scale system (ÄKTA chromatography systems), and manufacturing scale purifications. The results of this comparison are shown in Fig. 4. Initially chromatograms using each of the purification systems were compared by overlaying them after a normalization to the start of the elution phase for each system. This normalization was

performed because variation in load concentration (g mAb/mL load material) and column loading (g mAb/mL column) can result in variation in load duration. It should also be noted that there was a reproducible correlation between elution peak shape and column loadings. Specifically, columns that were under-loaded showed elution chromatogram peaks that were more trapezoidal as compared to Gaussian. Fig. 4a shows the mixed-mode polish chromatograms for mAb 2 across an average of 8 RoboColumns (red chromatogram with a point to indicate each collected fraction), 13 ÄKTA scale chromatograms, and 4 manufacturing scale chromatograms. There is good agreement for the 18 chromatograms shown. Fig. 4b shows one representative chromatogram from each system for ease of viewing.

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Fig. 5. Comparison of data from the Protein A affinity capture of mAb 1 across various purification scales. (A) monomer measured by HPSEC (%); (B) fragment measured by NRGE (%).

3.3. Product quality comparison of the RoboColumn system with bench-scale and manufacturing-scale systems To further evaluate the utility of the RoboColumn, product quality for various mAb 1 and mAb 3 purifications were compared across scales. Protein A affinity chromatography runs across various purifications scales were compared for mAb 1 and the results are shown in Fig. 5. In this figure, the product quality measurements for the protein A product are provided (y-axis) for various purification scales (x-axis). The green diamonds for each data set represent the mean and 95% confidence interval for each of the data sets at the various scales. The column volumes for the various purification scales were as follows: 0.6 mL for RoboColumn, 1.0 mL for Rotary Pump, 20 mL for ÄKTA, 6.9 and 13.4 L for Pilot, and 31.8 and 100 L for Manufacturing scale. Fig. 5a shows the results for the percent monomer purity by HPSEC of the Protein A product across scales. As can be seen in the figure, there is good agreement for the product quality for mAb 1 with all products demonstrating monomer purity above 95%. Fig. 5b shows the results for the percent fragment by NRGE of the Protein A

product across scales. Less than 10% fragment was observed for all of the runs with the manufacturing scale demonstrating lower levels with less variability. There was good agreement for the product quality across the scales for both monomer and fragment. A product quality comparison (% monomer measured by HPSEC) across purification systems (RoboColumn, ÄKTA, and pilot scale) was also performed for mAb 3 across multiple chromatography columns (a Protein A capture, Super Q column polish flow through, and an hydroxyapatite (HA) bind-elute column polish). Data from this evaluation is shown in Fig. 6. The figure shows good agreement for product quality (% monomer) for mAb 3 for the purifications at three scales. These experiments demonstrate consistency in product quality for different modes of chromatography including bead chemistry and elution mode (bind-and-elute versus flowthrough).

3.4. Purification system metrics: material and time comparison In evaluating the utility of the RoboColumn system, a number of factors were compared between the RoboColumn purification

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Table 4 Metrics for comparison of the RoboColumn and ÄKTA purification systems.

Metrics

ÄKTA

Parallel chromatography runs per instrument

1

RoboColumns 8

Column size (mL)

1-20

0.050-0.600

Column hardware

Potentially variable with vendor

Constant regardless of vendor or gel

Load/buffer volume required (mL) (e.g. 5 CV Wash + Holdup + Safety)

200-300

5-10

Run setup time (hr)

1

1

Automated

Yes

Yes

Time per run (hr)

4-6

4-6

Post run processing (hr) (e.g. experimental cleanup and sample submission)

1-2

1-2

In-line measurements (OD trace, pH, conductivity, pressure, peak collection criteria)

Yes

No

Off-line measurements (OD trace, pH, conductivity, peak collection criteria)

Yes

Yes

Product quality analysis possible? (i.e. HPSEC, IEC, RPLC, etc.)

Yes

Yes

Case Study Example Chromatography runs per instrument

8 in Series

8 in Parallel

Column volume (CV)

20 mL

0.6 mL

Total buffer required (mL) (e.g. 20 CVs of various solutions and buffers, add 1.2 CVs for system holdup and as a safety factor)

3,224

97 (33 fold reduction)

Load required (mL) (e.g. 10 CVs, add 1.2 CVs for system holdup and as a safety factor)

1,624 mL total (~224 mL for 1 run)

49 mL total (~7 mL for 1 run)

Load required (grams) (assuming 50 g/L resin loading)

8 g total (~1 g for 1 run)

0.024 g total (~0.03 g for 1 run)

Total consecutive time for all runs (hrs) ( assuming 6 hrs for 1 Run)

48

6

Volume product generated (mL) (assuming 3 CV elution)

60

1.8

Green shading: An advantage of one of the chromatography systems as compared to the other (improved throughput, increased time savings, lower material demands, or additional capabilities) (For interpretation of the references to color in this table legend, the reader is referred to the web version of this article.).

system and the typical ÄKTA scale down model purification system. The results of the comparison are shown in Table 4. The cells in the table for which there is an advantage of one of the chromatography systems as compared to the other are indicated with green shading. The advantage found for using the RoboColumn system include improved throughput, increased time savings, lower material demands, or additional capabilities. The capability to reduce the amount of material needed for each experiment combined with the increasing throughput provides an advantage to the RoboColumn system as a development tool. Further, some cell culture miniaturization and automation ® development tools (ambr bioreactors) produce limited amounts of product. The small consumption of the load material for the RoboColumn system is an advantage as compared to the ÄKTA scale down model. The parallel throughput capability of the RoboColumn system allows for process developers to evaluate more conditions (perform more experiments) in less time and using less material. An eight-fold increase in throughput with the RoboColumn scale column model as compared to traditional ÄKTA scale-down models

can be achieved. Less load and buffers (about 33 fold) are consumed in the RoboColumn system. Product quality analysis is still possible using the RoboColumn system despite the lesser amount (volume and mass) of protein eluted, especially when low volume analytical assays are employed. 4. Conclusion This paper presents the optimization and implementation of a high throughput process development tool. Commercially available micro-liter sized columns were used for the purification of multiple clinically relevant monoclonal antibodies. The development tool enables rapid chromatogram generation and offers advantages over earlier utilized methods. Analysis of protein concentration in 384well UV transparent plates as compared to 96-well plates provide a 4 fold reduction in more expensive UV transparent plates as well as removing the need to correct for path length of column fractions. Chromatographic profiles generated using this optimized tool were shown to overlay with comparable profiles from the conventional

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Fig. 6. Comparison of mAb3 product quality data monomer measured by HPSEC (%) from three column steps (Protein A, Super Q, and HA) and three purification scales (RoboColumn, ÄKTA, and pilot).

bench-scale and clinical manufacturing scale. All measured product quality attributes were comparable across scales for the mAb purifications. The ability to perform up to 8 chromatography purifications in parallel with reduced material requirements per run creates opportunities for gathering more process knowledge in less time for future chromatography process development efforts (e.g., optimization screening or characterization of product quality from small-scale bioreactor experiments). Acknowlegements The authors would like to acknowledge Matthew Dickson, Gisela Ferreira, Omayra Glance, Nicholas Knoepfle, Mimi Richert, and David Robbins (all currently or formerly at MedImmune). Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.chroma.2017.05. 041. References [1] S. Chhatre, N.J. Titchener-Hooker, Review: microscale methods for high-throughput chromatography development in the pharmaceutical industry, J. Chem. Technol. Biotechnol. 84 (2009) 927–940. [2] K.M. Łacki, High-throughput process development of chromatography steps: advantages and limitations of different formats used, Biotechnol. J. 7 (2012) 1192–1202. [3] J.L. Coffman, J.F. Kramarczyk, B.D. Kelley, High-throughput screening of chromatographic separations: i. Method development and column modeling, Biotechnol. Bioeng. 100 (2008) 605–618. [4] J.F. Kramarczyk, B.D. Kelley, J.L. Coffman, High-throughput screening of chromatographic separations: II. Hydrophobic interaction, Biotechnol. Bioeng. 100 (2008) 707–720. [5] B.D. Kelley, M. Switzer, P. Bastek, J.F. Kramarczyk, K. Molnar, T. Yu, J. Coffman, High-throughput screening of chromatographic separations: IV. Ion-exchange, Biotechnol. Bioeng. 100 (2008) 950–963. [6] D.L. Wensel, B.D. Kelley, J.L. Coffman, High-throughput screening of chromatographic separations: III. Monoclonal antibodies on ceramic hydroxyapatite, Biotechnol. Bioeng. 100 (2008) 839–854. [7] T. Bergander, K. Nilsson-Välimaa, K. Öberg, K.M. Łacki, High-throughput process development: determination of dynamic binding capacity using microtiter filter plates filled with chromatography resin, Biotechnol. Prog. 24 (2008) 632–639. [8] A. Susanto, E. Knieps-Grünhagen, E. von Lieres, J. Hubbuch, High throughput screening for the design and optimization of chromatographic processes: assessment of model parameter determination from high throughput compatible data, Chem. Eng. Technol. 31 (2008) 1846–1855.

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Please cite this article in press as: S.T. Evans, et al., Optimization of a micro-scale, high throughput process development tool and the demonstration of comparable process performance and product quality with biopharmaceutical manufacturing processes, J. Chromatogr. A (2017), http://dx.doi.org/10.1016/j.chroma.2017.05.041