A rapid procedure to establish a robust second step in bind/elute (B/E) mode for the purification of a mAb using Capto™ MMC ImpRes resin has been developed. This study presents results from optimization of the elution conditions using the Design of Experiments (DoE) approach. The results show high yield of monomeric mAb, as well as good clearance of aggregates, host cell proteins (HCP), and leached protein A.
Introduction
Cytiva’s mAb toolbox employs protein A chromatography resins such as MabSelect PrismA™ resin for capture of the target. After the initial protein A step, there is a range of options for intermediate and polishing purification steps. One of these options, Capto MMC ImpRes resin, is a cost-effective and flexible chromatography resin designed for high-resolution polishing of mAbs. The resin enhances Cytiva’s mAb toolbox by serving as a polishing resin with multimodal selectivity, enabling high mAb recovery alongside efficient impurity clearance.
This article describes a fast and efficient method to separate monomeric mAb from aggregates, HCP, and leached protein A remnants. The method described includes screening for optimal binding conditions in 96-well plates followed by verification in packed columns and optimization of elution conditions using design of experiments (DoE). The running conditions were then validated in larger scale with satisfactory correlation to DoE model prediction. All preparative chromatography experiments were performed in B/E mode.
A summary of the steps in the study is shown in Figure 1.
Fig 1. The steps used in this performance evaluation of Capto MMC ImpRes resin in removing contaminants from monomeric mAb.
Materials and methods
Start material
The mAb used in this study was initially purified from CHO cell supernatant by protein A affinity chromatography. Some characteristics of the antibody are shown in Table 1.
Table 1. Characteristics of the antibody used in the study
|
Antibody |
pI |
Aggregate content (%) |
DBC QB10% (mg/mL), Capto MMC ImpRes resin |
|
mAb A |
7.3 |
2.5 |
71 |
* Dynamic binding capacity (DBC) at 10% breakthrough measured at 4 min residence time (RT).
Determination of static binding capacity
Static binding capacity (SBC) was determined in 6 µL PreDictor™ Capto MMC ImpRes 96-well plates. Equilibration of wells in the plates was performed by addition of 200 µL of loading buffer per well followed by agitation at 1100 rpm for 1 min, after which the buffer was removed by vacuum suction. The equilibration step was performed three times.
The mAb, partially purified by protein A affinity chromatography (200 µL volume, 4 mg/mL sample load, corresponding to 133 mg mAb/mL chromatography resin) was added to each well followed by agitation for 90 min. Unbound material [flowthrough (FT) fraction] was removed by centrifugation for 1 min, and mAb concentration was determined by measurement of absorbance at 280 nm.
SBC was calculated according to:
mAbbound = 0.2 × (Cin - Cout) (mL × mg/mL = mg)
SBC = mAbbound/Vresin = mAbbound/0.006 (mg/mL)
where Cin = mAb concentration in sample, Cout = mAb concentration in FT fraction, and Vresin = resin volume in each well (i.e., 6 µL).
Determination of dynamic binding capacity
Dynamic binding capacity (DBC) was determined by frontal analysis using an ÄKTA™ chromatography system.
The UV-absorbance at 280 nm was used for determination of breakthrough. The dynamic binding capacity was then calculated according to:
QBX% = (VX% - V0) * C0/Vc
were VX% = load volume (mL) at x% breakthrough, V0 = void volume (mL), C0 = mAb concentration in the sample (mg/mL), and Vc = volumetric bed volume (mL).
Screening of elution conditions
Conditions for optimizing elution were investigated in a Tricorn™ 5/50 packed column with Capto MMC ImpRes resin at a bed height of 4.7 cm. We optimized the elution using ÄKTA™ avant 25 chromatography system, DoE, and scouting functionalities included in UNICORN™ software. The factors considered in the design were load volume, gradient length, and flow velocity. The responses were resolution of monomer/aggregates and pool volume.
The method used for the DoE runs was the following:
Column: Tricorn 5/50, bed height 4.7 cm
Resin: Capto MMC ImpRes
Sample: mAb (8 mg/mL) equilibrated in start buffer
Start buffer: 25 mM sodium phosphate, 25 mM sodium citrate, 100 mM NaCl, pH 6.0
Elution buffer: Start buffer + 1 M NaCl
CIP: 1 M NaOH
Determination of mAb aggregates and aggregate clearance
Fractions from the chromatographic runs were collected and analyzed by analytical size exclusion chromatography (SEC) on a Superdex™ 200 5/150 GL column. The peaks were integrated and the dimer/aggregate content (in percent) were estimated. Cumulated yield of monomers was plotted against cumulated aggregates (Fig 2).
Protein A and HCP ELISA
The protein A concentration in the start materials and flowthrough fractions was determined by Protein A ELISA kit (Repligen). HCP concentration was determined by HCP ELISA (Cygnus Technologies).
Fig 2. Evaluation of gradient elution was performed by SEC. The Figure shows an example of the resulting plot of cumulated yield of monomers vs cumulated aggregates derived from the SEC analysis.
Results and discussion
Case study
The case study with mAb shows a suggested workflow for method development including screening of binding conditions in 96-well format, verification of dynamic binding capacities in column format, screening-, optimization of elution conditions, and validation of the DoE model prediction in a HiScreen™ chromatography column. It also includes a Monte Carlo simulation that addresses the protocol robustness.
Static binding capacity
To find optimal binding capacity for the mAb, we determined static binding capacity (SBC) in 6 µL PreDictor 96-well filter plates. Binding pH was varied between pH 4.0 and 8.0(1,2) and salt concentration from 0 to 500 mM NaCl. All samples and buffers were prepared automatically using an automatic liquid handling system for the preparation of buffers. The results from the SBC study display an area of conditions with high binding capacities between pH 5.0 and 7.0 and NaCl between 0 and 150 mM. The highest SBC was obtained at approx. pH 6.0 and salt concentration of 0 to 150 mM (Fig 3). The binding capacity appeared to be more salt tolerant at lower pH and could represent an alternative binding condition. This is important to take into account since the choice of binding conditions affects the elution strategy. When binding at pH between 6.0 and 6.5, elution can be performed merely using a salt gradient whereas binding at pH between 5.0 and 5.5 is likely to require salt and pH gradient elution.
1Start buffers were sodium acetate, pH 4.0 and 5.3; sodium phosphate, pH 6.3; Tris, pH 8.0.
2 To avoid deamidation of the mAb, pH should normally be maintained below pH 8.0.
Fig 3. Contour map showing screening of SBC for Capto MMC ImpRes resin. The lower right corner is excluded since mAb tended to precipitate at pH > 6.7 and low salt concentration.
Dynamic binding capacity
The area with high SBC in the PreDictor plate studies—between pH 5.0 and 6.0 and NaCl content between 0 and 200 mM—were chosen for further investigation in column format. This particular mAb tended to precipitate at pH > 6.7 at certain conditions, which explains the choice of pH values for verification.
The trends seen in the PreDictor plate SBC experiment correlated well with the DBC studies (Fig 4). The condition with highest DBC (100 mM NaCl, pH 6.0) was chosen for further investigation in which the influence of residence time was studied (Fig 5). The DBC was found to be relatively independent of residence time in the investigated interval.
Fig 4. Dynamic binding capacity of Capto MMC ImpRes resin at 4 min RT in different salt concentrations and two different buffer pH.
Fig 5. Influence of residence time on DBC measured at 10% breakthrough.
Investigating elution conditions for selectivity
As high binding capacities were found at pH 5.0 to 7.0, aggregate removal and yield were investigated by linear NaCl gradient elution at pH 5.0, 6.0, and 7.0 (Fig 6).
Fig 6. Elution of the mAb in a salt gradient at three different pH: (A) pH 5.0, (B) pH 6.0, and (C) pH 7.0.
We collected fractions and performed SEC analysis. Fractions containing 90% of the mAb were pooled and analyzed for HCP and protein A content. A summary of the results is found in Table 2. As can be seen, efficient aggregate removal at 90% yield was obtained for all three binding pH values. However, at pH 5.0, larger pool volumes were observed and precipitation was observed at pH 7.0. Therefore, the conditions chosen were binding at pH 6.0 and elution with an NaCl gradient.
If higher purity levels or higher yield at maintained purity had been required than the performance observed, a pH closer to 5.0 for binding and NaCl gradient elution would be a suitable alternative.
Table 2. Summary of the results of the chromatography at different pH; start concentrations for HCP and protein A are shown in brackets
|
pH |
Aggregate at 90% yield (%) |
Pool volume (CV) |
HCP (ng/mL) |
Protein A (ng/mL) |
|
5.0 |
0.04 |
14.1 |
16 (245) |
Below LOQ* (16) |
|
6.0 |
0.2 |
5.4 |
56 (245) |
Below LOQ (16) |
|
7.0 |
0.2 |
6.5 |
44 (245) |
Below LOQ (16) |
* LOQ = Limit of quantitation
Optimization of purification performance
The binding study showed that binding at pH 6.0 with an addition of 100 mM NaCl resulted in high binding capacities. Also high purity and yields were obtained at pH 6.0 using a linear salt gradient for elution.
We could have stopped further evaluation at this point, but to build understanding and to optimize the purification performance, we instead set up a DoE model to evaluate the influence of three factors on aggregate content and pool volume. The factors that were varied and responses are displayed in Table 3.
The reduction of HCP and protein A was not included as a response in the design but was measured. The start concentration of HCP was 164 ng/mL and the start concentration of protein A was 26 ng/mL. Other factors that affect the purification performance and could be of interest to study from a robustness perspective using this methodology are, for example, aggregate content or HCP levels.
The rationale behind the high and low levels of the parameters in the DoE model was as follows; flow velocity was chosen to ensure that high and low flow velocities corresponded to a residence time (RT) of 2 and 8 min, respectively. For many processes, it is not possible to have shorter RT than 2 min due to limitations in the pumps and other equipment. The low flow velocity gives a longer RT but is still acceptable.
Gradient length was between 5 and 15 CV. The short gradient length of 5 CV challenged the performance of Capto MMC ImpRes since this gradient is shorter than most gradients used in purification processes today. A gradient length of 15 CV is closer to that typically used by process developers and represents an average, normal gradient length.
In this study, we used loads of 42 and 30 mg sample/mL. These represent loading of 70% and 50%, respectively of the DBC 10%. A load of 70% of DBC 10% is usually regarded as the upper limit for loading without risking any leakage of target molecules. A load of 50% of DBC 10% is substantially lower, but represents a plausible loading for a process.
Table 3. Factors and levels studied in by DoE
|
Factors |
Low |
High |
|
Load (mg/mL mAb) |
30 |
42 |
|
Gradient length (CV) |
5 |
15 |
|
Flow velocity (cm/h) |
37 |
140 |
Aggregate removal
Flow rate and gradient length were found to significantly affect aggregate removal while the influence of load was insignificant. Lower flow rates and longer gradients resulted in lower aggregate amounts. The significant factors in the model are shown in the coefficient plot (Fig 7A).
The summary plot in Figure 7B shows different model characteristics such as model fit (R2), an estimate of the precision of future predictions, model validity, and information on the reproducibility. The summary plot indicates that the model is valid.
Table 4. Summary of the factors and responses used in the three-factor screening design
|
Factors |
Responses |
|||||
|
Flow velocity (cm/h) |
Gradient length (CV) |
Sample load (mg/mL) |
Pool volume (CV) |
Aggregate at 90% yield (%) |
HCP (ng/mL) |
Protein A (ng/mL) |
|
37 |
5 |
30 |
2.7 |
0.4 |
93 |
* |
|
37 |
15 |
30 |
4.9 |
0.23 |
39 |
* |
|
37 |
15 |
42 |
6.0 |
0.26 |
71 |
* |
|
89 |
10 |
36 |
4.3 |
0.39 |
41 |
* |
|
89 |
10 |
36 |
4.3 |
0.39 |
60 |
* |
|
89 |
10 |
36 |
3.8 |
0.37 |
27 |
* |
|
140 |
5 |
30 |
3.3 |
0.48 |
58 |
* |
|
140 |
15 |
30 |
5.4 |
0.37 |
74 |
* |
|
140 |
5 |
42 |
3.3 |
0.42 |
62 |
* |
|
140 |
15 |
42 |
6.0 |
0.37 |
79 |
* |
* Below LOQ.
Fig 7. (A) Coefficient plot showing factors affecting the aggregate removal. (B) Summary plot showing different model characteristics for the aggregate removal response.
Pool volume
Gradient length and sample load were significant factors affecting pool volume (Fig 8). The summary plot in Figure 9B describes the characteristics and validity of the model.
Fig 8. (A) Coefficient plot showing factors affecting pool volume. (B) Summary plot showing different model characteristics for the response pool volume.
Prediction of aggregate removal and pool volumes using DoE and Monte Carlo simulation
To find optimal parameters for a purification protocol and investigate the robustness of that protocol, a Monte Carlo simulation based on the DoE model was used. The investigated design space for the DoE model and the target purification performance are shown in Table 5. The suggested chromatographic protocol and the allowed variation in each factor (triangular distribution) are shown in Table 6.
A Monte Carlo simulation was used in order to assess the design space with probabilities of failing to meet the target purification performance. The resulting design space defined by the Monte Carlo simulation is shown in Figure 9.
Table 5. Factors, responses, and target values for optimization in the DoE model
|
Factors |
Low |
High |
|
Flow velocity (cm/h) |
37 |
140 |
|
Gradient length (CV) |
5 |
15 |
|
Load (mg/mL) |
30 |
42 |
|
Response |
Criterion |
Target |
Max. |
|
Aggregate content (%) |
Minimize |
0.2 |
0.4 |
|
Pool volume (CV) |
Minimize |
2.0 |
4.5 |
Table 6. Factors, variation, and distribution of the factors of the final purification protocol used in the Monte Carlo simulation
|
Factors |
Low |
Optimum |
High |
Distribution |
|
Flow velocity (cm/h) |
46 |
49 |
52 |
Triangular |
|
Gradient length (CV) |
10 |
10.5 |
11 |
Triangular |
|
Load (mg/mL) |
31 |
34 |
36 |
Triangular |
Fig 9. Contour plots from the Monte Carlo analysis showing risk of failing (red area), as well as running conditions to meet the desired purification performance (green area) at flow velocities of (A) 46, (B) 49, and (C) 52 cm/h.
Validation of the DoE model
To validate the model, running conditions that would fulfill the desired purification performance (Fig 10, green area) were chosen and applied to a 4.7 mL HiScreen Capto MMC ImpRes column on ÄKTA avant 25 chromatography system. Flow rate and load volume were recalculated according to the size of the HiScreen column (see Materials and methods).
The chosen running conditions are summarized below and the purification performance was predicted using UNICORN software. The factor settings selected for validation of the model are shown in Table 7.
Column: HiScreen Capto MMC ImpRes, 4.7 mL
Sample: 20.25 mL mAb A (34 mg/mL) in 25 mM sodium citrate +100 mM NaCl, pH 6.0
Start buffer: 25 mM sodium citrate + 100 mM NaCl, pH 6.0
Elution buffer: Start buffer + 1 M NaCl
Flow velocity: 49 cm/h
Gradient: 0% to 100% in 10.5 CV
System: ÄKTA avant 25
Table 7. Factors selected for validation of the model
|
Flow velocity (cm/h) |
Gradient length (CV) |
Sample load (mg/mL) |
|
49 cm/h |
10.5 |
34 |
Table 8. Comparison of the responses between the predicted value from the model and the validation run using a HiScreen Capto MMC ImpRes column with the predicted settings
|
Identity |
Aggregate at 90% yield (%) |
Yield at 1% aggregate (%) |
Pool volume (CV) |
|
Predicted value |
0.34 |
NA |
4.1 |
|
HiScreen Capto MMC ImpRes |
0.39 |
> 95 |
4.0 |
Conclusions
This work describes a rapid procedure to establish a robust second step in B/E mode for the purification of a mAb using Capto MMC ImpRes resin. The resin provides high yield of monomeric mAb, as well as good clearance of aggregate, HCP, and leached protein A. We also show a model approach to the choice of running parameters defined by the desired purification performance.
Additional resources
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