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Ac c e p te d P r e p r i n t This article is protected by copyright. All rights reserved 1 Bioseparations and Downstream Processing Biotechnology and Bioengineering DOI 10.1002/bit.25639 Development of Robust Antibody Purification by Optimizing Protein-A Chromatography in Combination with Precipitation Methodologies Srinivas Chollangi, Ray Parker, Nripen Singh, Yi Li*, Mike Borys, Zhengjian Li Biologics Development, Global Manufacturing & Supply, Bristol-Myers Squibb *Corresponding Author: Yi Li Contact Information: 35 South St Hopkinton, MA 01748 Phone: (9784) 784-6513 Email: [email protected] Key Words: Monoclonal Antibody, Protein-A Chromatography, High-Throughput Screening, Precipitation Running Title: Impurity Clearance during antibody purification This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: [10.1002/bit.25639] This article is protected by copyright. All rights reserved Received February 18, 2015; Revision Received April 23, 2015; Accepted April 28, 2015

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Bioseparations and Downstream Processing Biotechnology and Bioengineering DOI 10.1002/bit.25639

Development of Robust Antibody Purification by Optimizing Protein-A

Chromatography in Combination with Precipitation Methodologies†

Srinivas Chollangi, Ray Parker, Nripen Singh, Yi Li*, Mike Borys, Zhengjian Li

Biologics Development, Global Manufacturing & Supply, Bristol-Myers Squibb

*Corresponding Author: Yi Li

Contact Information:

35 South St

Hopkinton, MA 01748

Phone: (9784) 784-6513

Email: [email protected]

Key Words:

Monoclonal Antibody, Protein-A Chromatography, High-Throughput Screening, Precipitation

Running Title: Impurity Clearance during antibody purification

†This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: [10.1002/bit.25639] This article is protected by copyright. All rights reserved Received February 18, 2015; Revision Received April 23, 2015; Accepted April 28, 2015

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Abstract

To be administered to patients, therapeutic monoclonal antibodies must have very high purity, with process

related impurities like host-cell proteins (HCPs) and DNA reduced to <100ppm and <10ppb respectively relative

to desired product. Traditionally, Protein-A chromatography as a capture step has been the work horse for

clearing a large proportion of these impurities. However, remaining levels of process and product related

impurities still present significant challenges on the development of polishing steps further downstream. In this

study, we have incorporated high throughput screening to evaluate three areas of separation a) Harvest

treatment b) Protein-A Chromatography and c) Low pH Viral Inactivation. Precipitation with low pH treatment of

cell culture harvest resulted in selective removal of impurities while manipulating the pH of wash buffers used in

Protein-A chromatography and incorporating wash additives that disrupt various modes of protein-protein

interaction resulted in further and more pronounced reduction in impurity levels. In addition, our study also

demonstrate that optimizing the neutralization pH post Protein-A elution can result in selective removal of

impurities. When applied over multiple mAbs, this optimization method proved to be very robust and the

strategy provides a new and improved purification process that reduces process related impurities like HCPs and

DNA to drug substance specifications with just one chromatography column and open avenues for significant

decrease in operating costs in monoclonal antibody purification. This article is protected by copyright. All rights

reserved

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1. Introduction

Monoclonal antibodies and their derivatives are currently a major source of revenue generation in global

biotechnology market (Lawrence 2007a; Lawrence 2007b). However, process economics can be greatly

influenced by the choice of expression and purification steps. Recent advances in cell line selection, growth

media and feeding strategies have led to significant improvement in cell densities and, expression levels are

consistently reaching 5 – 10g/L across the industry in a 14 day fed-batch process (Huang et al. 2010).

Consequently, process bottlenecks have shifted downstream and purification costs are now outweighing the

upstream cell culture costs (Follman and Fahrner 2004; Gagnon 2012; Guiochon and Beaver 2011).

Implementation of platform approach has greatly reduced downstream operation costs but challenges

associated with meeting final drug substance specifications still remain (Guiochon and Beaver 2011; Shukla et al.

2007).

For monoclonal antibodies purification platform, Protein-A chromatography is still the most robust step in

removing process and product related impurities (Vunnum 2009a). Owing to its specific affinity towards Fc

region containing antibodies and fusion proteins and, its ability to tolerate high conductivities, Protein-A

chromatography allows direct loading of harvested cell culture fluid (HCCF) and enables removal of a vast

majority of process and product related impurities while enriching the antibody pool (Vunnum 2009a).

Nevertheless, remaining impurities after Protein-A still present a significant challenge to the purification steps

downstream in order to achieve the drug substance specifications suitable for patient administration (Guiochon

and Beaver 2011; Liu et al. 2010). In addition, it has been consistently shown that Protein-A chromatography

alone constitutes more than a quarter of the total raw materials costs in downstream purification of the

antibodies (Follman and Fahrner 2004). Thus, optimal and efficient usage of Protein-A affinity resin is critical to

achieve high product quality and reduce the costs of antibody production.

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During Protein-A chromatography, post load wash step is a key means to achieve impurity clearance.

Manipulating the pH of wash buffer is usually the first choice and conventionally, a wash step with a pH between

the load and elution conditions is employed for Protein-A chromatography (Group 2009; Vunnum 2009a). The

pH of this intermediate wash is lowered as low as possible without initiating premature elution of the product

and this requires molecule specific effort. With this approach, HCP levels post Protein-A are usually in the range

of 3,000 to 12,000 ppm as reported in a case-study conducted by a consortium of biotech industry specialists

(Group 2009). Typically, this requires an additional of at least two chromatography steps to further purify and

polish the product to achieve drug substance specifications (Group 2009). In 2007, Shukla and Hinckley (Shukla

and Hinckley 2008) reported one of the first successful attempts to enhance the performance of Protein-A

chromatography by evaluating a number of wash additives like sodium chloride, urea, propylene glycol, ethanol,

isopropanol, tween-80, spermine and sodium sulfate during Protein-A chromatography. Based on the results,

they have identified urea as the best wash additive to achieve effective removal of HCPs. The levels of HCPs

reported upon incorporating urea wash were in the range of 1,000 – 3,500 ppm where recovery of the product

varied between 70% and 100%. However, it is also to be noted that at high concentrations, agents like urea,

ethanol and isopropanol can destabilize the structure of proteins through formation of hydrogen bonds with

peptide groups and exposing hydrophobic residues (Herskovits and Jaillet 1969; Herskovits et al. 1970a;

Herskovits et al. 1970b; Lim et al. 2009). On the other hand, presence of small amounts of sodium chloride,

sodium sulfate, propylene glycol and tween-80 are shown to help stabilize the protein structure by interacting

with the polar residues on the surface of the molecule (Agarkhed et al. 2013; Damodaran and Kinsella 1981;

Kerwin et al. 1998; Thurow and Geisen 1984). In addition, like other agents mentioned above, L-Arginine is

known to help stabilize monoclonal antibodies by breaking non-specific interactions between proteins and

preventing aggregation (Lange and Rudolph 2009; Schneider et al. 2011; Shukla and Trout 2010). Studies by

Yumioka et al., and Shujun Sun have shown that L-Arginine can also be used as a wash reagent to reduce

impurity levels during Protein-A chromatography (Sun 2013; Yumioka et al. 2010). HCP levels were reported to

be reduced by about 90-95% in Protein-A product pool using this strategy. However, in both of these cases, the

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HCP levels are still high compared to final drug substance specifications and require two more steps for further

polishing. Also, with the lack of high-throughput automation technologies at the time, all of these experiments

were carried out in a single case by case manner and limited the scope of identifying the most optimal

concentration and combinations of the additives that can yield better results.

Following the above works, significant efforts were focused on identifying the HCPs that are binding to Protein-A

column and co-eluting with the product during elution (Hogwood et al. 2013b; Jin et al. 2010; Levy et al. 2014;

Sisodiya et al. 2012; Tait et al. 2012; Tarrant et al. 2012). These studies demonstrated that the type of HCPs co-

eluting with product varied from molecule to molecule and from one expression system to the other, making the

development of effective platform purification process for Protein-A chromatography highly challenging

(Sisodiya et al. 2012). More recently, Aboulaich et al (Aboulaich et al. 2014) have covalently cross-linked

monoclonal antibodies to NHS-activated sepharose resin to study their interaction with various host-cell

proteins. Again, these studies confirmed that the type of HCPs associating with the product during Protein-A

chromatography varies from molecule to molecule. In addition, they showed that wash additives like arginine

can help reduce the HCP levels in product pool. However, the study is limited by the fact that the full extent of

interactions between process related impurities and the antibody is not captured because, unlike in cell culture

broth, the complete surface of antibody is inaccessible to the HCPs after its prior immobilization to the

sepharose resin. This limits the number of sites on the monoclonal antibody available for HCP interaction and

thereby not all HCP populations that normally interact with the antibody are accounted for. Also, the HCP

interaction with Protein-A ligand and co-elution with product during low pH treatment is not captured in such

setting. In addition, in all the above studies, the focus has been primarily on understanding HCP interaction and

removal during Protein-A chromatography and did not evaluate the effects of HCP clearance during Protein-A

chromatography in context with other steps (e.g. harvest clarification and low pH viral inactivation) involved in

typical purification platform.

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Recent advancements in high-throughput automation technologies have enabled rapid acquisition of large

datasets under several different operating conditions (Coffman et al. 2008; Kelley et al. 2008; Kramarczyk et al.

2008). This enables a practical strategy to establish a framework where customized wash steps for a particular

mAb is optimized together with harvest clarification and viral inactivation. Exploiting this, in this study we

incorporated high-throughput screening to investigate the effects of pH, buffer composition and a range of wash

additives (caprylic acid, propylene glycol, triton x-100, arginine, urea, isopropanol, EDTA and sodium chloride) to

identify the most optimal conditions for effective HCP removal and further improve the performance of Protein-

A chromatography. The wash additives employed and the high-throughput design of the study was aimed at not

only identifying an effective wash condition, but also understand the nature of interactions between the HCPs

and the antibody during Protein-A chromatography. This method of screening can serve as a template for all

therapeutic antibodies coming in the pipeline to rapidly identify an effective wash strategy during Protein-A

chromatography. In addition, combining this strategy with additional screening on separation techniques like

precipitation during cell culture harvest and optimizing the neutralization pH post Protein-A chromatography

yielded highly improved impurity clearance essentially meeting drug substance specifications for HCP and DNA

clearance with just one column process. When tested across multiple molecules, this method proved very robust

and can be effectively used to significantly improve the product quality while minimizing the load and cost on

subsequent operations.

2. Materials & Methods

2.1 Cell Culture and Harvest Treatment

Proprietary CHO cell lines engineered from either DG44 parental cells or GS parental cells were used to produce

the null harvest or harvests containing recombinant monoclonal antibodies (mAb1, mAb2, mAb3 and mAb4). All

cells were cultured using a chemically defined, animal component-free media. The bioreactors were operated in

a fed-batch mode with continuous feeds based on maintaining glucose concentration between 2 and 4 g/L.

Titers were measured using a Protein-A HPLC system (Agilent 1100, Waters Corporation, USA) with an

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established reference standard. During the harvest, cell culture suspensions were collected and then were either

left untreated or treated using acid titrants (acetic acid or citric acid) to lower the pH to desired range.

Treatment was carried out for 30mins under gentle mixing. Following treatment, the harvest material was

centrifuged and filtered using a depth filter (60SP05A, 3M, USA) followed by 0.8/0.2m filter capsule (Pall

Corporation, USA). Post filtration, pH of the clarified harvest was adjusted to a range between 7.0 and 7.2 using

2M Tris and subjected to analytical analyses to assess impurity reduction.

2.2 Protein-A Chromatography

GE healthcare’s MabSelect Protein-A resin was used for all capture chromatography experiments. Preparative

scale column-based chromatography experiments were carried out using an ÄKTA Avant instrument (GE

Healthcare Life Sciences, Sweden) controlled by Unicorn 6.3 software. All columns were packed in the lab

according to the resin manufacturer’s recommendations. Unless noted, equilibration of the resin was carried out

using phosphate-buffered saline (PBS) at pH 7.4 followed by loading with harvested cell culture fluid (HCCF). The

resin was then subjected to PBS wash followed by an acidic pH wash (pH 5.0 - 6.0) before eluting the mAb using

buffers at pH < 4.0.

2.3 Viral Inactivation and Filtration

Following elution, mAb pool from Protein-A chromatography was subjected to viral inactivation by holding at

low pH (3.4 to 4.0) for 1 hour at room temperature followed by neutralization to desired pH in a range between

4.0 and 9.0. Titration was carried out using 0.1HCl or 2M Tris. Post neutralization, filtration was carried out using

0.8/0.2m filter capsule or a 0.8/0.2m syringe filter (Pall Corporation, USA).

2.4 High Throughput Liquid Handling and Chromatography

Batch-mode high-throughput chromatography experiments were carried out using PreDictor plates packed with

50l MabSelect resin (GE healthcare, Sweden). Liquid handling was conducted in a high throughput manner

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using Tecan Freedom-Evo system equipped with a high-precision Liquid Handler arm (LiHa) and Robotic

Manipulator (RoMa) (Tecan Group, Ltd. Switzerland). Method creation and execution was carried out using

Tecan freedom-evoware software (Tecan group Ltd. Switzerland). Wash buffers containing various additives

were prepared using respective stock solutions and diluting them as needed on the tecan. These buffers are

dispensed and stored in plate format compatible for tecan liquid handling. For a typical batch mode Protein-A

chromatography experiment, the MabSelect resin is equilibrated with PBS followed by loading with HCCF. The

resin is then subjected to either PBS wash or wash buffers containing various additives. The target protein is

then eluted using a low pH buffer (pH < 4.0) and collected into a 96-well plate. The product pool is then

neutralized using 2M Tris followed by filtration using 0.2m filter plate (Pall Corporation, USA). The filtrate is

then subjected various analytical assays to assess product quality and impurity clearance.

2.5 Analytical Characterization

Post capture chromatography and filtration, protein concentration was assayed by high-throughput UV-Vis

spectroscopy using the DropSense96 polychromatic microplate reader (Trinean, Belgium). UV-Vis spectra were

quantified using DropQuant software (Trinean, Belgium). Size exclusion chromatography (SEC) was conducted

using Waters’ Acquity H-Class Bio UPLC® to measure the monomer and aggregate content in the product pool.

Acquity UPLC® BEH200 SEC 1.7 m column (4.6 x 150 mm) was utilized to perform this assay where the mobile

phase consisted of phosphate buffered saline (10mM Phoshphate, 137mM Sodium Chloride, 2.7mM Potassium

Chloride) at pH 6.8 and was run at a flow rate of 1 mL/min. Quantification of monomer, low molecular and the

high molecular weight species was performed using Empower software (Waters Corp. Orlando, FL). In addition,

secondary structure, charge profile and the binding activity were confirmed using circular dichroism (Jasco J-715

spectropolarimeter), iso-electric focusing (ProteinSimple iCE3) and custom ELISA with a reference standard. For

hydrophobicity estimation, primary sequences of the four antibodies in study are aligned using ClustalW2

(Larkin et al. 2007) and identified that the differences between the sequences largely lied in complementarity

determining regions (CDRs). 3D structures of the Fab regions of these four antibodies were built using homology

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modeling tool SWISS-Model (Arnold et al. 2006). Amino acid sequences of CDR loops containing all sequence

differences were identified in these structures and the hydrophobicity scores of these CDR loops were calculated

using Kyte-Doolittle hydrophobicity score (Kyte and Doolittle 1982). ELISA for quantification of residual CHO host

cell proteins (CHO-HCP) and residual Protein-A was conducted in a high throughput manner using the Tecan

liquid handling system. Host cell proteins were quantified using the CHO Host Cell proteins 3rd generation kit

(Cat # F550, Cygnus Technologies, Southport, NC) while residual Protein-A was quantified using Repligen

Protein-A ELISA kit (Cat # 9000-1, Repligen Corporation, USA) according to manufacturer’s protocol. Absorbance

was measured at 450/650 nm using EnVision Multilabel reader (PerkinElmer. Waltham, MA). Data quantification

and analysis was carried out using JMP software (SAS Institute Inc. Cary, NC). Residual CHO DNA in the samples

were measured using real-time quantitative PCR (RT-PCR). RT-PCR was carried out with the 2 x TaqMan

Universal PCR Master Mix kit (Life Technologies, USA) and 7900 HT Real Time PCR system (Life Technologies,

USA) according the manufacturer's instructions.

3. Results and Discussion

3.1 HCPs and DNA co-elution with antibody

Three different load materials a) mAb1 expressing CHO cell HCCF b) null-CHO cell HCCF and c) null-CHO cell HCCF

spiked with purified mAb1 were subjected to Protein-A purification process. Figure 1 shows the amount of

mAb1, HCPs and DNA being loaded and eluted from the Protein-A column. Consistent with the results reported

by Shukla and Hinckley (Shukla and Hinckley 2008) our results show that there is an increase in the HCP and DNA

levels in the elution pools when the antibody is present. This phenomenon is attributed to the non-covalent

interactions between the impurities and the antibody while the interaction between impurities and Protein-A

resin is minimal, particularly in the case of agarose based matrix (Levy et al. 2014; Nogal et al. 2012; Shukla and

Hinckley 2008; Sisodiya et al. 2012; Tarrant et al. 2012). Specifically, Tarrant et al., have compared the

adsorption behavior of host-cell proteins onto agarose based and glass based Protein-A resin matrices (Tarrant

et al. 2012). Using ELISA and SELDI-TOF mass-spectrometric analysis they have identified that the hydrophilic

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agarose based matrices exhibit low degree of interaction with the CHO host-cell proteins while the glass based

ProSep Ultra Plus Affinity (UPA) resin exhibited high degree of non-specific interaction with the host-cell

proteins. This was attributed to the hydrophobic nature of the controlled pore glass (CPG) back-bone of the

ProSep UPA resin. However, in the presence of antibody, both agarose and glass based resins started exhibiting

adsorptive behavior towards CHO host-cell proteins; indicating non-specific interactions between the antibody

and the host-cell proteins. Previous results have also shown that the degree of these antibody-HCP interactions

is highly variable and depends on the antibody present in the HCCF (Sisodiya et al. 2012).

3.2 HCPs associate with mAb through a complex mode of interactions

While the association of HCPs with antibody during Protein-A chromatography is well established, the mode of

this interaction is not well understood yet. A number of groups have used proteomic based approaches to

investigate the profiles of HCPs present in HCCF and the eluates from Protein-A column leading to identification

of specific populations that exhibit strong interaction with antibodies (Hogwood et al. 2013a; Hogwood et al.

2013b; Jin et al. 2010; Levy et al. 2014; Nogal et al. 2012; Shukla and Hinckley 2008; Sisodiya et al. 2012; Tait et

al. 2012; Tarrant et al. 2012). While progress was made to disrupt these interactions between HCPs and

antibody, the remaining levels of impurities are still high and require at least two additional steps to bring the

impurity levels down to drug substance specifications (Group 2009; Shukla and Hinckley 2008). To assess

improved ways that can disrupt these interactions, batch mode high-throughput Protein-A chromatography

experiments were carried out on mAb1 (an IgG4 with a pI between 6.5 and 7.0) using wash buffers at various pH

values and incorporating salts and other wash additives into them. Figure 2 shows the effect of wash buffer pH

on recovery of antibody and removal of HCPs from the product. As shown in panel A, the experiment was

carried out both in the presence and absence of 1M NaCl. In both cases, as expected, results show that there is

pronounced loss of antibody when the pH of wash buffer is lower than 5.0 compared to basic wash buffers with

pH > 7.0. In addition, the presence of 1M NaCl (high conductivity) made the loss of antibody more pronounced

even up to pH 7.0 and starts to show diminishing effect at pH greater than 7.0. Within this range, effect of wash

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buffer pH on the removal of HCPs from product pool is however much more dramatic than the effect on

recovery. Traditionally, an acidic buffer (pH in the range of 6.0 to 5.0) is often employed to wash off impurities

from the Protein-A column and also serve as a transition phase buffer to reduce the pH and help keep the

elution column volumes (CVs) low. However, the results here show that a basic buffer (pH ≥ 8.0) is instead much

more effective in reducing the HCPs from product pool. The presence of NaCl helps in realizing this benefit even

at pH 7.0 or greater. Combined with the recovery data shown in panel A, these results suggest that basic wash

buffers with pH ≥ 9.0 are effective in keeping the recoveries high and obtain selective removal of HCPs from

product pool.

Considering the results shown in figure 1 and keeping the pI of mAb1 (6.5 to 7.0) in view, these results strongly

suggest that electrostatic interactions do play an important role in antibody-HCP interactions. Shown in table I is

the list of iso-electric points of various molecular entities found in HCCF and Protein-A elution pools (Aboulaich

et al. 2014; Gottschalk 2009; Levy et al. 2014). Levy et al., (Levy et al. 2014) have shown that the diverse

population of CHO host cell proteins has a wide range of iso-electric points but a majority of this population has

a pI in the range of 4.5 to 7.0. At pH values between 4.5 and 7.0 mAbs are typically neutral or cationic while DNA

is anionic and a good number of HCPs are either neutral or anionic. This results in a mix of strong electrostatic

interactions and hydrophobic interactions between the mAbs and the impurities thus co-purifying during

elution. However, when the resin is subjected to washes with buffers at high (pH ≥ 8.0), mAbs become either

neutral or more anionic and with DNA and a vast of majority of HCPs being strongly anionic they start

dissociating from other. With mAbs strongly bound to the Protein-A resin owing to their specific affinity, HCPs

and DNA are washed off the column during these high pH washes resulting in product pool enriched with pure

mAb. However, it is also to be noticed that in the pH range of 7.0 to 10.0 there is still some population of HCPs

that is charged or neutral and can bind to the mAbs non-specifically by range of forces like hydrogen bonding,

Van der Waals forces or hydrophobic interactions. To assess whether these interactions can be dissociated using

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wash additives, a high throughput batch-mode chromatography experiment was carried out using wash buffers

containing a combination of salts and various wash additives.

Figures 3A and 3B show the contour maps of residual HCPs present in Protein-A elution pools and the recovery

after subjecting the HCCF loaded resin to washes with various buffers containing additives: sodium chloride,

arginine, EDTA, iso-propyl alcohol (IPA), propylene glycol, sodium octanoate (sodium caprylate/caprylic acid),

triton x-100 and urea. In figure 3A, the color progression represents the levels of HCPs remaining in the elution

pool while in figure 3B, the color progression represents recovery of the monoclonal antibody in elution pool. As

expected, figure 3B shows that the recoveries of the mAb1 are good at high pH and lower when we use low pH

wash buffer in combination with high concentrations of NaCl and wash additives particularly, urea. As observed

in figure 2, the control panel shown in figure 3A demonstrates that high pH buffer is more effective in removing

HCPs from the product pool. In addition, the results also show that supplementing wash buffers with various

wash additives can have a positive effect in reducing the HCPs levels from product pool. Particularly, urea and

arginine demonstrate excellent efficiency in disrupting the interactions between mAb1 and the HCPs. In both

cases, increasing the amount of the wash additive and increasing the pH enhanced the ability of the buffers to

disrupt the antibody-HCP interactions while maintaining good recoveries (figure 3A & 3B, bottom panels). It has

been shown previously that arginine can stabilize proteins by breaking non-specific protein-protein interactions

(Arakawa et al. 2007; Arakawa and Kita 2014; Arakawa et al. 2006; Arakawa and Tsumoto 2003; Borders et al.

1994; Schneider et al. 2011; Shukla and Trout 2010; Tsumoto et al. 2005). The guanidinium group on arginine

was shown to be primarily responsible for this ability as it can affect not only the electrostatic and hydrophobic

interactions but also hydrogen bonds between proteins. On the other hand, urea is shown to interact with

proteins both directly, by forming hydrogen bonds with the protein and indirectly by altering the solvent

environment thereby mitigating the hydrophobic effects that lead to protein-protein interactions. However, it

also to be noted that at high concentrations, urea can start to destabilize the protein structures by forming

hydrogen bonds with peptide groups present in the hydrophobic core of the molecule and unraveling the

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tertiary structure of the protein (Herskovits et al. 1970b; Lim et al. 2009). Thus a careful balance needs to be

maintained in case of urea to retain the protein structure but disrupt non-specific protein-protein interactions.

Combined with the effects of pH described above, both of these wash additives thus appear to be very effective

in disrupting non-specific mAb1-HCP interactions.

A wide variety of metals are often added to cell culture media to boost cell viability and promote high titers.

During the course of cell culture, these metals can bind to antibodies and Gagnon et.al., have shown that in

addition to altering antibody charge and hydrophobicity, metal ions can cause local conformational changes and

lead to formation of secondary complexes with contaminants like HCPs, DNA and endotoxins (Gagnon 2010).

However, in the case of mAb1, our results show that addition of EDTA to the wash buffer only has a modest

effect in terms of HCP removal. At pH 7.0, EDTA has slightly improved effect on HCP removal compared to the

control while at pH 9.0, it appears to behave similar or inferior to the control. Albeit better at pH 7.0, organic

solvent IPA exhibited similar performance to EDTA at pH 9.0. In contrast, propylene glycol and non-ionic

surfactant Triton X-100 appear to be much more effective than the control buffer in breaking down the non-

specific interactions between mAb1 and HCPs at all pH values. Both of these agents are hydrophilic and known

to stabilize proteins by altering solvent environment. Finally, sodium octanoate (also known as sodium

caprylate/caprylic acid) is an eight-carbon saturated fatty-acid chain that is shown in the literature to selectively

precipitate HCPs and other impurities in HCCF(Brodsky et al. 2012). When added to the wash buffers, this agent

proved very effective compared to the control wash, particularly at pH 9.0, and selectively disrupted the

interactions between HCPs and the antibody. Combined together, the effect of high pH, salt and the effects of

urea, arginine, propylene glycol and triton x-100 on strongly disrupting the interactions between HCPs and

mAb1 suggest that the HCPs associate with antibodies through a complex mode of interactions which may

include electrostatic interactions, hydrophobic interactions and hydrogen bonds.

3.3 HCPs can be selectively precipitated by optimizing the neutralization pH post Protein-A

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The ICH Q5A guidance document requires the use of at least 2 orthogonal steps for viral clearance to ensure the

safety of products produced using mammalian cell culture processes (FDA 1998). In addition to nanofiltration,

incubating product pools in low pH environment (pH 3.0 to 4.0) is often used as a robust method to inactivate

enveloped viruses (Brorson et al. 2003; Gagnon 2012; Omar et al. 1996). Given the requirement of low pH

buffers to elute antibodies from Protein-A column, this capture step is often utilized as both a separation as well

as transition for viral inactivation step. However, Protein-A elution pools are often reported to be associated

with turbidity and the extent of this turbidity was shown to be highly variable from antibody to antibody (Tobler

2006; Yigzaw et al. 2006). Depending upon the operating pH of the second chromatography step downstream of

Protein-A , the low pH viral inactivated pool needs to be neutralized to a pH suitable for loading onto the next

column. During this process, a significant increase in turbidity is often reported (Tobler 2006; Yigzaw et al. 2006).

This precipitation and turbidity was viewed as a risk for downstream process as it poses problems of clogging

inline sterile filters. The risk is usually mitigated by using depth filters to remove the precipitants and higher

order aggregates (Yigzaw et al. 2006). In our studies with mAb1, we observed similar precipitation behavior

when we used the control washes without any additives. To further characterize the phenomenon, we have

titrated the viral inactivated pool to various pH values between 4.0 and 8.5 in increments of 0.5 and then filtered

the pools using a 0.2m filter. Figure 4A shows the visual representation of turbidity in the samples pools after

titration while panel 4B shows that the turbidity can be removed by filtration. Panel 4C shows the quantitative

measurement of absorbance reading at 410nm before and after filtration. As it can be noticed, the turbidity

peaked between the pH range of 5.0 and 7.5 and as the pool was titrated to pH values further high, the turbidity

went down. When the filtered pools were subjected to analysis for antibody and HCP contents, results showed

that the precipitation strongly correlated with selective removal of HCPs (Figure 5). In contrast to what one

might expect for an affinity chromatography step, the HCP levels in the elution pool from Protein-A

chromatography have been reported to be as high as 2,000ppm – 50,000ppm (Group 2009; Sisodiya et al. 2012;

Yigzaw et al. 2006). As described above in section 3.2, a vast majority of CHO host cell proteins have a pI in this

pH range of 4.5 to 7.5 and can become less soluble during the neutralization process leading to aggregation and

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precipitation. However, as the pH moves further away from this range i.e. pH > 7.5 or pH < 4.0, the HCPs

become polar and stay solubilized in the solution leading to a decrease in turbidity. Thus, insoluble aggregate

formation during neutralization post viral inactivation is not necessarily an undesirable phenomenon and one

can design a process where the neutralization pH is optimal to get selective precipitation of HCPs while

minimizing any product loss. This optimal pH would vary from one expression system to the other and from one

antibody to another depending up on its surface properties and requires empirical characterization.

3.4 Enhancing impurity clearance by optimizing purification train

The most common purification schemes for monoclonal antibodies utilize Protein A affinity chromatography as a

capture step followed by 2 to 3 chromatographic steps for polishing (Kelley 2009; Vunnum 2009b). Even though

these chromatography steps are able to meet the stringent purification requirements, they are expensive and

often the downstream purification train contributes to about 50-80% of the total costs involved in antibody

purification (Guiochon and Beaver 2011). With rapidly rising demand for therapeutic antibodies, significant

attention is thus being focused on reducing manufacturing costs and improving process efficiency for industrial

scale production. Based on the findings described so far, we have tested various purification schemes to

evaluate the robustness of early separation steps and the most effective and economical purification train.

As described in sections 3.2 and 3.3, majority of CHO host cell proteins are unstable in acidic pH range between

4.5 and 7.0 and can be precipitated out by optimal adjustments to the pH. This can be performed post Protein-A

as well as before Protein-A during cell culture harvest. Lydersen et al., have previously shown that acidification

of fermentation broths can successfully induce precipitation of host cell proteins and cellular debris (Lydersen et

al. 1994). In case of mAb1, we have observed similar behavior (See figure 6). Acidification of the cell culture

broth below pH 5.0 using either citric acid or acetic acid, lead to precipitation and removal of host cell proteins

while maintaining antibody recovery above 95%.

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mAb1 was then subjected to preparative scale purification using various trains (see table II, panel A) where acid

precipitation was used either with control Protein-A process or with optimized Protein-A washes identified in

section 3.2 and optimized neutralization pH identified in section 3.3. Panel B in table II shows the results

achieved using these purification trains. As noted in train 1, purification of the antibody without harvest

treatment and control washes in Protein-A resulted in high levels of host cell proteins while the DNA was

reduced to 10 - 26 ppb. In contrast, using either of the enrichment techniques i.e. harvest treatment or

enhanced Protein-A washes, lead to significant decrease in both HCP and DNA levels. However, among the two,

enhanced Protein-A washes lead to a much greater decrease in the impurity levels compared to acid

precipitation (Train 2 vs. Train 3). When combined with optimization of neutralization pH post viral inactivation,

enhanced Protein-A washes lead to reduction of HCPs and DNA to 10 - 33 ppm and < 1ppb respectively,

essentially meeting the drug substance specifications for HCP and DNA clearance with just one column step. In

train 5, addition of the acid precipitation step prior to Protein-A chromatography lead to a slight improvement in

the product quality, but the gains were at the expense of antibody recovery. Considering these results train 4

was identified as the most optimal for mAb1 purification. In addition, secondary structure analysis using circular

dichroism, charge profile analysis using iso-electric focusing and binding activity analysis using ELISA confirmed

that the antibody subjected to enhanced washes still retained its structural integrity and comparable to

reference standard (data not shown).

3.5 Purification efficiency varies by molecule

Based on the results obtained above, further tests were carried out on additional antibodies to check the effects

of wash pH during Protein-A chromatography and the effect of neutralization pH post viral inactivation on HCP

removal. Shown in Table III is the IgG classification, iso-electric points and estimated hydrophobicity for each of

the mAbs chosen. For hydrophobicity estimation, 3D model structures of the Fab regions of these four antibodies

were built using homology modeling tool SWISS-Model (Arnold et al. 2006) and the hydrophobicity scores of the

CDR loops were calculated using Kyte-Doolittle hydrophobicity score (Kyte and Doolittle 1982). Results suggest

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that mAb3 is the most hydrophobic while mAb1 is the least hydrophobic. Different surface charge and

hydrophobicity from the four mAbs serve the purpose of a broad screening for common mechanisms.

Consistent with the observations made for mAb1, results in figure 7A show that high pH washes are more

effective in removing the HCPs from the product pool. However, the extent of removal clearly varies from

antibody to antibody. Particularly, in comparison to IgG4s (mAb1 and mAb2), the IgG1s (mAb3 and mAb4)

required a wash buffer with a pH of almost 10.0 to achieve similar percentage reduction in HCPs. This is not

unexpected because of the differences in the pI of the molecules and a higher pH is required to make mAb3 and

mAb4 anionic and dissociate the HCPs. However, it is also to be noted that the pH of buffer solution can have

significant impact on the stability of antibodies and alkaline pH, particularly pH > 10 can lead to deamidation of

asparagine residues on the antibody (Pace et al. 2013; Patel and Borchardt 1990a; Patel and Borchardt 1990b).

Thus, one has to exhibit caution on choosing the appropriate pH for wash buffers.

Neutralization pH studies on mAb2, mAb3 and mAb4 post viral inactivation yielded results similar to mAb1. In all

cases, there was an increase in turbidity of the pools with an increase in pH and the peak turbidity started

decreasing when the pH was increased above 7.5 (data not shown). Strongly correlating with this turbidity,

filtration of the samples resulted in removal of HCPs from the pool (Figure 7B). However, unlike other antibodies

in the study, mAb2 exhibited significant loss of recovery in the pH range of 6.0 to 7.0. This pH range coincided

with the iso-electric point of the antibody which might have resulted in aggregation/precipitation of the product

and removal by filtration. Similar observation was not made for mAb1 although the pI was between 6.5 and 7.0.

This suggests that the stability of molecule is highly variable from antibody to antibody and needs empirical

experiments to determine the optimum pH for neutralizing the Protein-A pool.

Having identified the optimal Protein-A wash conditions and the neutralization pH post viral inactivation, mAb2,

mAb3 and mAb4 were subjected to purification using Train 4 (see table II) and compared against the control

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purification process using Train 1. In all cases, implementation of the enhanced Protein-A washes along with

optimization of neutralization pH yielded vastly improved product quality with three out of four mAbs meeting

the drug substance specifications for HCP and DNA removal using just one column process. Even though there

was significant reduction in HCPs and DNA compared to the control process, there was essentially no removal of

high molecular weight (HMW) aggregates in mAb2. For antibodies that have high aggregates in the HCCF,

further optimization is needed to get efficient removal of HMW species. A new generation of Protein-A resins

have recently come into the market that claim to offer resolution between HMW species and the monomer

(Eshmuno-A®, EMD Millipore). In addition, recent studies have also demonstrated removal of HMW aggregates

by harvest treatments using flocculation (Kang et al. 2013). These need to be evaluated in combination with the

above Protein-A washes to gain further improvements in product quality where aggregation of the antibody

poses a problem.

Conclusions

The most common purification schemes for monoclonal antibodies and Fc fusion proteins utilize Protein-A

chromatography for capture followed by 2 to 3 additional steps for intermediate purification and polishing

(Kelley 2009; Vunnum 2009b). While Protein-A removes a vast majority of those impurities, remaining levels of

process and product related impurities present significant challenges downstream. Previous studies have

demonstrated that a bulk of those impurities that co-purify with the antibody do so by associating with the

antibody itself (Levy et al. 2014; Shukla and Hinckley 2008). Proteomic based approaches to investigate the

profiles of HCPs present in HCCF and the eluates from Protein-A column lead to identification of specific

populations that exhibit strong interaction with antibodies (Hogwood et al. 2013a; Hogwood et al. 2013b; Jin et

al. 2010; Levy et al. 2014; Nogal et al. 2012; Shukla and Hinckley 2008; Sisodiya et al. 2012; Tait et al. 2012;

Tarrant et al. 2012). However, common framework to selectively disrupt these interactions between HCPs and

antibody are still lacking.

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In this study, using batch mode high-throughput experiments, effect of pH was tested to selectively disrupt

interactions between the antibody and the HCPs. In contrast to the conventional operation where a wash buffer

pH was always chosen to be between the load pH and elution pH (Vunnum 2009b), results from these studies

suggested that a high pH wash buffer is more effective in removing process related impurities and this was

demonstrated across multiple antibodies. In addition, the high throughput screening technique used in this

study also provided an effective template to comprehensively screen a variety of buffers and wash additives in a

very short time frame. This has lead to rapid identification of optimal concentrations of wash additives like

arginine, urea and caprylic acid that result in getting additional removal of impurities. These results also

suggested that the HCPs associate with antibodies through a complex mode of interactions employing a wide

variety of forces like electrostatic interactions, hydrogen bonds, hydrophobic interactions and/or van der waal’s

forces. Extended studies on proteome and the protein interactions are underway to categorize the residual HCPs

across harvest clarification, Protein-A, and low pH inactivation respectively.

Further, our studies also demonstrate that turbidity associated with Protein-A pools and neutralization

thereafter is not necessarily an undesirable phenomenon. This is usually a consequence of HCPs becoming less

soluble when the product pool pH is at or close to their iso-electric points and thus provide a way to further

reduce the impurities by filtration. When used in combination with other separation techniques like acid

precipitation during cell culture harvest, new wash incorporated Protein-A chromatography and optimal

neutralization of product pool post Protein-A can lead to removal of HCPs and DNA to drug substance

specifications with just one column. This would essentially reduce the need for additional polishing and leave

opportunities for the subsequent steps to add robustness and focus on objectives such as viral clearance.

Integral to purification process of any therapeutic molecule is the demonstration of robust viral clearance along

with other impurity clearance (Bray 2004; CPMP/BWP/269/95 2001; Shi et al. 2004; Zhou 2007). Initial studies

have demonstrated that compared to Protein-A chromatography with phosphate buffer wash only,

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incorporation of the enhanced Protein-A wash led to two to three additional logs of clearance for retroviruses,

and between one and three additional logs of clearance for parvoviruses (data not shown). A comprehensive

analysis of improved virus clearance across multiple purification steps (i.e. harvest clarification, protein-a

chromatography, polishing chromatography and virus filtration) is ongoing and will be presented as a part of

future work. To be acknowledged is also the fact that current conditions identified here in Protein-A

chromatography are not optimal for separating high molecular weight aggregates or various glycoforms of the

proteins. Those areas are currently being explored together with new generation Protein-A resins as well as

novel flocculation techniques.

In summary, with high-throughput framework we can rapidly develop a robust Protein-A purification strategy

and co-optimize with harvest treatment and viral inactivation. Such screening can employ common strategies

for most mAbs (Figure 3, Figure 4, Table II), as well as identify molecule specific strategies (Figure 7, Table IV) to

accomplish the robustness. When combined with recent advancements in depth filtration and flocculation

techniques, the empowered Protein-A can represent a significant leap in process economics while meeting the

drug substance specifications and maintaining critical product attributes.

Acknowledgements

We would like to acknowledge the contributions from Bristol-Myers Squibb Process Analytics department for

supporting us with various assays and the upstream department for providing us with the harvest material. We

also thank Dr. Yuanli Song for performing molecular simulation.

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References

Aboulaich N, Chung WK, Thompson JH, Larkin C, Robbins D, Zhu M. 2014. A novel approach to monitor clearance of host cell proteins associated with monoclonal antibodies. Biotechnol Prog 30(5):1114-24.

Agarkhed M, O'Dell C, Hsieh MC, Zhang J, Goldstein J, Srivastava A. 2013. Effect of polysorbate 80 concentration on thermal and photostability of a monoclonal antibody. AAPS PharmSciTech 14(1):1-9.

Arakawa T, Ejima D, Tsumoto K, Obeyama N, Tanaka Y, Kita Y, Timasheff SN. 2007. Suppression of protein interactions by arginine: a proposed mechanism of the arginine effects. Biophys Chem 127(1-2):1-8.

Arakawa T, Kita Y. 2014. Multi-faceted arginine: mechanism of the effects of arginine on protein. Curr Protein Pept Sci 15(6):608-20.

Arakawa T, Kita Y, Ejima D, Tsumoto K, Fukada H. 2006. Aggregation suppression of proteins by arginine during thermal unfolding. Protein Pept Lett 13(9):921-7.

Arakawa T, Tsumoto K. 2003. The effects of arginine on refolding of aggregated proteins: not facilitate refolding, but suppress aggregation. Biochem Biophys Res Commun 304(1):148-52.

Arnold K, Bordoli L, Kopp J, Schwede T. 2006. The SWISS-MODEL workspace: a web-based environment for protein structure homology modelling. Bioinformatics 22(2):195-201.

Borders CL, Jr., Broadwater JA, Bekeny PA, Salmon JE, Lee AS, Eldridge AM, Pett VB. 1994. A structural role for arginine in proteins: multiple hydrogen bonds to backbone carbonyl oxygens. Protein Sci 3(4):541-8.

Bray J, Brattle, K. 2004. Monoclonal Antibody Production: Minimizing virus safety issues. New York, NY: Plenum Publishers. 199-225 p.

Brodsky Y, Zhang C, Yigzaw Y, Vedantham G. 2012. Caprylic acid precipitation method for impurity reduction: an alternative to conventional chromatography for monoclonal antibody purification. Biotechnol Bioeng 109(10):2589-98.

Brorson K, Krejci S, Lee K, Hamilton E, Stein K, Xu Y. 2003. Bracketed generic inactivation of rodent retroviruses by low pH treatment for monoclonal antibodies and recombinant proteins. Biotechnol Bioeng 82(3):321-9.

Coffman JL, Kramarczyk JF, Kelley BD. 2008. High-throughput screening of chromatographic separations: I. Method development and column modeling. Biotechnol Bioeng 100(4):605-18.

CPMP/BWP/269/95. 2001. Note for guidance on virus validation studies. Wharf, London: Canary. Damodaran S, Kinsella JE. 1981. The effects of neutral salts on the stability of macromolecules. A new approach

using a protein-ligand binding system. J Biol Chem 256(7):3394-8. FDA. 1998. FDA Q5A Guidance Document: Viral Safety Evaluation of Biotechnology Products Derived from Cell

Lines of Human or Animal Origin. In: Administration FaD, editor: Federal Register. Follman DK, Fahrner RL. 2004. Factorial screening of antibody purification processes using three

chromatography steps without protein A. J Chromatogr A 1024(1-2):79-85. Gagnon P. Production of biobetter IgG with enhanced wash and elution of Protein A; 2010 March 24, 2010;

Beijing, China. Gagnon P. 2012. Technology trends in antibody purification. J Chromatogr A 1221:57-70. Gottschalk U. 2009. Process Scale Purification of Antibodies. Hoboken, NJ: John Wiley & Sons. Group CBW. 2009. A-Mab: A Case Study in Bioprocess Development. Guiochon G, Beaver LA. 2011. Separation science is the key to successful biopharmaceuticals. J Chromatogr A

1218(49):8836-58. Herskovits TT, Jaillet H. 1969. Structural stability and solvent denaturation of myoglobin. Science 163(3864):282-

5. Herskovits TT, Jaillet H, DeSena T. 1970a. On the structural stability and solvent denaturation of proteins. 3.

Denaturation by the amides. J Biol Chem 245(24):6511-7. Herskovits TT, Jaillet H, Gadegbeku B. 1970b. On the structural stability and solvent denaturation of proteins. II.

Denaturation by the ureas. J Biol Chem 245(17):4544-50.

Page 22: BMS Publication

AcceptedPrepri n

t

This article is protected by copyright. All rights reserved 22

Hogwood CE, Bracewell DG, Smales CM. 2013a. Host cell protein dynamics in recombinant CHO cells: impacts from harvest to purification and beyond. Bioengineered 4(5):288-91.

Hogwood CE, Tait AS, Koloteva-Levine N, Bracewell DG, Smales CM. 2013b. The dynamics of the CHO host cell protein profile during clarification and protein A capture in a platform antibody purification process. Biotechnol Bioeng 110(1):240-51.

Huang YM, Hu W, Rustandi E, Chang K, Yusuf-Makagiansar H, Ryll T. 2010. Maximizing productivity of CHO cell-based fed-batch culture using chemically defined media conditions and typical manufacturing equipment. Biotechnol Prog 26(5):1400-10.

Jin M, Szapiel N, Zhang J, Hickey J, Ghose S. 2010. Profiling of host cell proteins by two-dimensional difference gel electrophoresis (2D-DIGE): Implications for downstream process development. Biotechnol Bioeng 105(2):306-16.

Kang YK, Hamzik J, Felo M, Qi B, Lee J, Ng S, Liebisch G, Shanehsaz B, Singh N, Persaud K and others. 2013. Development of a novel and efficient cell culture flocculation process using a stimulus responsive polymer to streamline antibody purification processes. Biotechnol Bioeng 110(11):2928-37.

Kelley BD, Switzer M, Bastek P, Kramarczyk JF, Molnar K, Yu T, Coffman J. 2008. High-throughput screening of chromatographic separations: IV. Ion-exchange. Biotechnol Bioeng 100(5):950-63.

Kelley BDB, G; Lee, A. 2009. Downstream Processing of Monoclonal Antibodies: Current Practices and Future Opportunities. Process Scale Purification of Antibodies. p 1-23.

Kerwin BA, Heller MC, Levin SH, Randolph TW. 1998. Effects of Tween 80 and sucrose on acute short-term stability and long-term storage at -20 degrees C of a recombinant hemoglobin. J Pharm Sci 87(9):1062-8.

Kramarczyk JF, Kelley BD, Coffman JL. 2008. High-throughput screening of chromatographic separations: II. Hydrophobic interaction. Biotechnol Bioeng 100(4):707-20.

Kyte J, Doolittle RF. 1982. A simple method for displaying the hydropathic character of a protein. J Mol Biol 157(1):105-32.

Lange C, Rudolph R. 2009. Suppression of protein aggregation by L-arginine. Curr Pharm Biotechnol 10(4):408-14.

Larkin MA, Blackshields G, Brown NP, Chenna R, McGettigan PA, McWilliam H, Valentin F, Wallace IM, Wilm A, Lopez R and others. 2007. Clustal W and Clustal X version 2.0. Bioinformatics 23(21):2947-8.

Lawrence S. 2007a. Billion dollar babies--biotech drugs as blockbusters. Nat Biotechnol 25(4):380-2. Lawrence S. 2007b. IPOs break $1 billion in Q2. Nat Biotechnol 25(8):833. Levy NE, Valente KN, Choe LH, Lee KH, Lenhoff AM. 2014. Identification and characterization of host cell protein

product-associated impurities in monoclonal antibody bioprocessing. Biotechnol Bioeng 111(5):904-12. Lim WK, Rosgen J, Englander SW. 2009. Urea, but not guanidinium, destabilizes proteins by forming hydrogen

bonds to the peptide group. Proc Natl Acad Sci U S A 106(8):2595-600. Liu HF, Ma J, Winter C, Bayer R. 2010. Recovery and purification process development for monoclonal antibody

production. MAbs 2(5):480-99. Lydersen BK, Brehm-Gibson T, Murel A. 1994. Acid precipitation of mammalian cell fermentation broth. Ann N Y

Acad Sci 745:222-31. Nogal B, Chhiba K, Emery JC. 2012. Select host cell proteins coelute with monoclonal antibodies in protein A

chromatography. Biotechnol Prog 28(2):454-8. Omar A, Kempf C, Immelmann A, Rentsch M, Morgenthaler JJ. 1996. Virus inactivation by pepsin treatment at

pH 4 of IgG solutions: factors affecting the rate of virus inactivation. Transfusion 36(10):866-72. Pace AL, Wong RL, Zhang YT, Kao YH, Wang YJ. 2013. Asparagine deamidation dependence on buffer type, pH,

and temperature. J Pharm Sci 102(6):1712-23. Patel K, Borchardt RT. 1990a. Chemical pathways of peptide degradation. III. Effect of primary sequence on the

pathways of deamidation of asparaginyl residues in hexapeptides. Pharm Res 7(8):787-93. Patel K, Borchardt RT. 1990b. Deamidation of asparaginyl residues in proteins: a potential pathway for chemical

degradation of proteins in lyophilized dosage forms. J Parenter Sci Technol 44(6):300-1. Schneider CP, Shukla D, Trout BL. 2011. Arginine and the Hofmeister Series: the role of ion-ion interactions in

protein aggregation suppression. J Phys Chem B 115(22):7447-58.

Page 23: BMS Publication

AcceptedPrepri n

t

This article is protected by copyright. All rights reserved 23

Shi L, Chen Q, Norling LA, Lau AS, Krejci S, Xu Y. 2004. Real time quantitative PCR as a method to evaluate xenotropic murine leukemia virus removal during pharmaceutical protein purification. Biotechnol Bioeng 87(7):884-96.

Shukla AA, Hinckley P. 2008. Host cell protein clearance during protein A chromatography: development of an improved column wash step. Biotechnol Prog 24(5):1115-21.

Shukla AA, Hubbard B, Tressel T, Guhan S, Low D. 2007. Downstream processing of monoclonal antibodies--application of platform approaches. J Chromatogr B Analyt Technol Biomed Life Sci 848(1):28-39.

Shukla D, Trout BL. 2010. Interaction of arginine with proteins and the mechanism by which it inhibits aggregation. J Phys Chem B 114(42):13426-38.

Sisodiya VN, Lequieu J, Rodriguez M, McDonald P, Lazzareschi KP. 2012. Studying host cell protein interactions with monoclonal antibodies using high throughput protein A chromatography. Biotechnol J 7(10):1233-41.

Sun S; 2013 Jan 8, 2013. Arginine wash in protein purification using affinity chromatography. Tait AS, Hogwood CE, Smales CM, Bracewell DG. 2012. Host cell protein dynamics in the supernatant of a mAb

producing CHO cell line. Biotechnol Bioeng 109(4):971-82. Tarrant RD, Velez-Suberbie ML, Tait AS, Smales CM, Bracewell DG. 2012. Host cell protein adsorption

characteristics during protein A chromatography. Biotechnol Prog 28(4):1037-44. Thurow H, Geisen K. 1984. Stabilisation of dissolved proteins against denaturation at hydrophobic interfaces.

Diabetologia 27(2):212-8. Tobler S, Noyes, A., Rajeswski, J., Shpritzer, R., Piacenza, W., Tannatt, W., Cofman, J., Vunnum, S., Kelley, B.

Analysis of Protein A peak precipitates and approaches to reduce peak turbidity; 2006; San Francisco. Tsumoto K, Ejima D, Kita Y, Arakawa T. 2005. Review: Why is arginine effective in suppressing aggregation?

Protein Pept Lett 12(7):613-9. Vunnum S, Vedantham G., Hubbard, B. 2009a. Protein-A based affinity chromatography. In: Gottschalk U, editor.

Process Scale Purification of Antibodies. Hoboken, NJ: John Wiley & Sons, Inc. p 79-102. Vunnum S, Vedantham, G., Hubbard, B.,. 2009b. Protein A-Based Affinity Chromatography. In: Gottshalk U,

editor. Process Scale Purification of Antibodies. Hoboken, NJ: John Wiley & Sons. p 79 - 102. Yigzaw Y, Piper R, Tran M, Shukla AA. 2006. Exploitation of the adsorptive properties of depth filters for host cell

protein removal during monoclonal antibody purification. Biotechnol Prog 22(1):288-96. Yumioka R, Tsumoto K, Arakawa T, Ejima D. 2010. Screening of effective column rinse solvent for Protein-A

chromatography. Protein Expr Purif 70(2):218-23. Zhou J, Dehghani, H. 2007. Development of viral clearance strategies for large-scle monoclonal antibody

production. In: Langer ES, editor. Advances in large scale biomanufacturing adn scale-up production. Rockville, MD: ASM Press/BioPlan Associates Inc. p 1-28.

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List of Tables

Table I. Iso electric points of various class of molecules commonly found in CHO cell harvests and Protein-A elution pools (Aboulaich et al., 2014, Levy et al., 2014, Gottschalk 2009) Table II. A) Conditions employed in various purification trains tested B) Recovery and purity levels of the final mAb pool obtained by purification using various trains shown in panel A Table III. Chemical characteristics of various mAbs used in purification evaluation. §3D structures of the Fab regions were built using homology modeling tool SWISS-Model (Arnold et al. 2006) and hydrophobicity scores of the CDR loops were calculated using Kyte-Doolittle hydrophobicity score (Kyte and Doolittle. 1982) as shown in the last column. According to the surface models, mAb3 is the most hydrophobic while mAb1 is the least hydrophobic molecule. Table IV. Recovery and impurity clearance levels in various mAb pools after purification using Train 1 (Control) or Train 4 (Enhanced Protein-A washes) described in Table IIa

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List of Figures Figure 1. CHO host cell proteins (HCP) and host cell DNA associate with the monoclonal antibodies (mAbs) and co-elute as impurities during low pH elution. Top panel shows the levels of mAb, HCPs and DNA loaded onto the Protein-A column while bottom panel shows the levels of mAb, HCPs and DNA present in the Protein-A eluate. The loading material came from either CHO cell supernatant expressing mAb, null cell supernatant or null cell supernatant spiked with purified mAb. Figure 2. High pH washes aid in reducing the HCP levels in Protein-A eluate without a loss of recovery. A) Recovery of mAb in Protein-A eluate is plotted against the pH of wash buffer used during Protein-A chromatography. B) HCP (ppm) levels in Protein-A eluate are plotted against the pH of wash buffer used during Protein-A chromatography. All experiments were conducted either in the presence or absence of 1M NaCl in the wash buffers. Error bars represent standard deviation of the analytical results. (* & **, p < 0.005) Figure 3. High pH washes and additives like Arginine and Urea help reduce HCP levels in Protein-A eluates. Shown in the figure are contour plots representing (A) HCP levels in Protein-A eluates and (B) Recovery of the antibody in eluate. CHO cell harvest was loaded equally onto a 96-well plate containing Protein-A resin followed by washes with buffers at 3 pH values (pH 5.5, 7.0 and 9.0) containing a range of wash additives in the presence or absence of NaCl. For each wash additive, the contour plot panel was generated using 12 data points; 4 NaCl concentrations in combination with 3 excipient concentrations. (A) The deep blue color represents low levels of HCPs in the eluate while the deep red color represents very high amounts of HCPs levels still remaining in the Protein-A eluate. (B) The deep blue color represents high recoveries while the deep red color represents low recoveries. Figure 4. Neutralization to optimal pH after low pH hold for viral inactivation leads to increase in turbidity of the pool. A) Pool turbidity of samples as a function of pH. VI hold is at pH 3.5 B) Pool turbidity of samples shown in panel A after filtration with 0.2mm filter C) Absorbance at 410 of the samples shown in panels A and B Figure 5. Neutralization to optimal pH after low pH hold for viral inactivation leads to selective precipitation of HCPs. Shown above are the recovery of mAb and HCP levels in viral inactivated and neutralized bulk samples post filtration. Error bars represent standard deviation of the analytical results. Figure 6. CHO host cell proteins (HCP) levels present in the clarified harvest after acid precipitation. Acid precipitation was carried out using either Acetic acid or Citric acid as the titrant Figure 7. A) Comparison of the effect of Protein-A wash pH on HCP removal from various mAb harvest pools B) Comparison of the effect of neutralization pH on HCP removal from various mAb Protein-A eluate pools. Error bars represent standard deviation of the analytical results.

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Table I. Iso electric points of various class of molecules commonly found in CHO cell harvests and Protein-A elution pools (Aboulaich et al., 2014, Levy et al., 2014, Gottschalk 2009)

Molecule Class pI Range

HCPs 2 – 11

DNA 2 – 3

Viruses 4 – 7.5

Protein-A 4.8 – 5.2

Endotoxins 1 – 4

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Table IIA. Conditions employed in various purification trains tested

Step Train 1 Train 2 Train 3 Train 4 Train 5

Harvest Treatment Control Low pH Control Control Low pH

Protein A Chromatography

Control Control Enhanced Washes

Enhanced Washes

Enhanced Washes

Neutralization to Optimal pH

No No No Yes Yes

Table IIB Recovery and purity levels of the final mAb pool obtained by purification using various trains shown in panel A

Train 1 Train 2 Train 3 Train 4 Train 5

Recovery (%) > 95% > 90% > 95% > 95% > 90%

HCP (ppm) 7100 - 25500 940 - 2400 180 - 275 10 - 33 3 - 12

DNA (ppb) 10 - 26 7 - 18 < 5 < 1 < 1

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Table III. Chemical characteristics of various mAbs used in purification evaluation

Molecule Class pI Range Hydrophobicity§

mAb 1 IgG4 6.5 – 7.0 -70.0

mAb 2 IgG4 6.0 – 7.0 -56.8

mAb 3 IgG1 8.0 – 8.5 -26.4

mAb4 IgG1 8.0 – 8.5 -41.4

. §

3D structures of the Fab

regions were built using homology modeling tool SWISS-Model (Arnold et al. 2006)

and hydrophobicity scores of the CDR loops were calculated using Kyte-Doolittle hydrophobicity score (Kyte and Doolittle. 1982) as shown in the last column. According to the surface models, mAb3 is most hydrophobic while mAb1 is the least hydrophobic molecule.

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Table IV. Recovery and impurity clearance levels in various mAb pools after purification using Train 1 (Control) or Train 4 (Enhanced Protein-A washes) described in Table IIA

Load Control Purification Train Optimized Purification Train

Molecule HCP (ppm)

DNA (ppb)

Recovery (%)

HCP (ppm)

DNA (ppb)

Monomer (%)

Recovery (%)

HCP (ppm)

DNA (ppb)

Monomer (%)

mAb1 5.8E+05 7.7E+05 > 95% 9851 18 > 98% > 95% 13 < 1 > 98 %

mAb2 6.8E+05 5.0E+05 > 95% 17486 2417 > 94% > 95% 146 < 5 > 94 %

mAb3 1.7E+06 3.1E+05 > 95% 7085 834 > 98% > 90% 68 < 1 > 98%

mAb4 3.6E+05 1.5E+05 > 95% 1362 1054 > 99% > 95% 74 < 1 > 99%

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Figure 1

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Figure 2

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Figure 3a

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Figure 3b

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Figure 4

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Figure 5

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Figure 6

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Figure 7