integrated utilization of high-throughput bioreactors & high-throughput analytics for rapid...

1

High-throughput Cell Culture Process Development

Integrated utilization of high-throughput bioreactors and high-throughput analytics for rapid and robust cell culture process development.

Shahid Rameez, Srivatsan Gopalakrishnan, Carl Zhang, Jaspreet S. Notey, Christopher Miller, Derek Ryan, Nathan Oien, James G. Smedley, Sigma S. Mostafa and Abhinav A. Shukla

KBI Biopharma Inc., 2 Triangle Drive, Research Triangle Park, NC 27709.

Executive Summary

There is a strong impetus towards rapidly advancing an increasing number of novel biotherapeutics to clinical trials. However, development of cell culture processes is labor intensive and time consuming. KBI focuses on a high throughput process development (HTPD) approach using high-throughput miniaturized bioreactors and high throughput analytics that generate growth, productivity and product quality data that match those seen with classical systems. This approach enables a significant reduction in the cell culture process development timeline and costs for investigational biopharmaceuticals to reach the clinic. We integrated three technologies; (1) ambrTM miniaturized disposable bioreactors controlled by an automated workstation for cell culture experiments. (2) ForteBio's Octet® for rapid and accurate analysis of antibody concentrations that utilizes biolayer interferometry based biosensors for antibody quantification. (3) The LabChip® separation system that utilizes reusable micro-fluidic chips for rapidly screening N-glycan, protein charge and molecular weight profiles. This HTPD approach has demonstrated the ability to match results from classical systems. The integrated utilization of high-throughput bioreactors and high-throughput analytics can be implemented during various stages of cell culture process development for a range of biologic therapeutics. This includes non mAb proteins that require more detailed process development as opposed to implementation of a platform approach and biosimilars that need to match a pre-determined product quality profile. In addition, this approach significantly increases knowledge of the process and the influence of upstream process parameters on product quality and process performance and facilitates more robust scale-up into manufacturing scales for any product class.

With the increase in prominence of

biopharmaceuticals in the clinic (> 900)

and a steady increase in approvals (> $ 100

billion in annual sales), there is a strong

impetus is put on strategies to accelerate

clinical entry.1 In the current regulatory

landscape it often takes ten years and

billions of dollars to bring a drug candidate

from development to the shelves.2 While it

is typically desired to keep CMC (chemistry,

manufacturing and controls) activities off

the critical path for drug development, this

situation cannot be avoided prior to clinical

entry. Hence, there is increased interest in

pursuing methodologies that can shorten

the window for process development and

manufacturing. Some of these have arisen in

the form of platform processes, high

throughput methods and single-use

manufacturing technologies.3-6 At KBI, we

2


have pursued all of these methodologies.

This white paper focuses on increasing

experimental throughput in process

development utilizing high throughput

methodologies.

Platform approaches have been successfully

adapted for the rapid development of

certain classes of therapeutics such as

monoclonal antibodies (mAbs). However,

even for this well-established product class,

what is gained in terms of speed is often

lacking in terms of process knowledge and

the influence of various process parameters

on process and product quality outcomes.

Biosimilar processes present an even

greater challenge. In this situation, a

comparable bioanalytical profile is critical to

achieve and is significantly influenced by

cell culture process parameters. Thus the

challenge in process development is finding

the right process conditions to produce a

molecule with matching product quality

attributes to the innovator.

With conventional laboratory scale

bioreactors and shake flasks being the

dominant forms of experimentation, the cell

culture development stage becomes a

resource and time intensive step.

Mammalian cell culture processes typically

have the longest experimental duration with

inoculum seed train and production culture

stretching between 4-6 weeks. In order to

test critical process parameters such as pH,

dissolved oxygen and agitation, bioreactors

must be used since shake flasks lack the

necessary control capabilities. During

optimization of a typical cell culture process,

at least 3-4 rounds of 10-12 bioreactor runs

need to be performed. This combination of

experimental duration and the extensive

resources required to run multiple reactors

in parallel makes the cell culture process

development stage a key bottleneck step

during process development. More

importantly, to develop a robust cell culture

process that ensures batch to batch product

quality consistency, Design of Experiment

(DOE) based studies have to be

implemented during cell culture process

development to reveal the effect of cell

culture changes on homogeneity, purity and

post translational modifications. These

studies provide for a comprehensive process

understanding which in turn enables the

production of more consistent batches.

However employing this approach produces

a large number of bioreactor runs and a

large number of samples. This in turn can

exceed the resources and capacity of cell

culture and analytical laboratories which

primarily depend on conventional small

scale glass bioreactors (1-15L in size) and

HPLC and CE based separations to monitor

protein quantification and product quality.

As a result there is a compelling demand for

a HTPD platform which enables key process

3


decisions during the early process

development phase.

In the paper above, we have demonstrated7

the ability to employ the ambr™ system to

make key process decisions during the

development of a biopharmaceutical

manufacturing process. The capability to

fine-tune process controls with 24-48

single-use miniature bioreactor vessels

provides for a platform to employ fractional

factorial and minimum-run designs to

enable identification of key process

parameters and interactions of those

process parameters. Moreover, the

reproducibility and scalability of the system

enable its use for high throughput

experiments for cell culture process

development during the first in human

(FIH) phase of biopharmaceutical drug

development, offering a significant

possibility of decreasing the development

timeframe prior to clinical entry (Figure 1).

4


Figure 1: Clinical and process development/manufacturing activities during biopharmaceutical development and role of ambr™ in accelerating product development during the FIH phase of the biopharmaceutical development lifecycle.

In addition to the ambr™ system we have

integrated two high throughput analytical

technologies to create a high throughput

process development (HTPD) platform

where the effect of media, feeds, feeding

frequency and process parameters on

various product quality attributes are

studied right from the early phases of cell

culture process development. The two high

throughput analytical technologies are

ForteBio's Octet® for rapid and accurate

analysis of antibody concentrations and

LabChip® separation system that utilizes

reusable micro-fluidic chips for rapidly

screening molecular weight, N-glycan and

protein charge profiles. Octet utilizes

biolayer interferometry (BLI) based

biosensors for antibody quantification.

These biosensors are coated with a

biocompatible matrix to analyze specific

5


biomolecular interactions. Both these

analytical technologies provide particular

value in applications where existing

methods such as HPLC, ELISA, SDS-PAGE

and Capillary Electrophoresis, have

limitations in throughput, performance,

workflow, and ease of use. Figure 2 shows a

schematic for the HTPD approach which

utilizes high throughput microbioreactors

and high throughput analytics to accelerate

product development. HTPD approach can

be utilized all the way starting from

selection of a clone during the cell line

development. Due to limitation of time and

resources relatively few top clones (top 1 - 4

clones) are evaluated in conventional

bioreactors which decreases the chance of

identifying a high producing clone with

desired quality attributes. HTPD overcomes

this limitation of time and resources while

offering capability of evaluating a larger

number of clones (top 24 – 48 clones) in

parallel under representative stirred tank

bioreactor conditions. In particular, this

broader screening benefits biosimilar

programs in which the desire is to identify a

clone that is capable of producing specific

product quality attributes. In addition,

during the cell culture process development

phase, HTPD enables the investigation of

factors like pH, temperature, dissolved

oxygen, nutrients in media and feeds,

glucose, ammonia, salt and other

metabolites that have shown to affect the

productivity and product quality of proteins.

The ambr™ system when operated under

fed-batch conditions with appropriate pH,

DO and feed controls can successfully

simulate bioreactor culture conditions with

highly reproducible results between the

replicates. Cell growth, process capabilities,

and product titer and product quality

profiles are comparable to classical

bioreactors of various scales, 3, 15 and 200L

and found to be within 10-15% of mean

values. The 24-48 single use vessels provide

flexibility to run larger experimental designs

in parallel to evaluate feeding regimes,

process operating limits and interactions

between various operating parameters.

Overall, the reproducibility of key

observations and scalability of key results

with the system has been demonstrated to

be adequate to utilize this system for cell

culture process development.7

A typical optimization of a cell culture

process, which requires at least 3-4 rounds

of 10-12 bioreactor runs, it takes 3-4

months. This is due to duration of 2-3 weeks

for the production bioreactor step with

additional 1-2 weeks on the seed cultures.

The same optimization can be achieved in

ambrTM system (48 bioreactors) in a month

with experiments run in parallel. In

addition, the classical reactors require

cleaning, set up and autoclaving prior to

6


Figure 2: Utilization of high throughput cell culture development and high throughput analytics (HTPD approach) in accelerating product development during the first in human (FIH) phase of the biopharmaceutical development lifecycle.

Figure 3: Comparison of time courses for viable cell growth for recombinant CHO cell lines in ambr™ vessel and other scales classical bioreactors; 3L and/or 15L glass bioreactors and 200L single-use bioreactor for (A) mAb and (B) non-mAb. The experimental data for ambr™ shows an average of 3 and 2 vessels in figures A and B respectively.

their use in studies. The single use pre

calibrated bioreactor vessels in the ambrTM

system overcome this limitation and provide

significantly faster turnaround times while

significantly reducing time, cost and labor.

7


Table 1: Cell culture performance comparison between bioreactor systems (ambrTM, 3 and/or 15L Glass bioreactors and 200L single-use bioreactor) for Viability at harvest (%), Titer (Normalized), Cell-maximum growth rate (1/d) and Cell-specific productivity (pg/cell/d) for a mAb and a non-mAb.

Bioreactor System

Viability at Harvest

(%)

Titer (Normalized to 200L

titer values)

Cell Maximum Growth Rateh

(1/d)

Cell-specific Productivity (pg/cell/d)

mAb ambra 90.27 ± 0.14 0.96 0.37 16.20 3-Lb 98.70 1.06 0.37 10.60 15-Lc 91.38 ± 2.19 0.88 0.34 10.80

200-Ld 90.20 1.00 0.34 11.70 non-mAb

ambre 81.20 0.99 0.46 15-Lf 61.40 0.94 0.51

200-Lg 84.20 1.00 0.47 a: n = 3, b: n = 1, c: n = 4, d: n = 1, e: n = 2, f: n = 1, g: n = 1, h: Measured from days 0-8 for mAb and from days 0-7 for non-mAb .

Figure 4: Comparison of two mAbs (X and Y) concentrations in eight 3L glass bioreactors using OctetTM and Protein A HPLC methods. The results between the two methods are comparable. For most of the samples the variability between two methods was less than 5%. Figure 3A shows the experimental data for Octet™ as an average of 3 measurements. Reproducible results are obtained between replicates in Octet™. The titers are within ±1% of each other. In addition, the % CV was less than 3%.

We present data from two case studies

demonstrating HTPD approach employed

during cell culture process development for

a Biosimilar. Case study I aimed at

evaluating 8 different feeds for CHO cell

line producing a Biosimilar. This was

followed by case study II which was a DOE

study evaluating the effect of process pH

and four different feeding frequencies (FDS

A, B, C and D) for the selected feed on the

Biosimilar. We monitored the productivity

and product quality attributes (charge and

N-glycan) and compared them to the

innovator drug product.

8


Figure 5: Multiple overlay electropherogram for a mAb C showing different charge species (left figure). Comparison of mAb C charge variants using LabChipTM and conventional cation exchange chromatography (CEX) method (right figure). Comparable results were obtained between two methods for different charge variants. The variability between two methods was less than 5%.

Figure 6: Multiple overlay electropherogram for a mAb C showing different charge species (left figure). Comparison of mAb C charge variants using LabChipTM and conventional cation exchange chromatography (CEX) method (right figure). Comparable results were obtained between two methods for different charge variants. The variability between two methods was less than 5%.

As an example, Figure 7 A and B show one

specific glycan structure (G0F) from these

case studies, a critical quality attribute in

this Biosimilar, and show the change it

undergoes under various tested process

conditions. Based on the results, the

conditions which do not allow the G0F to

remains within the value ± variability of the

originator molecule were not carried

forward. Thus feeds 3, 7 and 8 (Figure 7A)

were not evaluated further. Moreover, the

selected feed showed strong interaction with

respect to process pH to control the critical

quality attribute in this Biosimilar (Figure

7B). Both these studies helped assess

product quality metrics from cell culture

process development and identify right

conditions to produce the molecule with

matching product quality attributes to the

innovator.

9


Figure 7: Percentage (normalized to innovator value) of specific glycan structure (G0F) in case studies I and II, a critical quality attribute in the Biosimilar, and change it undergoes under various tested process conditions. Based on the results, the conditions which do not allow the G0F to remains within the value ± variability (blue region) of the originator molecule were not carried forward.

Conclusions

The multi-stage nature of process

development and the long duration of

mammalian cell culture experiments makes

it time and resource intensive. HTPD

approach offers realistic possibility of

decreasing the timeline for process

development experimentation. This in turn

decreases the timeframe to manufacturing

clinical material prior to clinical entry. In

addition, material needs and other

resources are minimized and thus a larger

number of drug candidates can be advanced

into the clinic faster to address the unmet

clinical needs.

References

1. Walsh, G. Biopharmaceutical

benchmarks 2010. Nature Biotechnology

2010, 28, (9), 917-924.

2. Gottschalk, U.; Brorson, K.; Shukla, A. A.

The need for innovation in

biomanufacturing. Nature Biotechnology

2012, 30, (6), 489-492.

3. Shukla, A. A.; Thömmes, J. Recent

advances in large-scale production of

monoclonal antibodies and related proteins.

Trends in Biotechnology 2010, 28, (5), 253-

261.

4. Shukla, A. A.; Gottschalk, U. Single-use

disposable technologies for

biopharmaceutical manufacturing. Trends

in Biotechnology 2013, 31, (3), 147-154.

5. Rege, K.; Pepsin, M.; Falcon, B.; Steele,

L.; Heng, M. High-throughput process

development for recombinant protein

purification. Biotechnology and

Bioengineering 2006, 93, (4), 618-630.

6. Chen, A.; Chitta, R.; Chang, D.;

Amanullah, A. Twenty-four well plate

miniature bioreactor system as a scale-down

10


model for cell culture process development.

Biotechnology and Bioengineering 2009,

102, (1), 148-160.

7. Rameez, S.; Mostafa, S. S.; Miller, C.;

Shukla, A. A. High-throughput miniaturized

bioreactors for cell culture process

development: Reproducibility, scalability,

and control. Biotechnology Progress 2014,

(30): 718-727.

Acknowledgements

We thank Joe McMahon, CEO of KBI Biopharma Inc., for his support for this work. Members

of the process development, analytical development and formulation sciences teams at KBI

Biopharma Inc. are thanked for providing support during the pursuit of process development

programs.

integrated utilization of high-throughput bioreactors & high-throughput analytics for rapid...

Health & Medicine