Application Note

Highly automated protein formulation development:a case study
Introduction and backgroundenhanced visual inspection with visible particle
counting — all on a single platform. The powerful
and intuitive software, Lab Execution and Analysis(LEA), controls the freeslate system and integrates
third-party analytical and processing equipment.
LEA collects all processing information and analytical results in a shared database. The database links
sample composition information, stress conditions
and analytical results. A wide range of Unchained
Labs' analytical systems and third-party analytics,
including DLS, UV/Vis and HPLC can be integrated
into the freeslate system.

Therapeutic proteins can be inherently prone todegradation and instability, and they often posechallenges to drug developers. These developers
perform screening and stability studies to identify
suitable formuations from preformulation all theway through the formulation development process.
The number of formulations that can be screened
for each project is constrained by short timelines
and the availability of material and resources.
Scientists that automate formulation screening andstability studies significantly increase their productivity and improve throughput without additional
resources.

A fully-integrated automation
workspace

Unchained Labs developed the freeslate system
configured for biologics formulation to automate
the entire formulation development process: liquidand solid dispensing, preparation and stressingof samples, high-throughput pH, viscometry andDesigned with collaborators from R&D divisions ofleading pharmaceutical and biotechnology companies, the freeslate system automates many workflows common to formulation development andanalytical testing labs. Robots and instruments areconnected and configured for each customer workflow. Every freeslate system removes manual steps
to speed up lab work and liberate scientists to focus
on more valuable tasks (Figure 1). One robot prepares the formulations and measures pH, viscosity,visible particles, color and turbidity. The other robot
performs sample processing, stressing and analysis(DLS and UV/Vis, etc.). The freeslate system handles
a variety of formats from 96-well microplates to20 mL serum vials. Powerful LEA software enables
instrument control, data collection, data management and reporting. By combining the aforementioned activities, the freeslate system supports theentire formulation development process from preformulation to late stage formulation for virtually all
proteins, peptides and other biotechnology products.

Figure 1: The freeslate system configured for biologics formulation. The robot on the right prepares formulations and measures
pH, viscosity and visual inspection. The left robot integrates with
the Wyatt DynaPro II dynamic light scattering (DLS) instrument and Molecular Devices SpectraMax microplate reader. A
low-bioburden HEPA enclosure encapsulates the system.

1

HIGHLY AUTOMATED PROTEIN FORMULATION DEVELOPMENT: A CASE STUDY

The freeslate system configured for biologics formulation workflow
Prepare formulations in 2 mL vialst0(unstressed)

Agitation
stressingHeatstressing

Freeze-thawstressing

Automated enhanced
visual inspection

Automated enhanced
visual inspection

Automated enhanced
visual inspection

Automated enhanced
visual inspection

DLS

DLS

DLS

DLS

pH

SEC-HPLC

SEC-HPLC

SEC-HPLC

Viscosity

RP-HPLC

RP-HPLC

RP-HPLCUV/VisSEC-HPLC
RP-HPLC

Figure 2: A schematic flowchart summarizes the automated study. The freeslate system automatically prepared all formulations inserum vials, then t0 samples were analyzed by nine analytical techniques using this system. Automated enhanced visual inspection:
particles, color, turbidity. Three sets of vials were subjected to agitation, heat or freeze-thaw stressing on the freeslate system, andthen the samples were tested by six analytical methods.

Case study: formulation screening and stability studies can beautomated• Three sets of formulations were subjected tothree different stress conditions: agitation,
heating and freeze-thaw cycles. An additional
set of formulations was used for initial time point(t0) measurements. Initial time point (t) samples
were analyzed by both system analytics andthird-party analytics, which were directly integrated into the freeslate system via LEA software.

In this study, we applied a freeslate system tocomplete a formulation screening and stability
study.
To demonstrate the productivity improvements
made possible with the freeslate system, we
automated the buffer and excipient screen for a
protein, and the stressing and analysis of eachsample (Figure 2).

• Each formulation was made from sterile stock
solutions using automated liquid handling (airdisplacement and positive displacement pipetting) together with the cooled storage bay andvortexer deck elements of the freeslate system.

• Using bovine serum albumin (BSA) as a surrogate drug substance, a single scientist was able
to prepare and screen 48 formulations in 2 mLvials• After compounding, automated protocols aliquoted and diluted sample material from each
formulation into the appropriate vials and 96well plates to complete the t0 testing.

• 48 total formulations (Table 1) with BSA concentrations of 10 mg/mL were prepared using fivebuffer systems (with pH values from 4.5–7.0)
and four excipient combinations. All formulations
were prepared in 2 mL (2R) serum vials.

The freeslate system analytics were pH, viscosityand visible inspection (color, turbidity and visible
particle detection). Integrated third-party
analytics were Wyatt DynaPro™ for protein

2HIGHLY AUTOMATED PROTEIN FORMULATION DEVELOPMENT: A CASE STUDY

Form

BufferpH

Excipients

Form

1

Sorbitol, NaCl

29

Sorbitol, NaCl

2Arginine, NaCl

30

Arginine, NaCl

Aspartic acid, NaCl

31

Aspartic acid,Arginine, NaCl

32

Sorbitol, NaCl

33

Arginine, NaCl

34

Aspartic acid, NaCl

35

8Aspartic acid,Arginine, NaCl36Aspartic acid,Arginine, NaCl

9Sorbitol, NaCl *37

Sorbitol, NaCl

10Arginine, NaCl *38

Arginine, NaCl

Aspartic acid, NaCl
*

39

5.0

345

Sodiumcitrate

65.5

7

11

6.5

12

Aspartic acid,
Arginine, NaCl *13

Sorbitol, NaCl

14Arginine, NaCl

15

Sodiumphosphate

6.5

16Aspartic acid,
Arginine, NaCl

17

Sorbitol, NaCl

18

Arginine, NaCl
7.0

1920

Aspartic acid,
Arginine, NaCl

21

Sorbitol, NaCl

22

Arginine, NaCl
4.5

23
24
252728Aspartic acid, NaCl

Arginine, NaCl
5.0

Aspartic acid,Arginine, NaClSodium
phosphatecitrate

Sorbitol, NaCl
Arginine, NaCl
6.5

6.0

Aspartic acid, NaCl

Aspartic acid, NaCl

Sorbitol, NaCl

42

Arginine, NaCl
L-Histidine

6.5

Aspartic acid, NaCl

44

Aspartic acid,Arginine, NaCl

45

Sorbitol, NaCl

46

Arginine, NaCl
7.0

Aspartic acid, NaCl
Aspartic acid,
Arginine, NaCl

Table 1: Compositions of the 48 formulations prepared by thefreeslate system are summarized. Each formulation includes
sorbic acid (0.1%), except control formulations denoted withasterisks. BSA concentration is 10 mg/mL in each formulation.

Sorbitol, NaCl26Aspartic acid, NaCl

41

48

Aspartic acid,Arginine, NaCl

Sodiumacetate

6.0

Excipients

Aspartic acid,Arginine, NaCl

47

Aspartic acid, NaCl

pH40

43

Aspartic acid, NaCl

BufferAspartic acid, NaCl
Aspartic acid,Arginine, NaCl

3

HIGHLY AUTOMATED PROTEIN FORMULATION DEVELOPMENT: A CASE STUDY

aggregation, Molecular Devices SpectraMax®
for protein concentration (A280nm) and Agilent
1100 HPLC for reversed-phase (RP) and sizeexclusion chromatography (SEC). After t0 analysis,
each formulation was analyzed by all analytics,
except pH and A280nm. The freeslate systemgenerated agitation and heat stressed samples
on the robotic work space. All sample stressing
was automated by the freeslate system, except
freeze-thaw stressing. Analytical results wereautomatically linked to appropriate sample
composition and stress conditions via the LEA
software and stored in its database. Data
series were viewed and organized in LEA, andresults were then exported to Microsoft Excel for
generation of tables and plots.

observed compared to t0 samples after freezethaw and agitation stressing. Heat stressing led
to significant increases in the number of visible
particles for many formulations. Heat stressing
also induced color changes for formulations 2,4, 26 and 37–48 from ≤ BY7 (nearly colorless orcolorless) to BY5 or darker (noticeable brownyellow tint).
Modest increases in turbidity (Figure 6) weredetected in the samples after freeze-thaw andagitation stressing compared to their t0 values.
Heat stressing led to significant changes in theturbidity of the formulations, usually an increase of
100 NTUs or more.
The results of DLS measurements of all formulations and conditions are shown in Figure 3. At t0,the polydispersity percentage of formulated BSA
ranged from 20%–24%. For most formulations,
heat stressing was correlated with no change ordecreases in the polydispersity compared to the t0
samples. Agitation generally did not significantly
alter the polydispersity of samples, except in thecase of formulation 23, which showed a significant
increase in polydispersity.

Results from the automatedstudy
At t0, the freeslate system automatically
prepared samples and performed color, turbidity,
visible particle count, viscosity, pH, DLS, UVand HPLC. Initial turbidity measurements for all
formulations were between 5–13 nephelometricturbidity units (NTU), which corresponded toclear solutions by manual visual inspection.
Visible particles (particulates) counted by theautomated visual inspection station ranged from
0–4 in the vials at t0. The initial viscosities for
all formulations were consistently low (around1.0 cP), as expected for such protein solutions.
All formulations had less coloration than the
BY7 (brown-yellow 7) standard, except forformulations 1, 2 and 4, which were all equivalent
to BY7. Formulations containing sorbic acidhad interfering absorbance at 280 nm, so thistechnique was only used to measure control
formulations (9–12), which did not contain sorbic
acid. Additional t0 results are shown in Table 2.
Results from t0 and after stress exposure
are presented for DLS (Figure 3) and HPLC
(Figure 4).

Formulations with low pH values (4.5–5.0), suchas formulations 1–4 and 21–24 that were exposed
to freeze-thaw stressing had significant increases
in the polydispersity and the actual polydispersity
values were not determined
All formulations were analyzed by RP and SEC forpurity and colloidal stability, respectively, using anAgilent HPLC that was virtually integrated with thefreeslate system. Chromatograms for each formulation were compared to those of an unstressed
BSA reference standard in 50 mM sodium phosphate, pH 7.0. Results from both RP and SEC
HPLC indicate that the stability of the protein islargely unaffected by these stress conditions.
Placebo formulations with the same compositions,with BSA excluded were analyzed at t0 with all analytics except HPLC (SEC and RP), DLS and A280.
The results were nearly identical to those of therespective protein formulations (results not shown).

Figure 5 shows visible particle counts for all
formulations across stress conditions comparedto t0. Small increases in visible particles (~1) were4HIGHLY AUTOMATED PROTEIN FORMULATION DEVELOPMENT: A CASE STUDY

Automated
pH

Automatedturbidity (NTU)

Automatedparticulates

Automatedviscosity (Cp)

Automated
color

1

5.5

8

1

1.3

BY72

5.5

10

1

1.2

BY7

5.6

70

1.2

Colorless(<BY7)

4

5.5

70

1.2

BY75

5.9

80

1.3

6

5.9

73

1.2

7

6.1

80

1.2

8

5.9

80

1.2

9

6.5

82

1.3

7.0

10

6.5

721.27.6116.6

112

1.2

7.4

126.5

110

1.3

8.0

13

6.5

120

1.3

146.5

911.315

6.6

801.2

166.4

81

1.1

176.4

1301.2

18

6.5

70

1.2

19

6.6

70

1.5

20

6.4

70

1.1

21

4.8

90

1.4

22

4.8

90

1.3

23

5.0

70

1.2

24

4.8

71

1.2

25

5.1

80

1.2

Form

35Automated
A280

ND

Colorless(<BY7)ND

HIGHLY AUTOMATED PROTEIN FORMULATION DEVELOPMENT: A CASE STUDY

FormAutomated
pHAutomatedturbidity (NTU)Automatedparticulates

Automatedviscosity (Cp)

26

5.2

7

1

1.1

27

5.2

61

1.2

28

5.2

71

1.3

29

6.2

60

1.4

30

6.2

7

1

1.2

31

6.3

61

1.3

32

6.2

60

1.0

33

6.6

11

1

1.3

34

6.6

9

0

1.3

35

6.7

6

1

1.4

36

6.6

60

1.4

37

6.1

51

1.4

38

6.2

8

0

1.2

39

6.3

72

1.2

40

6.2

50

1.3

41

6.7

8

0

1.3

42

6.7

7

1

1.3

43

6.8

50

1.1

44

6.7

74

1.2

45

7.4

110

1.1

46

7.4

8

0

1.147

7.5711.1

48

7.3

611.3

Table 2: Summary of results from six analytics collected at t0. ND: not determined.

6Automatedcolor

Automated
A280

Colorless(<BY7)

ND

HIGHLY AUTOMATED PROTEIN FORMULATION DEVELOPMENT: A CASE STUDY

47T0FTAg

Heat

42% Polydispersity

3732*

*

* *27

*

222625242322

2120

19

18

1716

15

14

1312111098

76543212117

Formulation

Figure 3: A graph of the DLS results shows that stressing by heat (Heat), freeze-thaw (FT) and agitation (Ag) causedincreases in percent polydispersity. Increased polydispersity could indicate formation of particles. Formulations with pH
values around 5 had significant increases in polydispersity to the point where many samples were not measurable (highlighted by the asterisks*).

T0FTAgHeat

Main peak % area

10095

90

26

25

24

23

22

21

20

19

18

17

16

15

14

13

12

11

10

9

8

7

6

5

4

3

280

185

Formulation

Figure 4: A graph of the RP HPLC results shows that the BSA is highly pure in all formulations at t0 and that purity is maintained in all formulations throughout each stress condition.

7HIGHLY AUTOMATED PROTEIN FORMULATION DEVELOPMENT: A CASE STUDY

1816T0FTAgHeat14Particle count1210864262524232221201918

171615141312111098765432012

Formulation

Figure 5: A graph of the visible particle counts is shown. Particle counting was performed by Unchained Labs' visualinspection station. Heat stressing (Heat) led to marked increases in particles in most formulations. Freeze-thaw (FT) andagitation (Ag) caused modest increases in particle counts in most formulations.

180160T0FTAgHeat

140120NTU

100806040

Formulation

Figure 6: A graph of turbidity values shows that heat stressing (Heat) led to marked increases for most formulations.
Freeze-thaw (FT) and agitation (Ag) lead to only modest increases in turbidity for most formulations.

826

25

24

23

22

21

20

1918

1716

15

1413121110

98

7

6

54

3

20120

HIGHLY AUTOMATED PROTEIN FORMULATION DEVELOPMENT: A CASE STUDY

Attended time using
the freeslate system for48 formulations (h)Attended time using manualmethods for 48 formulations (h)Formulation preparation byliquid compounding*

0.5

2.5

Analytical sample preparation
for six methods*

0.5

2.0

Visual inspection

0.3

0.5

DLS

0.3

0.3

pH

0.3

2.4

Viscosity

0.3

12.0

UV/Vis0.1

0.1

SEC-HPLC*

0.8

0.8

RP-HPLC*

0.8

0.8

HPLC analysis and reporting

1.0

3.0

Lab notebook entries

1.5

5.5

Total attended time (h)

6.1

29.7

Process

Table 3: A chart of turbidity values shows that heat stressing (Heat) led to marked increases for most formulations. Freeze-thaw(FT) and agitation (Ag) lead to only modest increases in turbidity for most formulations. * Not including preparation of stock or mobile phase solutions.

Conclusion

stabilities of the sodium phosphate formulations,as indicated by the control formulations (no sorbicacid). Results from HPLC (RP and SEC) testing
indicated that BSA maintained a high purity andcolloidal stability, which suggests that the stability
indicators for each formulation may be due tocomponents of the formulation exclusive of theprotein. For this study, the results suggested
that the performance of each formulation wasindependent of the stability of BSA, and that thestability for each formulation may be due to thebuffer and excipients components.

We developed and performed an automatedprocedure for the preparation and analysis
of protein formulations suitable for a buffer
and excipient screen. This demonstrated the
productivity improvements that are possible
with the freeslate system configured for biologics
formulation. Automated procedures significantly
reduced the time scientists were working in thelab while efficiently providing highly informative
results. Data from visual inspection and DLS reveal
to the scientist strong relationships between buffer
systems and pHs to the overall performance of theformulation. Formulations with lower pH values(4.5–5.0) demonstrated lower stabilities comparedto those with higher pH values (5.5 to 7.0).

To complete this study, approximately 28 hours
of scientist time was required. A similar study
performed by current manual procedures would
require 110–170 hours of scientist time (Table 3).

Generally, excipient conditions with sorbitoland NaCl were correlated with less stable
formulations. Sorbic acid had little influence on theBy using the procedure automated by thefreeslate system, a 4X–6X reduction in scientist
time was achieved. Without the benefit of9HIGHLY AUTOMATED PROTEIN FORMULATION DEVELOPMENT: A CASE STUDY

automated execution of formulation compounding,analytical sample preparation analytics and data
aggregation, evaluating such a broad range offormulation and stress conditions would be asignificant commitment for a single scientist, oreven a team of experts. Additional benefits ofautomating include:scientists. Unchained Labs' proprietary automation
technologies enable a broad range of formulations to be screened with reduced time and labor
requirements. Analytical results were collected ina central database, allowing scientists to reachmeaningful conclusions quickly and confidently. Additionally, the use of automation provided consistency of sample handling while the automated datacollection and tracking features of LEA increased
confidence in data integrity and accelerated thetime from experimental completion to reporting.

• Robust automation enabled consistency and standardization of sample handling across all conditions• Sample tracking for all time points ensures dataintegrity• Raw data linked to appropriate samples and sample conditions in a user-friendly centralized database reducing interpretation time and effort

Approximately 28 hours of scientist time wasrequired to complete this study using thefreeslate system compared to 110-170 hours,
which would have been required with manual
procedures.

• Intuitive software allows scientists to rapidly review,
reprocess and report
This case study demonstrates that high-throughput automation offered with the freeslate system
improves efficiency and productivity of formulation

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