This presentation looks at the different technologies available for detection of particles generated during the drug development lifecycle and their control using a formulation approach for particles generated as a result of agitation and freeze/thaw, events commonly observed during sample shipment and temperature excursions.

1. PARTICLES IN THE BIOTECH
PRODUCT LIFE CYCLE: ANALYSIS,
IDENTIFICATION AND CONTROL
Dr Tara Sanderson, Formulation Services Manager, SGS M-Scan

2. 2
KEY MESSAGES
 Why is it important to characterise and control particles in
the product?
 What different types of particles are often seen in the
product?
 Summary of mechanisms of proteinaceous particle
generation
 Overview of instrumentation useful for particle analysis
 Higher risk areas of particle generation in a drug
development program and routes of control
 Case study: Reformulation of a mAb showing significant
aggregation following shipment and temperature
excursions – useful HTS techniques to incorporate

3. 3
WHY DO WE NEED TO CONTROL PARTICLE
LEVELS?
 Potential to cause immunogenic responses
 Regulators require demonstrable limitation, control and
identification of product-related impurities
 Can impact product stability and shelf life

4. 4
WHAT IS THE IMPACT IF PARTICLE
GENERATION IS NOT CONTROLLED?
 Decreased shelf life and / or alternative storage has an
overall impact on cost and profitability of the drug product
 Regulators will require further characterisation and
evidence of clearance
 If aggregation is significant, process changes or
reformulation may be required - Time and cost
implications
 Following reformulation, comparability studies are required to
determine impact on continued use of reference standard and
suitability of method validations
 Significant time and cost impacts if method validations need
repeating or new Ref Std required
 Additional batches / new stability studies required

5. 5
TYPES OF PARTICLES
 There are various types of particles that may be present in
biotech products
 Non-Proteinaceous:
 Fibres: e.g. container closure shards, shedding from filters
 Particulates that shed from packaging: glass / plastics
Delamination: Plastic: Rubber:
Silicone oil from syringes:

6. 6
TYPES OF PARTICLES
 Proteinacious aggregates: visible and subvisible
Particle Size Particle Nature
~>100µm Visible particles
~1-100µm Sub-visible particles
>10nm – 1µm Oligomers

7. 7
COMPARISON OF DP PROTEINACEOUS VS
NON-PROTEINACEOUS PARTICLES
 Silicone oil particles from a syringe  Protein aggregation in DP vial

8. 8
Fragments Monomer Oligomers Subvisible Particles Visible Particles
SEC / SEC/MALS
SV-AUC
LO / MFI
NATIVE-PAGE
DLS / Nanoparticle Tracking
Analysis (Nanosight)
AF4
Visual Appearance
Resonant Mass Measurement
ANALYSIS OF PARTICLES
1mn 10mn 100nm 1µm 10µm 50µm >100µm

9. 9
 Protein / protein interactions: electrostatic interactions /
hydrophobic interactions / covalent bonding from free thiols
or exposed internal thiols
 Air / liquid interface / container interactions: partial
unfolding of the molecule
 Protein / contaminant interactions: critical nucleus –
catalyst for aggregation formation
IN MOST CASES AGGREGATION EVENTS OCCUR AS A RESULT OF
PARTIAL CONFORMATIONAL CHANGES
MECHANISMS BEHIND PARTICLE FORMATION?

10. 10
• Control through
Sequence design:
Technologies
available for
evaluation of
aggregation
propensity
• Free thiols
Sequence • Low pH hold
• Filtration /
column selection
• Include in-
process
aggregate
analysis
Expression
and
Purification
• Inadequate
formulation design:
Ensure
aggregation
assessed upon
agitation and F/T
Formulation
• Include continued
sub-visible particle
testing as part of
characterisation &
comparability studies
• Reformulate
Characterisation
• Agitation of
liquids
• Ensure shipment
studies and
excursions
studies
completed:
alternative
condition
• Reformulate
Shipments
• Thawing may
show particles –
ensure before
and after tests
performed
• Filter before fill
• Reformulate
Drug Product Fill
• Route of
administration:
Assess with
in-use studies
• Reformulate
Release
• Measure particle
trends
• Characterise any
particles generated
• Reformulate
Stability Studies
POTENTIAL ROUTES FOR AGGREGATION &
CONTROL

11. 11
CONTROL THROUGH FORMULATION –
CASE STUDY
Case Study: IgG1, pI 9.6, ~150 kDa, formulated in 20mM PO4, 125mM NaCl, pH.7
 IgG1 candidate was found to have higher than specification aggregation upon
shipment and F/T
 Challenges: Time and material constraints
 Aim: To reformulate to control aggregation during shipment and potential
temperature excursions
Formulation Design Strategy:
 Employ preformulation characterisation on control and agitated material to
determine degradation pathway and choose required methods for screening
approach
 Employ pH screen / followed by excipient screen using agitation and F/T
degradation to define the optimum formulation
Sample Treatment
 To mimic problem: Samples were degraded using conditions equivalent to the worst
case shipment and temperature excursions that could be observed for the product-
specific shipment route:
 24h agitation at ambient / 3 x cycles in thermal cycling unit from -20°C to 40°C.
 Degraded protein compared to control protein

12. 12
PREFORMULATION CHARACTERISATION
Analysis Control Degraded
Primary
structure:
NR Peptide
mapping-MS
for SS-
bridges
No scrambling
observed,
expected IgG1 SS-
bridge pattern
SS-bridge scrambling
observed
Charge
profile: icIEF
pI 9.3-9.6, 6
isoforms
pI 9.3-9.6, 6 isoforms
Equivalent profile to native
Secondary
structure:
FTIR
α-helix: 0%
β-sheet: 42%
α-helix: 0%
β-sheet: 43%
Equivalent profile
to control
Overall
tertiary
structure:
Near-UV CD
Equivalent profile
to degraded
Equivalent profile to
control, but some
differences observed
~ 280nm

13. 13
PREFORMULATION CHARACTERISATION
 Conformational stability: Intrinsic Fluorescence: 9-50µl, 96 well plate format
35
30
25
20
15
10
5
0
Intensity/10
3
counts
500450400350300250
Wavelength / nm
Optim 2
-5000
0
5000
10000
15000
20000
25000
30000
35000
40000
320 370 420
Fluorescenceintensity(au)
Wavelength (nm)
untreated
treated
Clariostar
BCM, Barycentric Mean

14. 14
Oligomers
Analysis Control Degraded Material
consumption
Visual
appearance
Clear, colourless Opalescent,
colourless
0.5mL
SE-UPLC Monomer: 98.7%
Aggregate: 1.2%
Fragment: 0.2%
Monomer: 95.1%
Aggregate: 1.5%
Fragment: 3.4%
5 µg
96 well plate format
SV-AUC Monomer: 82.2%
Dimer: 6.5%
Trimer: 5.8%
Pentamer: 2.1%
Hexamer: 3.4%
Monomer: 80.1%
Dimer: 7.6%
Trimer: 5.2%
Pentamer: 3.3%
Hexamer: 3.8%
40 µL
1mg/mL at 400µL
PREFORMULATION CHARACTERISATION:
AGGREGATION
AU
0.000
0.001
0.002
0.003
0.004
0.005
0.006
0.007
0.008
0.009
0.010
0.011
0.012
Minutes
4.20 4.40 4.60 4.80 5.00 5.20 5.40 5.60 5.80 6.00 6.20 6.40 6.60 6.80 7.00 7.20 7.40 7.60 7.80 8.00 8.20 8.40 8.60 8.80 9.00 9.20 9.40 9.60 9.80 10.00 10.20 10.40 10.60
Aggregates
Fragments
280 nm Monomer

15. 15
Analysis Control Degraded Material
consumption
DLS
Peak 1
Peak 2
Mean Radius (nm): 5.5
Mean MW: 182kDa
% Intensity: 100%
ND
Mean Radius (nm): 2.7
Mean MW: 34kDa
% Intensity: 34.7%
Mean Radius (nm): 34.4
Mean MW: 13,248kDa
% Intensity: 65.3%
20µl
384 well plate format
PREFORMULATION CHARACTERISATION
Control Aggregated
Control Aggregated

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PREFORMULATION CHARACTERISATION
≥2µm ≥5µm ≥10µm ≥25µm ≥50µm ≥100µm
LO Untreated 1730 515 110 15 0 0
MFI Untreated 12378 1486 187 31 0 0
LO Treated 27525 25080 19565 5340 635 10
MFI Treated 61224 61661 30396 3042 363 25
0
10000
20000
30000
40000
50000
60000
70000
NumberofParticlespermL
Particle Size (µm)
LO Untreated
MFI Untreated
LO Treated
MFI Treated
6000 / container 600 / containerUSP<788>

17. 17
CONCLUSIONS FROM THE PREFORMULATION
CHARACTERISATION
 Conclusions from the preformulation characterisation:
 Aggregation – irreversible SS-bridge scrambling occuring
but no apparent charge based changes (deamidation /
oxidation)
 No significant changes to 2°, minimal 3° structure or
conformational structure changes detected
 Significant changes in particle numbers, with the majority
observed higher than 2µm
 Screening Tools:
SE-UPLC & DLS
 In addition, for lead candidates: Particle counts, DSC,
Intrinsic fluorescence

18. 18
PH SCREEN
Buffers salts and excipients selected based on the
the et the route of administration and degradation profile
 pH screen: from pH 3.5 to 7.5
 Buffer ions containing 125mM NaCl: citrate, acetate,
glutamate, succinate, histidine (25mM)
 Samples agitated and treated to 3 x F/T cycles to choose
optimum pH and buffer salt.
 SE-UPLC & DLS utilised: total material consumed: 160ul
(1.6mg) / total preparation & screen time: 48h
 Optimal pH and buffer ion: 25mM succinate, pH 6.5
containing 125mM NaCl
 Excipient screen: excipients selected for conformational
stability & surfactants to reduce surface charge interaction

19. 19
EXCIPIENT SCREEN
From pH Screen: 25mM succinate, 125mM NaCl, pH6.5
Design Factors for DOE:
 2 % Trehalose
 His, Pro, Glu, Arg, Gly: 0 – 67 mM
 Tween 20, Poloxamer 188: 0.01% to 0.1%
 44 combinations
 Screened using SE-UPLC: 5µg / degraded sample,15h
analysis time
 DLS with heat ramp from 20-60°C: 20 µl / undegraded
sample, 3h analysis time

20. 20
RESULTS FROM EXCIPIENT SCREEN
SEC
DLS (60°C)

21. 21
LEAD CANDIDATE SELECTION AND ANALYSIS
DOE Lead candidates selection:
 R25: 67mM Gly, 67mM Arg, 0.01% Tween 20, 0.05%
Poloxamer 188
 R25b: 67mM Gly, 67mM Arg, 0.06% Tween 20
 R30: 67mM Pro, 22mM Gln, 0.1% Poloxamer 188
 R38: 67mM Pro, 22mM Gln, 67mM Gly, 0.1% Tween 20,
0.1% Pol188
Predictive analysis using undegraded material by intrinsic
fluorescence and DSC for thermal and conformational stability
 Particle counts for >2 µm particles
 Temperature Ramps: 20°C – 100°C, domain Tm’s and Tm
onset and Tagg compared

22. 22
Tm2 Fab
Tm1 Fc, CH2
Tm3 Fc, CH3
DSC Thermograms
LEAD CANDIDATE SELECTION

23. 23
LEAD CANDIDATE SELECTION
(TM ONSET DATA )
Optimal candidates from DSC
Ranking:
1: R25
2: R25b
3: R38
4: R30

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LEAD CANDIDATE SELECTION:
INTRINSIC FLUORESCENCE & SLS: OPTIM 2 WITH HEAT RAMP
FROM 20-95°C
Tm1
Tm2
Tagg 266nm
Tagg 473nm

25. 25
LEAD CANDIDATE SELECTION:
PARTICLE COUNT RESULTS

26. 26
Ranking from Conformational Analyses:
 1 R25: 67mM Gly, 67mM Arg, 0.01% Tween 20, 0.05% Poloxamer 188
 2 R25b: 67mM Gly, 67mM Arg, 0.06% Tween 20
 3 R38: 67mM Pro, 22mM Gln, 67mM Gly, 0.1% Tween 20, 0.1% Poloxamer 188
 4 R30: 67mM Pro, 22mM Gln, 0.1% Poloxamer 188
Ranking from Particle Counts:
 1 R25: 67mM Gly, 67mM Arg, 0.01% Tween 20, 0.05% Poloxamer 188
 2 R25b: 67mM Gly, 67mM Arg, 0.06% Tween 20
 3 R38: 67mM Pro, 22mM Gln, 67mM Gly, 0.1% Tween 20, 0.1% Poloxamer 188
 4 R30: 67mM Pro, 22mM Gln, 0.1% Poloxamer 18
Final Selection: 25mM Succinate, 125mM NaCl, 67mM Gly, 67mM
Arg, 0.01% Tween 20, 0.05% Poloxamer 188, pH 6.5
FINAL SELECTION

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SUMMARY
 Traditional screening tools, such as SEC & DSC are useful
methods to employ in a formulation screen, but it is also
critical to ensure larger aggregates are also investigated in
combination with these.
 It is also critical to use methods that allow analysis of the
full range of aggregates and subvisible particles otherwise
a significant degradation pathway may not be properly
evaluated.
 Ever increasing constraints on material availability and
shorter time to decision point means that more sensitive /
high throughput instrumentation is required for effective
early screening.

28. 28
ACKNOWLEDGEMENTS
SGS M-Scan Formulation and Biophysical team:
 Aoife Bolger
 Marisa Barnard
 Inigo Rodriguez-Mendieta
 Zeb Younes
 David Miles
 Stella Chotou
 Jon Phillips
 Fabio Rossi

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Life Science Services Dr. Tara Sanderson
Formulation Services Manager
SGS M-Scan Ldt Phone: +44 (0)118 989 6940
Berlin & Taunusstein
E-mail : tara.sanderson.@sgs.com
Web : www.sgs.com/lifescience
THANK YOU FOR YOUR ATTENTION