Joseph A Tweed

The delivery of automated sample preparation and
extraction solutions for antibody-drug conjugate
(ADC) biospecimens using robotic liquid handling
Joseph A Tweed
Pfizer Proprietary
Overview
•  General review of Regulated Bioanalysis
•  General review of ADCs and ADC
payload bioanalysis
•  Assay considerations:
•  Liquid Chromatography
•  Mass Spectrometry
•  Sample Preparation
•  Logistics and Automation
•  Conclusions
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Regulated Bioanalysis
• 
An analytical discipline that typically provides quantitative data in support of
pharmacokinetic and toxicokinetic studies.
•  Compliance and Quality:
•  Scrutiny via regulatory bodies (FDA, EMA, TPD, MHRA).
•  Guidance documents applicable for small molecules and
biotherapeutic validations and biospecimen sample analysis
(FDA, EMA).
•  Subject to internal and external audits via internal quality
assurance (QA) organizations and regulatory agencies (FDA).
•  Robust and reliable bioanalytical methods are developed and
validated for use over the course of the study.
•  Timeliness:
•  Must meet the demands of project team to meet portfolio
objectives.
•  Concentration data, toxicokinetic findings, dose-escalation,
etc.
•  Tools :
•  Many different types of analytical methods, instrumentation,
computers, software, processes and procedures.
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Portfolio Support Workflow
• 
A typical regulated bioanalysis workflow involves:
•  Biospecimen sample collection, sample management and logistics
(chain-of-custody)
•  Sample preparation and extraction
•  Data acquisition, analysis and reporting
Our Laboratory:
•  PK/TK support
•  Small molecules
•  Biomarkers
•  ADC payloads
•  LC-MS/MS
•  Automation
•  Tomtec
•  Hamilton STAR
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Mechanism of Action of a Typical ADC
Payload Release
Cleavable ADC: Enzyme cleaves
linker to release free payload
Non-Cleavable ADC: Enzymes
degrade mAb to release amino
acid capped-linker-payload
Modified from Schrama et al., 2006
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ADC and Payload Physiochemical Properties
calicheamicin
Pfizer ACD Payload
Monographic supplement series CROs/CMOs - Chimica Oggi - Chemistry Today - vol. 31(4) July/August
2013
O
O
CH3
I
O
O
O
H3C
CH3
CH3
HO
O
NH
OH
CH3
OO
O
S
O
CH3
S
NH
S
CH3
O
H3C
OH
O
H3C
O
HO
OH
CH3
O
NH NH2
OO
N
H3C
O
CH3
O
CH3
N-acetyl-γ-calicheamicin DMH structure
Monoisotopic Mass = 1477.3764
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Developing Regulated LC-MS/MS ADC Assays
ADC Assay Considerations
•  Complex molecular entities
•  Previous data suggests that pH
should be maintained in the 5-8
range.
•  Factors influencing ADC stability:
•  Denaturation
•  Aggregation
•  Surface adsorption
•  Chemical instability
•  Shear stress, cross linking
and more
•  Payload stability
•  Cyclization @ ↑ pH
•  Thermodynamically stable
Regulated Bioanalysis Requirements
•  Solution Stability
•  Acceptable batch run statistics
(Intra and Inter)
•  Acceptable matrix effect profile
(matrix factor, ionization effects)
•  Demonstrated selectivity
•  Reproducible recovery
•  Stability in matrix
•  Freeze and thaw
•  Room temperature
•  Processed sample
•  Short and Long Term
•  Stability of the payload must
be demonstrated with and
without the presence of the
ADC
•  Incurred Sample Reanalysis (ISR)
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LC-MS/MS Assay Considerations
Liquid Chromatography
•  Porous and non-porous (Core shell)
chromatography is used
•  HPLC, UFLC, UHPLC (UPLC)
capabilities
•  Gradient separations are typical @
low pH
•  Data suggests that UHPLC is
needed for separations and
throughput
•  100 µm columns, 1-2.1 mm IDs,
1.7 µ particle size
•  Micro flow (1- 25 µL/min)
applications will be evaluated
(Eksigent, Dionex)
Mass Spectrometry
•  Triple Quad Quantitation
•  Platform types include:
•  API4000, API6500
•  API5500
•  limited quantitative mass
range 10–1250 Da
•  Singly ([M+H]+) and doubly ([M
+2H]2+) charged ions have been
used for quantitation
•  In-source fragmentation occurring
•  Micro flow probes (25, 50 µm) have
been evaluated to ↑ sensitivity
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m/z 414
9.8e7
m/z 619
2.2e8
m/z 414
3.4e8
API5500
Micro probe (50 um)
M+H
m/z 619
5.5e7
API5500
Micro probe (50 um)
M+2H
API5500
STD probe (160 um)
M+2H
API5500
STD probe (160 um)
M+H
Micro Flow Method Development (API5500)
m/z 414
2.3e8
m/z 619
1.2e8
m/z 414
4.5e8
m/z 619
3.3e8
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Sample collection and Logistics
•  Sample collection and its challenges:
•  Blood collected on ice
•  Matrix samples typically stored at -70ºC
•  Samples typically serum but plasma is coming
•  Logistics plays a critical role as follows:
•  Establishes data standards for proper LIMS
database integration
•  Links LIMS with downstream sample processing
using automation (1D and 2D barcodes)
•  Standardizes tubes and cold storage
processes
•  Facilitates faster sample analysis
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Sample Preparation
•  Preparation of calibration standards and quality
control samples (wet-ice, 4ºC)
•  Prepare samples prior to extraction:
•  pH
•  internal standard fortification
•  Biospecimen aliquoting
•  ADC sample analysis
•  Typically analyzed on wet-ice (4ºC)
•  Require more selective extractions
•  May need multiple sample preparation and
extraction protocols (e.g. ~PPT -> SPE)
+
GUI
+
Hamilton Method
Hamilton Microlab STAR
LC-MS/MS Analysis
Change in total payload concentration
(ADC bound + Free Payload)
Sample 25ug/mL sample 300ug/mL sample Stability Sample ADC-L ADC-L+PL ADC-L+PH ADC-H ADC-H+PL ADC-H+PH M ADC M PL 0.000000171 0.000000343 0.00000206 0.00000411 pg/mL Total Payload 254736 254781 266736 3056832 3056877 3068832 pg/mL PL 254736 3056832 High %
Change Low %change 0.000111 0.00118 -0.262 0.000398 0.00312 0.0418 -0.00313 -0.00896 -1.77 -0.00276 -0.00284 -0.121 Pfizer Proprietary
Sample Extraction
•  More selective assays may be required to
increase assay robustness (SPE, SLE, LLE).
•  Increasing assay selectivity is a recommended
approach, but can be more generic:
•  ACN vs. MeOH vs. mixture
•  Acid vs. base vs. neutral
•  SPE plate format (µElution)
•  HLB (polymer) vs. mixed mode
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Automated ADC-Payload Bioanalysis
Goal: Using the Hamilton STAR robotic liquid handling platform with dedicated
temperature controlled hardware, develop a range of automated bioanalytical
assays suitable for ADC-payload bioanalysis.
•  Applicable for pre-clinical and clinical ADC-payload
bioanalytical study support.
•  Maintain a constant cold temperature of 4ºC throughout:
• 
the preparation of calibration standards and quality control
samples.
•  the entirety of the sample preparation and extraction
protocol.
•  Assays anticipated to be validated:
•  SPE, SLE, LLE, PPT
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Robotic Platform Hardware Modifications
Right View
Left View
AVS Manifold
Chiller Modules (2)
Insulated Tubing
Cold Temperature Hardware
•  96 well plate(s)
•  Solvent/Matrix reservoirs
•  96-well cluster tubes (Tox)
•  13-15 mm clinical sample tubes
•  4 or 8 mL glass vials
Integrated Shaker
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Limitations and Trade-offs
• 
• 
• 
Pipetting:
•  RT vs 4ºC liquids result in different pipetting accuracy.
•  Required testing includes:
•  Gravimetric and colorimetric evaluations (RT vs. 4ºC).
•  Iterative changes to liquid class (correction curves).
Logistics
•  No 1D barcode capability
•  Blood samples collected on ice (serum and plasma).
•  Limited sample volume contributes to rigid matrix sample aspiration
procedures (pre-clinical).
•  Only a few collection tubes can be used on the cold temperature
hardware (clinical).
Stacked Assays (increased complexity):
•  PPT followed by SPE, SLE
•  requires special programing and file handling in order to perform
two sample preparation or extraction assays for a single batch
run.
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Improving Automated Assay Quality
Pipetting:
•  Air vs. positive vs. liquid-air
•  Colorimetric (Artel, Hamilton)
•  Gravimetric
•  Assay results
T
T
T
300 µL
100 µL
10 µL
Labware:
•  Definitions must be as
accurate as possible
•  Positioning must
accommodate
disparate types of
labware
•  Standardization
improves assay
performance
Slice Data
mm
1
2
3
4
5
6
7
8
9
10
volume (inch cubed) volume (microliters)
1.87102538E-04
3.066
5.09713660E-04
8.353
8.77463785E-04
14.379
1.29309230E-03
21.190
1.75985974E-03
28.839
2.28006694E-03
37.364
2.85702727E-03
46.818
3.58762054E-03
58.791
4.79584128E-03
78.590
6.46893697E-03
106.007
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Improving Automated Assay Quality (cont.)
Room Temperature
4C
•  Routine volumes used in
single step: 10 – 1000 uL
•  Significant differences in
accuracy: RT vs. 4C
•  Gravimetric assessments
in sample matrix are
required to correct volume
differences
Pressure monitoring through platform software:
total aspirate and dispense monitoring (TADM)
•  Pressure monitoring evaluated
to enhance sample aspirate
and dispense traceability
•  Some practical
implementation problems
associated with error handling
•  Increased confidence begets
routine use
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Assay Data
Run
Curve LLOQ_QC
LOW_QC
MED_QC
Date Number 0.100 ng/mL 0.300 ng/mL 2.50 ng/mL 24-Jun-14 3 0.118 0.316 0.104 0.318 0.111 0.305 0.100 0.315 0.110 0.319 0.109 0.314 25-Jun-14 4 0.110 0.330 0.104 0.332 0.116 0.322 0.103 0.320 0.114 0.332 0.105 0.316 27-Jun-14 6 0.106 0.325 0.100 0.314 0.105 0.313 0.106 0.324 0.107 0.332 0.112 0.339 Mean S.D. %CV %Theoretical %Bias n 0.108 0.00512 4.7 108 8 18 0.321 0.00877 2.7 107 7 18 HIGH_QC
10X_DIL_QC 100X_DIL_QC LOW_BT_QC HIGH_BT_QC LOW_FT_QC HIGH_FT_QC
16.0 ng/mL 100 ng/mL 100 ng/mL 0.300 ng/mL 16.0 ng/mL 0.300 ng/mL 16.0 ng/mL 2.55 15.9 97.4 2.61 16.2 99.7 2.63 16.6 97.5 2.60 15.9 101 2.60 16.3 98.1 2.55 16.1 99.2 2.60 17.0 104 2.61 17.0 106 2.60 16.4 107 2.59 16.7 102 2.58 16.1 103 2.58 16.9 102 2.70 16.9 0.333 16.1 0.297 15.7 2.69 16.6 0.306 16.1 0.320 15.6 2.62 16.2 0.325 15.8 0.314 15.9 2.65 16.4 0.317 16.1 0.311 15.9 2.67 16.3 0.311 15.7 0.312 15.4 2.61 16.7 0.32 16.3 0.311 15.7 2.61 0.0419 1.6 104.4 4.4 18 16.5 0.36 2.2 103.1 3.1 18 104 2.1 2 104 4 6 98.8 1.41 1.4 98.8 -1.2 6 0.319 0.00969 3 106.3 6.3 6 16 0.223 1.4 100 0 6 0.311 0.00757 2.4 103.7 3.7 6 15.7 0.19 1.2 98.1 -1.9 6 Summary:
•  Assay range: 0.100 – 20 ng/mL
•  4 QC levels (0.100, 0.300, 2.5 and 16 ng/mL)
•  100% of quality control samples meet acceptance criteria (108/108)
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Conclusion
•  Many challenges exist in the regulated
quantitative bioanalysis of ADC-payloads.
•  Robust automated workflows are achievable for
the regulated bioanalysis of ADC-payloads.
•  A resource investment must be made to deliver
a suitable hardware solution.
•  Labware must be re-developed to
accommodate reduced sample volumes.
•  Significant pipetting accuracy differences are
observed from RT to 4ºC.
•  Liquid class creation requires careful attention.
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Acknowledgements
Zhenhua Gu
Mark Milisci
Leanne Grafmuller
Mark Wallace
Henry Zeng
James Saunders
Frances Clark
Ying Zhang
Mauricio Leal
Alex Porte
Amarnauth Prashad
Quazi Shakey
Ragu Ramanathan
Rick Steenwyk
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Backup Slides
Backup Slides
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Artel @ 50 uL
Room Temperature
4ºC
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Graphical User Interface
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Platform Integration
Figure3 from Tweed, et. al , Bioanalysis 2010 2(6)
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2D Barcode Workflow
Figure 3 from Tweed, et. al , Bioanalysis 2012 4(3)
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Validation Statistics (Expanded)
Run
Date Mean S.D. %CV %Theoretical %Bias n Curve
Number 24-Jun-14 3 25-Jun-14 4 27-Jun-14 6 17-Jul-14 9 24-Jul-14 10 LLOQ_QC
0.100 ng/mL 0.118 0.104 0.111 0.1 0.11 0.109 0.11 0.104 0.116 0.103 0.114 0.105 0.106 0.1 0.105 0.106 0.107 0.112 0.111 0.102 0.113 0.112 0.105 0.111 0.0983 0.0948 0.102 0.103 0.106 0.0998 LOW_QC
MED_QC
HIGH_QC 100X_DIL_QC
0.300 ng/mL 2.50 ng/mL 16.0 ng/mL 100 ng/mL 0.316 2.55 15.9 97.4 0.318 2.61 16.2 99.7 0.305 2.63 16.6 97.5 0.315 2.6 15.9 101 0.319 2.6 16.3 98.1 0.314 2.55 16.1 99.2 0.33 2.6 17 0.332 2.61 17 0.322 2.6 16.4 0.32 2.59 16.7 0.332 2.58 16.1 0.316 2.58 16.9 0.325 2.7 16.9 0.314 2.69 16.6 0.313 2.62 16.2 0.324 2.65 16.4 0.332 2.67 16.3 0.339 2.61 16.7 0.318 2.6 16.3 0.313 2.67 15.8 0.307 2.66 16.1 0.305 2.79 16.1 0.308 2.57 16 0.314 2.65 15.9 0.307 2.41 16.8 0.312 2.5 16.8 0.314 2.47 17.2 0.312 2.53 17.6 0.309 2.5 17.5 0.326 2.56 17.6 10X_DIL_QC
100 ng/mL LOW_BT_QC
0.300 ng/mL HIGH_BT_QC
16.0 ng/mL LOW_FT_QC
0.300 ng/mL HIGH_FT_QC
16.0 ng/mL 0.333 0.306 0.325 0.317 0.311 0.32 16.1 16.1 15.8 16.1 15.7 16.3 0.297 0.32 0.314 0.311 0.312 0.311 15.7 15.6 15.9 15.9 15.4 15.7 104 106 107 102 103 102 0.107 0.00554 5.2 0.318 0.00891 2.8 2.6 0.0744 2.9 16.5 0.517 3.1 98.8 1.41 1.4 104 2.1 2 0.319 0.00969 3 16 0.223 1.4 0.311 0.00757 2.4 15.7 0.19 1.2 107 7 30 106 6 30 104 4 30 103.1 3.1 30 98.8 -1.2 6 104 4 6 106.3 6.3 6 100 0 6 103.7 3.7 6 98.1 -1.9 6 • 
100% of quality control samples meet acceptance criteria (156/156)
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