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© 2019 Artel1
© 2013 ARTEL
SLAS2019 Tutorial: Coupling Assay Design And
Process Optimization Toward Minimizing Variability
Nathaniel Hentz, PhD
05 February; 12:30-1:15P
Acknowledgment: Becky Kitchener, PhD
© 2019 Artel2
© 2013 ARTEL
Tutorial Agenda
▪ Assay variability
▪ Liquid handler optimization: current practices
▪ Process optimization – What? Why? How?
▪ Case study: model assay & findings
▪ Conclusions
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© 2013 ARTEL
OVERVIEW: ASSAY VARIABILITY
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© 2013 ARTEL
Assay
Detector
ALH
Settings
Sample
Environment
Hardware /
Labware
Plate type, tip type,
tubing, automation
Off-set volume, single/multi
dispense, aspirate/dispense
rate, aspirate/dispense
height, liquid class, pre / post
air gaps, etc.
PMT, wavelength, x-y-z
position
Mixing, incubation
time, centrifugation, #
liquid transfers, wash
steps, dilution steps,
serial dilutions
Viscosity, density,
surface tension,
volatility
Temperature,
humidity, light,
vibration
Parameters that Effect Assay Variability
© 2019 Artel5
© 2013 ARTEL
Assay Validation in a High-Throughput World
Reagent
Stability
Signal
Variability
Plate
Uniformity
DMSO
Compatibility
Reaction
Stability
Assay
© 2019 Artel6
© 2013 ARTEL
So, What Does A “Good” Assay Look Like?
Let’s define a couple of parameters:
▪ First, let’s consider the assay variability
▪ Second, let’s consider the assay window
−
+−=
minmax
minmax 331
Z
Z-Factor Value Assay Quality
1 Ideal assay
1 > Z ≥ 0.5 Excellent assay
0.5 > Z > 0 Marginal assay
0 Yes/no assay
<0 Assay not useful
© 2019 Artel7
© 2013 ARTEL
The Result
Z’ = 0.74
0 1 2 2 4 3 6 4 8 6 0 7 2 8 4 9 6
0
2 0 0 0
4 0 0 0
6 0 0 0
8 0 0 0
1 0 0 0 0
W e ll ID
Sig
na
l (R
FU
)
Z’ = 0.94
0 1 2 2 4 3 6 4 8 6 0 7 2 8 4 9 60
2 0 0 0
4 0 0 0
6 0 0 0
8 0 0 0
1 0 0 0 0
W e ll ID
Sig
na
l (R
FU
)
© 2019 Artel8
© 2013 ARTEL
-2 -1 0 1 20
1000
2000
3000
4000
Log Inhibitor (nM)
Sig
na
l (
RF
U)
Opt 1
Opt 2
Opt 3
The Result
Useful assay descriptors:
Hill slope
Assay span
Upper asymptote
Lower asymptote
Variability
© 2019 Artel9
© 2013 ARTEL
OVERVIEW:
LIQUID HANDLER OPTIMIZATION
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© 2013 ARTEL
Liquid Dispense Technologies
Dispense Technology Attributes
Air displacement
• Problematic for volatile liquids
• Possible cross contamination
• Wide range of volumes
Positive displacement
• Useful for volatile solvents
• Cross contamination possible
• Wide range of volumes
Droplet (acoustic)• Non-contact
• Useful for small volumes (pL – nL)
Droplet (solenoid/inkjet)• Useful for small volumes (nL)
• Sensitive to fluid types
Capillary (pintool)
• Useful for small volumes
• Direct contact with sample
(contamination)
• Sensitive to fluid type
Peristaltic• Useful for bulk dispense;
• More frequent calibrations needed
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© 2013 ARTEL
Parameters that Effect Volume Transfer
▪ Hardware/labware – plate format, tip types, tubing type
▪ ALH settings – target (or off-set) volume, single/multi dispense,
aspirate/dispense rate, aspirate/dispense height, liquid class, pre and post air
gaps, accuracy/precision of volume transfer, transfer speed/time delays, on-
board mixing
▪ Assay – reagent mixing, incubation, centrifugation, number of liquid transfers,
wash steps, dilution steps, serial dilutions
▪ Sample – viscosity, density, surface tension, temperature, volatility
▪ Environment – temperature, humidity, light, vibration
© 2019 Artel12
© 2013 ARTEL
Typical Liquid Handler Optimization
▪ Usually performed as a stand-alone activity
▪ Precision is always checked, but accuracy is not as easy
▪ Several methods for volume verification
▪ In-house (e.g., fluorescence, gravimetric, absorbance, etc.)
▪ Commercial (e.g., dual-dye spectrophotometry)
▪ Volume verification is typically performed with ideal solutions
▪ Liquid handler is certified, calibrated, or repaired (if necessary)
▪ Then….someone programs ALH for assay use
▪ Default method
▪ Specific to basic assay requirements
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© 2013 ARTEL
Artel MVS: A Useful Tool
▪ Employs a dual-dye, dual-wavelength,
ratiometric absorbance-based
measurement method for calculating the
dispense volume.
▪ How it works: dyes of known concentration
are dispensed into well-characterized
microtiter plate. The plate is mixed on a
plate shaker to ensure solution
homogeneity. Absorbance readings are
taken at 520 nm and 730 nm.
=
730
520
r
bTS
A
A
a
aVV
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© 2013 ARTEL
ADOPTING A PROCESS OPTIMIZATION APPROACH
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© 2013 ARTEL
Instrumentation
▪ Liquid handlers
▪ Detectors
▪ Mixers
▪ Incubators
▪ Centrifuges
Consumables
▪ Reagents
▪ Tips
▪ Plate type
▪ Plate seals
Sources of Assay Variability
Biology
▪ Diffusion
▪ Binding equilibrium
▪ Steric hindrance
▪ Cell population
diversity
▪ Protein activity
Environment
▪ Temperature
▪ Light
▪ Humidity
▪ People
What can
we control or
optimize?
© 2019 Artel16
© 2013 ARTEL
Artel MVS is More Than a Calibration Tool
Trouble-
shooting
Serial
Dilutions
Mixing
Plate
Washing
Tip
Evaluation
Calibrations
Plate
Evaluation
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© 2013 ARTEL
CASE STUDY
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© 2013 ARTEL
Assessing Effects of Liquid Handling on the Assay
▪ Phase I: Using a well-characterized model assay, develop and optimize the
assay platform at bench scale.
▪ Phase II: Perform method transfer to ALH: examine effects of automated
liquid handling parameters on the same assay.
▪ Phase III: “Deconstruct” the assay: decide which parameters, when altered,
significantly vary assay outcome.
© 2019 Artel19
© 2013 ARTEL
Streptavidin: Biotin-Fl Assay Principle
Streptavidin (SA) is a tetravalent biotin-binding protein that is isolated from
Streptomyces avidinii and has a mass of 60.0 kDa. SA has a very high affinity
for biotin (Kd = 10-14 to -15 M).
1. Waner, MJ; Mascotti DP. Journal of Biochemical and Biophysical Methods 70(6), 2008, 873-877.
2. Ebner, A; Marek, M; Kaiser, K; Kada, G; Hahn, CD; Lackner, B; Gruber, HJ. Methods in
Molecular Biology, 418, 2008, 73-88.
Quenched fluorescence
SA
Fl
FlFl
Fl
SA
Enhanced fluorescence
Assay Set-up
▪ PBS, PBS+0.1%BSA, and PBS+0.1% glycerol
▪ Add 25 µL of biotin-4-fluorescein (Fl) to black 96w
plate
▪ Add 25 µL of inhibitor
▪ Add 25 µL of streptavidin (SA)
▪ Incubate for 30 min at room temperature
▪ Read fluorescence: Ex = 485 nm and Em = 515 nm
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© 2013 ARTEL
Assay Development Parameters Evaluated
Parameter Manual Automated
Solution stability X X
Plate type X X
Background buffer X X
Inhibitor X X
Inhibitor conc. X X
Incubation time X X
Mixing X X
Pipette calibration X
Asp/Disp rates X
Fluid exit rate X
Air gaps X
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© 2013 ARTEL
PB
S M
an
ual
PB
S A
uto
BS
A M
an
ual
BS
A A
uto
GL
Man
ual
GL
Au
to
PB
S M
an
ual
PB
S A
uto
BS
A M
an
ual
BS
A A
uto
GL
Man
ual
GL
Au
to
0 .0
0 .2
0 .4
0 .6
IC5
0 (
M)
N o M ix
M ix
Effect of Mixing on Assay Variability
Key Takeaway
Buffer has an impact on
mixing; Mixing improved BSA
and glycerol buffers
PBS = phosphate buffered saline / BSA = PBS + 0.1% bovine serum albumin / GL = PBS + 0.1% glycerol
Mixing was conducted by
aspirating and dispensing 3
cycles after the third reagent was
added. The plates were then
incubated for 30 minutes at room
temperature.
© 2019 Artel22
© 2013 ARTEL
-2 -1 0 1 20
1000
2000
3000
4000
Log Inhibitor Concentration (nM)
Sig
na
l (
RF
U)
PBS
BSA
Glycerol
Effect of Buffer Type on Assay Performance
-2 -1 0 1 20
1000
2000
3000
4000
Log Inhibitor Concentration (nM)
Sig
na
l (
RF
U)
PBS
BSA
Glycerol
Manual Mixing Auto Mixing
Key Takeaway
Manual mixing can behave differently than automated
mixing, especially depending on assay buffer ingredients.
© 2019 Artel23
© 2013 ARTEL
Effect of Source Plates on Automated Liquid Handler Verification
A
B Key Takeaway
Source plate affected the destination
plate – observed by visual inspection
Artel MVS plates containing
reagent from non-binding (A) and
untreated (B) 96w black source
plates.
MVS precision: 6.3% for non-
binding and 1.2% for untreated
© 2019 Artel24
© 2013 ARTEL
PBS M
anual
PBS A
uto
GL M
anual
GL A
uto
PBS M
anual
PBS A
uto
GL M
anual
GL A
uto0.0
0.1
0.2
0.3
0.4IC
50
(
M)
Non-binding
Untreated
Effect of Plate Type on Assay Variability
Key Takeaway
When subjected to the assay, the
uncoated plate yielded slightly
lower variability.
PBS = phosphate buffered saline / BSA = PBS + 0.1% bovine serum albumin / GL = PBS + 0.1% glycerol
Black, 96-well plates used:
• Corning #3650 (Non-binding)
• Corning #3915 (Untreated)
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© 2013 ARTEL
Effect of Reagent Temperature on Assay Variability
-2 -1 0 1 20
1000
2000
3000
4000
5000
Log Inhibitor Concentration (nM)
Sig
nal (R
FU
)
Cold Reagent Dispense
Room Temp Dispense
IC50 (µM)
0.311
0.235
Key Takeaway
Cold reagent dispense
yielded slightly lower potency
“Cold reagents” were stored at 4°C until use. The reagents were not maintained at 4°C during pipetting.
© 2019 Artel26
© 2013 ARTEL
Effect of Aspirate (ASP) Speed on Assay Performance
-2 -1 0 1 20
1000
2000
3000
4000
Log Inhibitor Concentration (nM)
Sig
nal (R
FU
)
Aspirate 1 PBS
Aspirate 5 PBS
Aspirate 5 GL
Aspirate 1 GL
Aspirate 1 BSA
Aspirate 5 BSA
IC50 (µM)
0.157
0.163
0.151
0.225
0.145
0.207
Key Takeaway
Aspirate speed affected potency for
glycerol and BSA buffers
PBS = phosphate buffered saline / BSA = PBS + 0.1% bovine serum albumin / GL = PBS + 0.1% glycerol
© 2019 Artel27
© 2013 ARTEL
-2 -1 0 1 2
0
1000
2000
3000
4000
Log Inhibitor Concentration (nM)
Sig
nal (R
FU
)
Dispense 1 BSA
Dispense 5 BSA
Dispense 1 GL
Dispense 5 GL
Dispense 1 PBS
Dispense 5 PBS
Effect of Dispense (DISP) Speed on Assay Performance
IC50 (µM)
0.268
0.2660.136
0.197
0.164
0.167
Key Takeaway
Dispense speed affected potency
for glycerol but not PBS or BSA
PBS = phosphate buffered saline / BSA = PBS + 0.1% bovine serum albumin / GL = PBS + 0.1% glycerol
© 2019 Artel28
© 2013 ARTEL
-2 -1 0 1 2
0
1000
2000
3000
4000
Log Inhibitor Concentration (nM)
Sig
nal (R
FU
)
AirGap0BSA
AirGap2BSA
AirGap5BSA
AirGap0GL
AirGap2GL
AirGap5GL
AirGap0PBS
AirGap2PBS
AirGap5PBS
Effect of Air Gap on Inhibitor Potency
IC50 (µM)
0.243
0.269
0.171
0.179
0.155
0.163
0.172
0.175
0.205
Key Takeaway
Air gap affects the assay containing PBS
and BSA buffers with respect to potency and
variability
PBS = phosphate buffered saline / BSA = PBS + 0.1% bovine serum albumin / GL = PBS + 0.1% glycerol
© 2019 Artel29
© 2013 ARTEL
PB
S
BS
A
GL
PB
S
BS
A
GL
PB
S
BS
A
GL
0 .0
0 .1
0 .2
0 .3
0 .4
IC5
0 (
M)
A irG a p 0
A irG a p 2
A irG a p 5
Effect of Air Gap on Assay Variability
PBS = phosphate buffered saline / BSA = PBS + 0.1% bovine serum albumin / GL = PBS + 0.1% glycerol
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© 2013 ARTEL
Study Summary
▪ Four assay parameters were identified which required optimization both
during development at bench-scale and on the ALH.
▪ Assay buffer selection
▪ Mixing
▪ Reagent stability
▪ Plate type
▪ Certain ALH parameters were dependent on buffer type. Not all ALH
parameters will effect an assay.
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© 2013 ARTEL
Conclusions
▪ Performing assay optimization AND liquid handler optimization together as
a whole process reduces potential for error introduction and
prolonged/difficult method transfer.
▪ Evaluate critical liquid handling parameters and potential sources of
variability at bench scale and on the ALH for each new assay.
Assay optimization or LH qualification alone isn’t enough.
© 2019 Artel32
© 2013 ARTEL
Putting It
Together… Assays
depend on
reagent
concentrations
Reagent
concentrations
are volume-
dependent THEREFORE:
Assay
integrity is
dependent on
accurate
volume
deliveryAssay results are impacted by
liquid handling variability
© 2019 Artel33
© 2013 ARTEL