Journal of Laboratory Automation

Journal of Laboratory
Automation
http://jla.sagepub.com/
A User-Friendly Robotic Sample Preparation Program for Fully Automated Biological Sample Pipetting
and Dilution to Benefit the Regulated Bioanalysis
Hao Jiang, Zheng Ouyang, Jianing Zeng, Long Yuan, Naiyu Zheng, Mohammed Jemal and Mark E. Arnold
Journal of Laboratory Automation 2012 17: 211 originally published online 24 January 2012
DOI: 10.1177/2211068211429775
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429775
Jiang et al.Journal of Laboratory Automation
JLAXXX10.1177/2211068211429775
A User-Friendly Robotic Sample
Preparation Program for Fully Automated
Biological Sample Pipetting and Dilution
to Benefit the Regulated Bioanalysis
Journal of Laboratory Automation
17(3) 211­–221
© 2012 Society for Laboratory
Automation and Screening
DOI: 10.1177/2211068211429775
http://jala.sagepub.com
Hao Jiang1, Zheng Ouyang2, Jianing Zeng1, Long Yuan1, Naiyu Zheng1,
Mohammed Jemal2, and Mark E. Arnold1
Abstract
Biological sample dilution is a rate-limiting step in bioanalytical sample preparation when the concentrations of samples are
beyond standard curve ranges, especially when multiple dilution factors are needed in an analytical run. We have developed
and validated a Microsoft Excel–based robotic sample preparation program (RSPP) that automatically transforms Watson
worklist sample information (identification, sequence and dilution factor) to comma-separated value (CSV) files. The
Freedom EVO liquid handler software imports and transforms the CSV files to executable worklists (.gwl files), allowing
the robot to perform sample dilutions at variable dilution factors. The dynamic dilution range is 1- to 1000-fold and divided
into three dilution steps: 1- to 10-, 11- to 100-, and 101- to 1000-fold. The whole process, including pipetting samples,
diluting samples, and adding internal standard(s), is accomplished within 1 h for two racks of samples (96 samples/rack). This
platform also supports online sample extraction (liquid-liquid extraction, solid-phase extraction, protein precipitation, etc.)
using 96 multichannel arms. This fully automated and validated sample dilution and preparation process has been applied
to several drug development programs. The results demonstrate that application of the RSPP for fully automated sample
processing is efficient and rugged. The RSPP not only saved more than 50% of the time in sample pipetting and dilution but
also reduced human errors. The generated bioanalytical data are accurate and precise; therefore, this application can be
used in regulated bioanalysis.
Keywords
robotic sample preparation program, automated, sample dilution and preparation
Introduction
Bioanalytical sample pipetting and dilution are a bottleneck
in bioanalytical process due to the complexities in sample
preparation. At least four types of samples need to be
included in an analytical run, namely, blanks, standards,
quality controls (QCs), and study samples.1 The sequence
and replicates of these samples in an analytical run are different run to run. When using 96-well plates for sample
processing, the locations of blanks, standards, QCs, and
study samples on the plates vary from run to run. Study
samples and QCs are required to be interspersed in the
96-well plate and are bracketed by standards placed at the
front and back of the run. In addition, when the concentrations of samples are beyond standard curve ranges, study
samples need to be diluted up front before being transferred
to 96-well plates for further sample clean up (liquid-liquid
extraction, solid-phase extraction, or protein precipitation,
etc.). Sometimes different dilution factors (DF) should
apply to different bioanalytical samples in a run (e.g., pharmacokinetic samples), which make the process even more
complicated. If an internal standard is needed for an assay,
the internal standard should be added to all standards, QCs,
and study samples except for blanks to which a solvent is
added. The overall process in preparing samples for an analytical run (less than 96 samples × two plates) is very labor
intensive and extremely time-consuming if the samples are
1
Bioanalytical Sciences Department, Bristol-Myers Squibb Company,
Princeton, New Jersey, USA
2
Bioanalytical & Discovery Analytical Sciences Department, Bristol-Myers
Squibb Company, Princeton, New Jersey, USA
Received July 15, 2011.
Corresponding Author:
Hao Jiang or Jianing Zeng, Bristol-Myers Squibb, Bioanalytical Sciences,
Rt. 206 & Province Line Rd, Princeton, NJ 08543
Email: hao.jiang@bms.com or jianing.zeng@bms.com
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212
Journal of Laboratory Automation 17(3)
pipetted and diluted manually. Generally, it takes about 2 to
4 h to complete this step of sample preparation depending
on sample quantity, number of samples needed to be diluted,
and steps of the dilution process. Besides, it is very hard to
control human errors during the long and boring process in
sample pipetting and dilution.
Current available liquid-handling robots such as Tecan
Freedom EVO, Tecan Genesis RSP, Hamilton STAR line,
and JANUS Automated Workstation have been widely used
for liquid pipetting and sample preparation in laboratories.
Some studies2–11 reported that automations had been applied
for pipetting samples and solvents to facilitate sample preparation and extraction, but samples had to be diluted manually before automatic sample extraction, or all the samples
should have a consistent DF and preassigned locations on
96-well plates; otherwise, it is not possible to accommodate
the process to different analytical runs with different sample numbers, DF, and varied sample locations on 96-well
plates. Although there is a worklist function available in
some robots, it is very time-consuming and error prone to
program a robotic script for each sample’s dilution in every
analytical run. Some robots support worklist functions to
allow bioanalyst’s entry of sample information (e.g., source
position, destination position, volume, and liquid class) to a
comma-separated values (CSV) worklist that is executable
by robotic scripts, but it is still not practical or efficient to
edit the CSV worklist for every analytical run. A Microsoft
Visual C++ program12 has been developed recently that is
capable of automatically generating run-specific robot
scripts for fully automated sample pipetting, dilution, and
downstream sample extraction. This program is the first
successful program for automated sample dilution, which
makes the sample preparation process fully automated.
However, a unique script has to be generated for every
individual run, and the complexity of the generated script
with several hundred robot commands makes it impossible to effectively troubleshoot during sample pipetting and
dilution.
We have developed and validated a Microsoft Excel–
based robotic sample preparation program (RSPP). The
RSPP contains a dilution calculation spreadsheet and a
Visual Basic for Applications (VBA) macro to automatically transform sample information from a Watson worklist
to executable CSV worklists that contain each sample’s
dilution scheme, source well positions, destination well positions, and liquid classes. A preprogrammed robotic script that
operates within the Freedom EVO software (EVOware)
with several executable commands transforms the CSV
files to executable worklists (.gwl files) and then executes
the sample pipetting and dilution. It is simple and easy for
troubleshooting errors in sample pipetting and dilution
because EVOware records each step of liquid pipetting and
is able to continue pipetting from an unexpected stop in a
run. The RSPP program can be integrated within other robot
commands to facilitate a fully automated sample preparation and extraction.
Experimental
Materials
Drug-free K2EDTA plasma specimens were purchased from
Bioreclamation Inc. (Hicksville, NY). Deionized water was
prepared from an in-house Barnstead Nanopure Diamond
system (Dubuque, IA). All solvents for sample extraction
and LC-MS/MS were obtained from different vendors at
the highest grade available. Reference materials of
BMS-650032 and isotopically labeled BMS-650032
(internal standard) were obtained from Bristol-Myers
Squibb Company (New Brunswick, NJ). Dilution plates
(96-square well, 2.0 mL) were obtained from VWR Co.
and 96-microtube plates (1.1 mL) from National Scientific
Supply Co. (Claremont, CA).
Instrumentation
The liquid-handling robot used in this study was a Tecan
Freedom EVO150 liquid-handling unit equipped with
an eight-channel liquid handler (LiHa) arm and a
96-multichannel arm (96-MCA). The system was controlled
by Freedom EVO software, which had been validated for use
in regulated bioanalysis by the department staff and the internal Informatics Quality Assurance Group. The Freedom EVO
worktable was loaded with one disposable tip carrier (DiTi
200/1000, 2 Pos.), one solvent reservoir carrier (Trough 100
mL, 3 Pos.), three 96-well plate carriers (96-Well, 3 Pos.),
two 96-sample racks (16 × 6), and one 96-MCA carrier (see
Fig. 1). The following labware was used for sample dilution
and liquid-liquid extraction: one tray of 200-µL DiTi tips,
one tray of 1000-µL DiTi tips, three 100-mL troughs
(containing the diluent, the internal standard, and the blank
solvent, respectively), three 96-square well plates (dilution
plates, labeled as A, B, and C), one 96-microtube plate (a final
sample plate, labeled as D) for each rack of samples, and
three boxes of 96-MCA tips. A balance (Mettler AG285)
communicating with the workstation computer was used to
weigh and record weights of the liquid pipetted by the
Freedom EVO.
RSPP
The RSPP is a Microsoft Excel–based application that consists
of a calculation spreadsheet and a VBA macro (Fig. 2A, B).
The calculation spreadsheet contains an IF-THEN function
formula to determine six dilution parameters (source rack
label, source position, destination rack label, destination
position, volume, and liquid class) for samples and the diluent at each dilution step. The calculation is based on DF
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213
Jiang et al.
A
Trough 100 mL
Diluon 96-Well Plate
DiTi 200
Plasma
DiTi 1000
Water
Wash Staon
Balance
Plasma
Waste
Trough 100 mL
2B
2D
1C
2C
6)
1B
Sample
S
Rack 2 (16
6
Plaasma
1D
IS
Waste
2A
Solvent
DiTi 1000
1A
6)
Diluon 96-Well Plate
Wash Staon
DiTi 200
Final 96-Microtube Plate
SSample Rack 1 (16
6
B
Final 96-Microtube Plate
C
96-Well LLE
Collecon Plate
Recon.
Soluon
96-MCA Carrier
1D’
1D
1D
2D’
2D
Extracon
Solvent
Buffer
Figure 1. Freedom EVO worktable configuration. (A) System gravimetric verification. (B) Sample diliution. (C) Liquid-liquid extraction.
from Watson worklist and preset parameters (final diluted
sample volume, internal standard volume, and liquid
classes for pipetting samples; internal standards; diluents;
and diluted samples). The macro was programmed with the
VBA, which has the following functions:
1. copy and paste sample identification and dilution
factors (DF) from a Watson worklist (an Excel file
that is exported from Watson) to the calculation
spreadsheet,
2. clean and reformat the resulting spreadsheet with
dilution parameters, and
3. generate eight CSV files for sample pipetting,
diluting, and adding internal standard (IS)
The dilution range is 1- to 1000-fold, which is divided
into three dilution steps: 1- to 10-, 11-to 100-, and 101- to
1000-fold. An example of the dilution scheme for a final
volume of 50 µL samples is shown in Table 1. For samples
with DF ≤2, each sample (blanks, standards, QCs, or study
samples) is pipetted from a sample vial in a sample rack
(sample rack 1 or sample rack 2; Fig. 1B) to a final
96-microtube plate D (1D or 2D; Fig. 1B), and then an
appropriate volume of diluent (blank plasma) is added followed by automated pipette mixing. Similarly, for samples
with 2 < DF ≤ 10, each sample is pipetted to a plate C for
dilution; for samples with 10 < DF ≤ 100, each sample is
pipetted to a plate A for step 1 dilution and after the first
step of dilution to a plate C for step 2 dilution; for samples
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214
Journal of Laboratory Automation 17(3)
Figure 2. The interface of the robotic sample preparation program. (A) Calculation spreadsheet. (B) Visual Basic for Applications macro.
with 100 < DF ≤ 1000, each sample is pipetted to a plate A
for step 1 dilution, to a plate B for step 2 dilution, and to a
plate C for step 3 dilution. After the last dilution step for
each sample, the final diluted sample is pipetted to the plate
D. IS solution or a blank solvent is added to each sample
according to the specified sample types. A minimum sample
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215
Jiang et al.
Table 1. Representative Dilution Schemes for Diluted Samples with a Final Volume of 50 µL
Step 1 (DF 1-10)
Dilution
Factor
1
2
5
10
20
50
100
200
500
1000
Step 2 (DF 11-100)
Step 3 (DF 101-1000)
Final
Pipetting
IS Pipetting
Worklist 2
Worklist 3
Worklist 4
Worklist 5
Worklist 6
Worklist 7
Worklist 8
Worklist 1
Study Sample
(µL)
Diluent
(µL)
Diluted
Sample (µL)
Diluent
(µL)
Diluted
Sample (µL)
Diluent
(µL)
Diluted
Sample (µL)
Diluent
(µL)
0
0
0
0
0
0
0
50
50
50
50
50
50
50
50
50
50
50
50
50
50
25
25
25
25
25
25
25
25
25
0
25
100
225
225
225
225
225
225
225
0
0
50
50
50
50
50
50
50
50
0
0
0
0
50
200
450
450
450
450
0
0
0
0
50
50
50
50
50
50
0
0
0
0
0
0
0
50
200
450
Figure 3. Representative comma-separated value (CSV) worklists generated by the robotic sample preparation program macro. When
transferring CSV worklists to .executable GWL files, EVOware reads columns A to F (representing the dilution parameters of source
rack label, source position, destination rack label, destination position, volume, and liquid class, respectively) of worklists 1, columns G
to L of worklists 2, columns M to R of worklists 3, columns S to X of worklists 4, columns Y to AD of worklists 5, columns AE to AJ of
worklists 6, columns AK to AP of worklists 7, and columns AQ to AV of worklists 8.
volume of 25 µL is required for step 1 dilution to ensure
pipetting accuracy, and minimum 50 µL of samples is
required for step 2 and 3 dilutions. Six dilution parameters
for each sample at each step dilution are located in the specific columns in the CSV worklists (Fig. 3).
The RSPP is user friendly with a simple interface. The
VBA macro is executed by clicking the hyperlink of the
RSPP macro (the instruction panel; Fig. 2A); a pop-up
window then guides users to select an exported Watson
worklists. Lastly, a second pop-up window directs users to
generate eight CSV files to a user-defined project folder.
The program is closed automatically after successfully generating CSV worklists. For multiple analytical runs, these
eight CSV worklists will be updated for each analytical run,
and a run-specific backup worklist (with a time stamp on the
file name) will be generated.
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216
Journal of Laboratory Automation 17(3)
Verification of Freedom
EVO System Performance
Plasma Sample Collection
Deionized water was used as the standard solvent for system verification. The manufacturer’s default “water” liquid class was used for water aspirating and dispensing. Six
aliquots of 25 µL and 900 µL of water, respectively, were
aspirated and dispensed onto the online balance by each
channel pipettor (Fig. 1A). The weight of each aliquot was
recorded by EVOware. The accuracy (%Dev) and precision (%CV) for each pipettor at the volumes of 25 and 900
µL should be within 5%, based on the internal standard
operation procedure.
Verification of Plasma Pipetting Accuracy
and Precision
The manufacturer’s default “serum” liquid class was used as
a template for creating a customized liquid class. A volume
of 25, 50, 100, 200, 225, and 450 µL plasma (rat, dog, monkey, rabbit, mouse, or human plasma) was pipetted by
Freedom EVO onto the balance in replicates of six, respectively. The same volumes for these plasmas were manually
pipetted using calibrated handheld pipettors onto the balance
in replicates of six. The mean of six aliquots of rat plasma
at each volume was used as the nominal value for calculations. The mean %Dev of the weights from Freedom EVO
pipetting against the nominal values and %CV at each volume were calculated to determine the pipetting accuracy and
precision.
The impact of various sample volumes in tubes on
pipetting accuracy and precision was also evaluated for
two types of sample tubes. The BMS-customized 5 mL
tube has a built-in insert with a narrower inner diameter ( ˜ 5 mm). The Corning cryogenic tube has a bigger
inner diameter ( ˜ 10 mm, catalog no. 430491). Six replicate 25 µL volumes of plasma were pipetted from
each type of tube containing 50, 75, 100, and 200 µL of
rat plasma, respectively, and weighed. The %Dev and
%CV were calculated to evaluate the accuracy and
precision.
BMS-650032 Standards and
QC Sample Preparation
Standards (5.00, 10.0, 20.0, 50.0, 100, 500, 1000, and
2000 ng/mL) and QCs (5.00, 15.0, 25, 125, 1000, 1600
and 50 000 ng/mL) were prepared using calibrated
handheld pipettors in drug-free dog plasma by spiking
BMS-650032 stock solutions (1.0 mg/mL in methanol
from two separate weighings) and serial dilutions with
dog plasma. All QCs were aliquotted into polypropylene tubes and stored at approximately –20 °C. The
standards were freshly prepared on the day of sample
preparation.
Four male dogs were orally dosed with 400 mg of BMS650032 on days 1 and 8. Whole-blood (˜1 mL) samples
were collected into tubes containing K2EDTA at time
points 0, 1, 2, 3, 4, 8, and 24 h after dosing. The plasma was
separated after centrifugation and then transferred to polypropylene tubes for storage at –20 °C.
Plasma Sample Dilution Using
the RSPP and Freedom EVO
Study samples and standards/QCs were placed in sample
racks according to the sequence in the Watson worklist.
Two sets of the standards bracketed all study samples and
QCs in a run. QCs were interspersed among study samples.
QCs at the concentration of 25, 1600, and 50 000 ng/mL
(defined as RSPP QCs) were diluted at dilution factors of 1,
2, 5, 10, 20, and 200 in replicates of six to test dilution accuracy and precision. For each rack of samples, three 96-well
dilution plates (1A or 2A sample dilution plate, 1B or 2B
sample dilution plate, and 1C or 2C sample dilution plate)
and one 96-microtube plate (1D or 2D sample dilution plate)
were placed on the plate carrier as shown in Figure 1B.
Appropriate volumes of the diluent (drug-free dog plasma),
the IS solution (100 ng/mL of D9-BMS-650032 in 50%
acetonitrile/water), and blank solvent (50% acetonitrile/
water) were poured into the 100 mL trough reservoirs.
RSPP-generated CSV worklist were imported and transformed into .gwl files by “worklist import” command in
Freedom EVO scripts. The .gwl files were then executed by
the user selecting the “worklist execution” command to
pipette and dilute samples. A minimum volume of 25 µL of
a plasma sample was pipetted for the dilutions. The maximum volume in a well was 500 µL. Five cycles of aspirating and dispensing after pipetting the diluent (plasma) were
automatically conducted. There was also an option to use
manual mixing by modifying the liquid class by not activating the “mix after dispense” function. Several pauses were
inserted in between every dilution step to allow an optional
manual mixing. Once the final volume of 50 µL of each
blank, standard, QC, and study sample were pipetted into
the final sample plate, 50 µL of the IS solution was automatically pipetted to each sample.
Liquid-Liquid Extraction
and LC-MS/MS Detection
After completion of sample pipetting and dilution, a semiautomated liquid-liquid extraction was conducted by the
96-MCA that pipetted 100 µL of 1.0 M ammonium formate
buffer (pH ˜3) and 600 µL of ethyl acetate/hexane (10:90,
v/v) into each sample in the final sample plate, followed by
an offline vortexing for 1 min (Fig. 1C). After centrifugation
for 4 min at 2000×g, the upper organic layer was pipetted
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217
Jiang et al.
Table 2. System Verification for Pipetting Accuracy and Precision
Volume of Water (µL)
Tip
25 (n = 6)
900 (n = 6)
Mean Weight (mg)
Mean %Dev
%CV
Mean Weight (mg)
Mean %Dev
%CV
25.3
24.9
25.1
24.7
24.5
24.7
24.6
25.3
1.1
-0.3
0.5
-1.1
-2.1
-1.1
-1.5
1.1
1.2
1.0
1.1
1.3
1.6
1.1
0.6
0.6
906.0
905.9
905.5
905.5
904.1
905.0
905.4
906.0
0.7
0.6
0.6
0.6
0.5
0.6
0.6
0.7
0.0
0.1
0.1
0.3
0.0
0.0
0.0
0.0
1
2
3
4
5
6
7
8
Table 3. The Mean, %CV, and %Dev of Plasma Weights at Different Pipetting Volumes (Manual vs. Automated)
Nominal
Volume
(µL)
Mean Weight
(mg) of
Rat Plasma
by Manual
Pipetting,
(%CV)
Rat
Mouse
Rabbit
Monkey
Dog
Human
25
50
100
200
225
450
24.9 (1.6)
49.7 (1.8)
101.8 (0.7)
202.6 (2.1)
226.9 (0.9)
458.7 (0.5)
25.4 (0.8; 2.0)
50.6 (0.5; 1.8)
101.3 (0.2; –0.5)
204.2 (0.1; 0.8)
230.0 (0.1; 1.4)
458.1 (0.1; –0.1)
25.7 (0.5; 3.2)
50.5 (0.3; 1.6)
101.4 (0.2; –0.4)
204.3 (0.1; 0.8)
229.9 (0.1; 1.3)
458.6 (0.0; 0.0)
25.5 (0.7; 2.4)
50.8 (0.4; 2.2)
101.7 (0.2; –0.1)
204.6 (0.1; 1.0)
230.1 (0.1; 1.4)
458.8 (0.1; 0.0)
25.5 (2.5; 2.4)
50.7 (0.2; 2.0)
101.7 (0.2; –0.1)
204.8 (0.0; 1.1)
230.5 (0.1; 1.6)
459.3 (0.0; 0.1)
25.8 (0.9; 3.6)
50.7 (0.4; 2.0)
101.6 (0.1; –0.2)
204.9 (0.1; 1.1)
230.7 (0.2; 1.7)
459.5 (0.1; 0.2)
25.9 (0.5; 4.0)
50.7 (0.5; 2.0)
102.0 (1.0; 0.2)
204.9 (0.1; 1.1)
230.6 (0.0; 1.6)
459.9 (0.2; 0.3)
Mean Weight (mg) of Plasma Pipetted by Freedom EVO in Six Replicates (%CV; %Deva)
a. The weight from manual pipetting (by handheld pipettors) was used as the nominal value.
to a collection 96-well plate (labeled as 1D′ or 2D′ in Fig.
1C) and evaporated under nitrogen for 30 min at 40 °C. The
residue was reconstituted in 100 µL of 5 mM ammonium
bicarbonate in acetonitrile/water (50:50, v/v) and then
injected into the LC-MS/MS system for analyses.13
Chromatographic separation was achieved in 4 min on a
Waters Atlantis dC18 analytical column (2.1 × 50 mm, 3
µm) with the mobile phases A (10 mM ammonium bicarbonate) and B (acetonitrile) under a gradient program. Detection
was accomplished using a Sciex API4000 triple quadrupole
mass spectrometer using positive ion electrospray and multiple reaction monitoring (BMS-650032, m/z 748 > 535;
isotopically labeled BMS-650032, m/z 757 > 536).
Results and Discussion
Freedom EVO Pipetting
Accuracy and Precision
Water is commonly used as a standard solvent to evaluate
pipetting performance because its specific gravity is known
(˜0.998 g/mL at 25 °C) and it is easy to obtain in laboratories.
In this study, good pipetting accuracies (%Dev ≤ ±2.1%)
and precisions (%CV ≤ 1.6%) were demonstrated at both
volumes of 25 and 900 µL for eight channel pipettors
(Table 2). The results showed that the Freedom EVO was
accurate and precise in pipetting 25 to 900 µL liquids.
The relative gravity (density) of human plasma is about
2% higher than that of water.14 It is not practical to calibrate
Freedom EVO based on the plasma relative gravity15 because
it is labor intensive and has minimal benefit in improving
pipetting accuracy. In addition, minor differences in the
plasma from different species or individuals may exist. In
this study, a relative comparison between manual pipetting
(using handheld pipettors) and automated pipetting (by
Freedom EVO) was conducted. The mean weights of six aliquots of plasma from different sources were compared with
the mean weights of rat plasma by manual pipetting. The
maximum %Dev (2.5%) and %CV (4.0%) were observed at
the lowest pipetted volume (25 µL); the %Dev and %CV at
all the other volumes were within ±2.0% (Table 3).
Based on the mean weight of rat plasma at different
volumes, the dilution bias (%Dev) at each dilution factor
(2, 5, 10, 20, 50, 100, 200, 500, and 1000) was calculated
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218
Journal of Laboratory Automation 17(3)
Table 4. Estimated Dilution Biases (%Dev) from Automated Dilution Compared with Manual Dilution
Automated
Nominal DF (DFn)
Dilution Scheme (µL)
Actual DF (DFa)
(25 + 25)
(25 + 100)
(25 + 225)
(50 + 50)
(50 + 200)
(50 + 450)
(25 + 225) ; (50 + 50)
(25 + 225); (50 + 200)
(25 + 225); (50 + 450)
(25 + 225); (50 + 450); (50 + 50)
(25 + 225); (50 + 450); (50 + 200)
(25 + 225); (50 + 450); (50 + 450)
2
5
10
2
5
10
20
50
100
200
500
1000
Manual
%Dev*
2.0
5.0
10.1
2.0
5.0
10.1
20.1
50.6
101.1
202.2
509.0
1016.3
Actual DF (DFa)
0.0
0.2
-0.5
0.0
-0.7
-0.5
-0.5
-1.3
-1.1
-1.1
-1.8
-1.6
2.0
5.1
10.1
2.0
5.1
10.2
20.2
51.3
103.4
206.9
525.1
1058.2
%Dev*
0.0
-1.7
-1.1
0.0
-1.5
-2.2
-1.1
-2.6
-3.3
-3.3
-4.8
-5.5
*%Dev = (1/DFa - 1/DFn)/(1/DFn) ´ 100%, herein, DFn = Nominal DF, DFa = Actual DF
Table 5. Impact of Sample Volume on the Accuracy and Precision of Pipetting from Tubes
Initial
Volume in
Tube (µL)
Mean
%Deva
SD
%CV
Weight (mg) of 25 µL Plasma from BMSCustomized Tube
Weight (mg) of 25 µL Plasma from Corning Tube
50
75
100
200
50
75
100
200
24.9
25.4
25.8
25.8
25.0
25.3
25.4
-0.1
0.4
1.5
24.7
25.2
25.0
24.9
25.1
24.4
24.9
-2.0
0.3
1.2
25.2
25.0
25.7
25.4
25.5
24.9
25.3
-0.5
0.3
1.2
25.2
25.3
25.5
24.3
24.5
24.7
24.9
-1.9
0.5
1.9
25.9
25.2
25.2
25.9
25.8
25.4
25.6
0.7
0.3
1.3
25.0
25.0
25.2
24.5
25.8
25.1
25.1
-1.2
0.4
1.7
25.7
25.3
25.2
25.4
25.9
25.1
25.4
0.1
0.3
1.2
25.6
25.2
25.5
25.2
25.1
25.0
25.3
-0.5
0.2
0.9
a. The nominal value was defined as the mean weight (25.4 mg) of 25 µL rat plasma pipetted by Freedom EVO (Table 3).
from the nominal dilution factors (DFn) and the actual dilution factors (DFa), expressed as %Dev = (1/DFa – 1/DFn)/
(1/DFn) × 100% (Table 4). The estimated dilution bias
(%Dev) from the nominal value was within ±2.0% at the
dilution factors 2 to 1000. The bias was slightly increased
with the increase of the dilution steps. In contrast, manual
dilution results had greater biases at all the dilution factors.
Plasma pipetting accuracy was further demonstrated by
pipetting 25 µL of plasma from different volumes of rat
plasma in two types of sample tubes (Table 5). The %Dev
from the nominal value (defined as 25.4 mg by pipetting
25 µL of rat plasma from the 100 mL trough by the Freedom
EVO; Table 3) was within ±1.9%, and %CV was within
1.9%. The results showed that the plasma pipetting accuracy and precision were independent of the sample volume
in the tubes; that is, even 50 µL of plasma in the tubes was
sufficient for pipetting 25 µL volumes.
Accuracy and Precision of Sample Dilution
To evaluate sample dilution accuracy and precision, RSPP
prepared QCs containing BMS-650032 were diluted at
different dilution factors followed by LC-MS/MS analyses. The measured concentrations of these QCs were
obtained by back-calculating from standard curves and
multiplying by the corresponding dilution factors. The
mean %Dev of the concentrations from corresponding
nominal concentrations was within ±7.7% at different
dilution factors and concentration levels (Table 6). These
results confirm the estimation of the dilution bias from
Table 4. The results of incurred study sample reanalysis
show good reproducibility (Table 7). The %Dev of the
repeat value from the mean of the initial value and the
repeat value was within ±7.6% for samples from different
animals and collection times.
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Jiang et al.
Table 6. Accuracy and Precision of the Concentrations of BMS-650032 in Diluted Samples
Sample
Run ID
1
2
3
Dilution Factor
%CV (n = 6)
%Dev
%CV (n = 6)
%Dev
%CV (n = 6)
%Dev
5 × LLOQ QC
(25 ng/mL)
1
2
a
3.8
-1.3
3.9
-5.0
6.2
-5.0
Dilution QC
(50 000 ng/mL)
High QC (1600 ng/mL)
NA
NA
7.6
-6.7
6.4
-3.3
1
2
5
10
20
200
1.7
-0.6
3.5
3.2
2.1
1.3
NA
NA
2.2
-6.5
1.9
-5.3
2.1
-2.5
1.2
2.5
2.1
3.4
2.9
-0.5
2.8
4.0
3.6
3.7
0.9
-3.5
6.2
6.7
1.7
-1.8
1.0
-7.7
2.3
-2.3
1.6
-5.8
a. Not available.
Table 7. Reproducibility Demonstrated by the Incurred Sample Reanalysis Results
Number
Sample Identification
Initial Value
(ng/mL)
Repeat Value
(ng/mL)
Mean
(ng/mL)
Absolute % Deviation
of Values from Mean
Dilution
Factor
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Animal 1, day 1, 1 h
Animal 1, day 1, 2 h
Animal 1, day 1, 4 h
Animal 1, day 8, 4 h
Animal 1, day 8, 8 h
Animal 2, day 1, 2 h
Animal 2, day 1, 3 h
Animal 2, day 8, 1 h
Animal 2, day 8, 2 h
Animal 2, day 8, 3 h
Animal 3, day 1, 3 h
Animal 3, day 1, 4 h
Animal 3, day 1, 8 h
Animal 3, day 8, 1 h
Animal 3, day 8, 4 h
Animal 4, day 1, 1 h
Animal 4, day 1, 4 h
Animal 4, day 8, 2 h
Animal 4, day 8, 4 h
Animal 4, day 8, 8 h
13 048.47
33 599.94
52 765.33
28 205.64
24 367.19
55 760.54
72 060.16
14 083.52
24 667.09
47 847.39
15 920.19
9439.29
2681.97
13 262.83
5747.48
13 711.41
10 991.09
3569.42
1993.90
263.12
14 555.66
33 831.26
57 405.45
29 013.13
23 697.26
55 604.93
68 738.49
16 075.20
25 064.90
48 040.40
17 271.13
11 001.40
2980.12
14 438.23
5381.79
14 338.18
10 754.75
3758.36
1881.94
284.54
13 802.07
33 715.60
55 085.39
28 609.39
24 032.23
55 682.74
70 399.33
15 079.36
24 866.00
47 943.90
16 595.66
10 220.35
2831.05
13 850.53
5564.64
14 024.80
10 872.92
3663.89
1937.92
273.83
5.5
0.3
4.2
1.4
1.4
0.1
2.4
6.6
0.8
0.2
4.1
7.6
5.3
4.2
3.3
2.2
1.1
2.6
2.9
3.9
20
50
50
50
50
50
50
20
50
50
50
50
50
20
50
20
50
50
50
50
Freedom EVO System Configuration
Each carrier and labware on the worktable was well calibrated and aligned on x-, y-, and z-axis positions. The z-max
value was critical for accurately pipetting liquid from sample tubes and the wells of the 96-well plates. The liquid
detection mode was turned on in the liquid class for plasma
pipetting to check of liquid volumes. The function of “mix
after dispense” was activated to allow automatic mixing
during the sample dilution process. Disposable tips (DiTi
200 µL and DiTi 1000 µL) were used to avoid carryover and
dilution effects from fixed tips.16,17 The integrated RSPP
Freedom EVO system is not limiting and provides flexibility for using different types and dimensions of carriers and
labware; however, a set of standardized carriers and labware
is recommended to ensure reproducibility and ruggedness in
sample pipetting and dilution.
Advantages and Future Improvements
The RSPP is an interface program bridging Watson and
EVOware. Thus, automated sample pipetting and dilution
can be accomplished based on sample sequence and dilution factors from a Watson worklist. The entire process for
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220
Journal of Laboratory Automation 17(3)
192 samples, two 96-well plates, can be completed within an
hour, which saves more than 50% in sample preparation time
compared with a manual process. In addition, this automated
process provides significantly better data reproducibility.
The improved functions of EVOware at tracking and recovering the dilution process (resuming dilution process from
an unexpected stop) make the RSPP application more powerful and controllable because EVOware records each step
of liquid pipetting and is able to continue pipetting from an
unexpected stop in a run. Both the RSPP and EVOware
have been validated in house according to regulatory guidance and are being applied to the regulated nonclinical and
clinical bioanalytical sample analyses.
It should be noted that several factors may affect dilution
accuracy and precision: (1) The quality of biological samples is critical to the pipetting accuracy. For example, gellike and clotted plasma samples, and samples that may be
less homogeneous (e.g., tissue homogenates), may not be
accurately pipetted; therefore, checking the sample quality
and homogeneity before sample dilution is necessary. (2)
Appropriate integer dilution factors are recommended to
use, such as 2, 5, 10, 20, 50, 100, 200, 500, and 1000.
Dilution factors such as 11, 12. . ., 21, 22, . . ., 51, 52, . . .,
101, 102, . . ., 201, 202,. . ., 501, 502, are not recommended
because the initial sample pipetting volumes may be less
than the lowest qualified pipetting volume (25 µL), which
may cause dilution bias.
The following improvements on the RSPP will be considered in the future: (1) a Watson worklist can be transformed directly to one .gwl file without generating any
CSV worklist, because the .gwl file is the final executable
file for pipetting; (2) standards and QCs can be pipetted
from sample tubes in a rack separate from the study sample
racks to avoid rearranging samples in a sample sequence
consistent with Watson; and (3) standards or QCs can be
multipipetted from same sample tubes for preparing replicate standards and QCs in a run. These improvements
should make the process even more user-friendly, efficient,
and convenient.
This Microsoft Excel–based RSPP makes it possible to
automatically pipette and dilute samples based on the
sequence and dilution factors from a Watson worklist. This
fully automated sample dilution and preparation process
greatly saves effort and time in biological sample analysis
and provides higher quality bioanalytical data.
Declaration of Conflicting Interests
The authors declared no potential conflicts of interest with respect
to the research, authorship, and/or publication of this article.
Funding
The authors received no financial support for the research, authorship, and/or publication of this article.
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