This presentation looks at common issues encountered with DMSO-solvated compounds in HTS libraries and, current methods for identifying and tracking these issues. It also introduces applications of a novel high resolution and imaging processing instrument (HIAPI) for rapid assessment and quality control of HTS library compound library quality.

1. Addressing Quality Control Issues
in Day-to-Day HTS Compound
Management Operations
Pierre Baillargeon
HTS/Lead Identification

2. About Scripps Florida
I. Introduction to Lead Identification and Compound
Management at Scripps Florida
II. Review of issues with DMSO solvated compounds
in HTS libraries and methods for addressing these
issues
III. An introduction to the High-resolution Image
Acquisition and Processing Instrument for
Compound Management applications (HIAPI-CM)
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3. About Scripps Florida
• Started activities in 2004
• Located in Jupiter, FL
• More than 450 employees
• Screened 115 targets in over 145
primary campaigns to generate more than
35 million data points for academic &
industrial collaborators
• First drug candidate entered phase 1
clinical trials in January 2011
Phase I & II (Feb 2005-Sep 2006): 75,000 sq ft lab space
Phase III (early 2009): 350,000 sq ft lab space
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4. Drug Discovery at Scripps Florida
Discovery
Clinical Trials Biology Identify “target” for drug
discovery
In Vivo
Lead ID
Studies Identify drug-like
Prepare leads for
clinical studies “leads” for target
Translational through High
Throughput
Research Screening
Institute
Determine if
leads have drug- Improve
like properties pharmacologic
Medicinal properties of
DMPK leads
Chemistry
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5. The Lead Identification Department at Scripps
Integrated Assay Development, uHTS and Compound Management
Assay Development HTS Compound Management
• Tissue culture suite • >250,000 tests per day • >982K Screening File
• 96/384/1536 well format • 1536 well format • >622K Proprietary (largest in
supported • 1 of 6 worldwide GNF/Kalypsys academia, ~30k unique
• “From test tube to plate” platforms compounds, focused sub-
• Protein expression/purification • All major HTS screening formats libraries, professionally curated)
supported • >360K Public Domain (NIH)
• Integrated Compound QC (LC-MS, HIAPI-CM)
>$20MM Investment by Scripps Florida
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6. Compound Management Systems
• “Working copies” of all HTS
screening samples are
available for quick cherry
picking and reformatting.
• CM Automation integrates
proven hardware solutions
with customized software to
improve process efficiency.
• Equipment and procedures
optimized for rapid
response. Automation is
closely integrated with
software, ensuring timely
delivery of samples and
minimizing waste.
Photo by Tom Arban
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7. Issues With Compound Libraries
I. Introduction to Lead Identification and Compound
Management at Scripps Florida
II. Review of issues with DMSO solvated compounds
in HTS libraries and methods for addressing these
issues
III. An introduction to the High-resolution Image
Acquisition and Processing Instrument for
Compound Management applications (HIAPI-CM)
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8. Compound Management Responsibilities & Customers
What role does CM play at
HTS
Scripps?
• HTS Library Procurement
• HTS Library Stewardship
• HTS Library QC (via LC-MS) Medicinal
Chemistry
DMPK &
Pharm
• Cherry pick for HTS Core
• Compound re-synthesis &
restock
Compound
• Receive & reformat samples Management
from external collaborators
• Ship samples to external
collaborators Compound External
• Medicinal Chemistry support Vendors Collaborator
Therapeutic
Areas
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9. Compound Management Responsibilities & Customers
What operational challenges are
HTS
encountered during these
interactions?
• Quality of external samples &
sample data Medicinal DMPK &
Chemistry Pharm
• Degradation of samples over
time
• Enforcing internal QA/QC
standards Compound
Management
• Tracking sample properties &
genealogy in a way that can
be easily audited in the
future Compound External
Vendors Collaborator
• Managing large sample
libraries which are constantly
in flux (multiple
copies, samples becoming Therapeutic
Areas
depleted, new
acquisitions, etc.)
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10. Compound Management Responsibilities & Customers
What operational challenges are How do we currently address
encountered during these these issues and what are the
interactions? limitations?
• Quality of external samples &
sample data • LC-MS (time consuming)
• Degradation of samples over
time
• Enforcing internal QA/QC • Acoustic auditing (time
standards consuming, labware
• Tracking sample properties & dependent)
genealogy in a way that can
be easily audited in the • Manual visual inspection (time
future consuming, subjective)
• Managing large sample
libraries which are constantly
in flux (multiple
copies, samples becoming
depleted, new
acquisitions, etc.)
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11. Opportunities For Error
COMPOUND SUBMISSION
• Has the correct sample been put into the labware?
• Is the volume and concentration of the sample accurately recorded?
COMPOUND PROCESSING
• Has the sample store delivered the correct samples?
• Has the liquid handling automation pipetted the samples properly?
• Has the plate been registered correctly?
COMPOUND DELIVERY
• Do we have a record of what we are delivering?
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12. Introduction to HIAPI-CM
I. Introduction to Lead Identification and Compound
Management at Scripps Florida
II. Review of issues with DMSO solvated compounds
in HTS libraries and methods for addressing these
issues
III. An introduction to the High-resolution Image
Acquisition and Processing Instrument for
Compound Management applications (HIAPI-CM)
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13. Why Do We Need HIAPI-CM?
Are empty/partially filled Do these wells
wells in Quadrant 1? contain precipitate?
The contents
of a plate are
a fingerprint
for all of the
potential
problems you
encounter in
a CM
operation!
My db says
this well is
empty. Does
it actually
have sample
in it?
My HTS detection format is sensitive to Are these wells partially
purple compounds. Where are they? filled?
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14. HIAPI-CM Applications & Features
• Instant detection of errors from compound reformatting
• Detect missed/partially filled wells, quadrant effects
• “Pre-screen” compound plates for HTS assay interferents
• Detect colored compounds, suspended materials
• Identify database entry errors in corporate LIMS db
• Determine which full/empty wells in plate differ from the full/empty well
assignments in corporate db
• Periodic check-ups on the “health” of stored compounds
• Detect ppt. formation, evaporation
• Quantitative detection of compound solubility
• Useful for medicinal chemistry synthesis operations, DMPK experiments
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15. What is HIAPI-CM?
• A custom HTS plate reader, incorporating
recent advances in machine vision, image
analysis, & the spectroscopy sciences
• It saves labor by automatically identifying
& annotating issues specific to compound
libraries:
• Colored compounds
• Precipitate / Crystallization
• Low volume / Full wells
• It can be used in “stand-alone” mode, or
integrated with automation
• Works with microtiter plates
• Fast: reads a 384 well plate in <1 minute
• All measurements are non-contact
• User-friendly, intuitive analysis software
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16. HIAPI-CM Features: Instrument Design
• Completely automated
& intuitive to operate
• Classification Results
shown in real-time
• Simple interface only
requires user to select
plate type to perform
analysis
• Analysis results
exported as text file or
compared to existing
records in corporate
LIMS database
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17. HIAPI-CM Features: Plate Gallery
HIAPI-CM Plate Gallery provides an easy to navigate interface to
edit, export or browse analysis results
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18. HIAPI-CM Features: Plate Gallery
From the Plate Gallery, a user can click on a plate to load the Plate Detail
View. The user can inspect different artifact analysis results or overwrite
classifications made by HIAPI-CM.
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19. HIAPI-CM Features: Color Recognition & Classification
• HIAPI-CM detects and classifies colored
Before Processing
compounds
• HIAPI-CM currently recognizes and classifies the
“standard” colors listed below:
Limit of
Color
Dye Used Detection
Detected
(uM)
Red Allura Red 35.1
Green Brilliant Green 9.0
Blue Euroglaucine 0.6
After Processing
Yellow Tartrazine 12.7
Violet Gentian violet 1.3
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20. HIAPI-CM Features: Precipitate Detection
Compound plates contain precipitates which are masked by colors in the
wells:
HIAPI-CM Precipitate analysis is:
• Insensitive to color
• Able to detect ppt. beyond “naked eye” inspection
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21. HIAPI-CM Feature: Low Volume Detection
What can cause a well
to have a low volume?
• Incorrectly reported
volume in LIMS
• Oversampled by
cherry picking
operations
• Evaporation
• Liquid handling
errors (clogged
tips, samples
transferred to
40uL 20uL 10uL 8uL 4uL 2uL 1uL
incorrect
wells/quadrants, etc
.)
HIAPI-CM distinguishes normal wells (“full”) from empty/partially filled
wells (“low volume”) - low volume designation dependent on plate type
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22. HIAPI-CM Features: LIMS/Corporate Database Auditing
RESULTS OF COMPOUND PLATE QUERY
IN CORPORATE DATABASE:
• Scripps database (MDL Symyx/Plate Manager)
displays several wells as empty (white
rectangles in figure on left)
RESULTS OF THE SAME COMPOUND
PLATE QUERY IN HIAPI-CM DATABASE:
• HIAPI-CM compares instrument results to
corporate db records
• HIAPI-CM identifies discrepancies with
corporate db (red “x’s” in figure on left):
• Colored compounds (upper left)
• Full wells that corporate db assigns as “empty”
HIAPI-CM CAN BE USED TO AUDIT/UPDATE CORPORATE DB RECORDS
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23. Opportunities For Error
What new information do we obtain with HIAPI-CM in the process?
• We know which wells have been filled and which have low volume
• We know which wells contain colored samples
• We know which wells have precipitated
What can we do with this information?
• Compare filled & low volume wells against LIMS to verify proper liquid handling & plate
registration
• Compare „color fingerprint‟ of samples against database of known samples to identify issues
with incorrect concentration & samples
• Take measures to put precipitated samples back into solution (sonication, heating, etc.)
• Keep a historical record of the health of the plate at the point when it was delivered (a
receipt of transaction)
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24. Why do we need HIAPI-CM?
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25. Why do we need HIAPI-CM?
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26. Practical Examples: HIAPI-CM 384 Well Plate Timing
To visually inspect three 384 well In the same amount of
plates: time, HIAPI-CM can automatically
Plate #1 – 3 minutes 12 seconds inspect fifteen 384 well plates!
Plate #2 – 1 minute 46 seconds
Plate #3 – 1 minute 40 seconds
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27. Practical Examples: HTS Library Analysis
To date, Scripps has run over This includes Scripps Florida‟s
1,000 plates through HIAPI-CM internal 622k Drug Discovery
resulting in over 1,000,000 wells library and the NIH‟s Molecular
which have been analyzed for Libraries-Small Molecule
color, precipitate and low volume Repository (MLSMR) 362k library.
artifacts.
How can we leverage all of this new data to improve our workflow?
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28. Practical Examples: Color Analysis
HIAPI-CM data can be used to monitor consistency of sample color over time…
A sample provided by an external source in 2009 vs. the
same sample provided by the same source in 2011.
With HIAPI-CM, we can
automatically query and
identify inconsistencies
across entire compound
collections.
Is this the same sample? Is the concentration recorded
correctly?
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29. Practical Examples: Color Analysis
Running color comparison
reveals color inconsistencies…
Two copies of plate prepared by external vendor reveal inconsistencies
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30. Practical Examples: LIMS Comparison
Finds plates which have not been properly registered in corporate LIMS db…
… in this case, LIMS record had odd barcode for plate instead of even barcode.
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31. Practical Examples: LIMS Comparison
When checking reformatted plates, CM team noticed high # of LIMS disagreement wells…
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32. Practical Examples: LIMS Comparison
When checking reformatted plates, CM team noticed high # of LIMS disagreement wells…
… examining the plate detail view reveals a pattern in quadrant 1…
… checking the LIMS record reveals samples in quadrant 1 are not registered …
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33. Practical Examples: LIMS Comparison
… CM team updates LIMS record and runs plate through HIAPI-
CM to confirm the corrected LIMS record matches the physical
locations of samples within the plate.
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34. Practical Examples: LIMS Comparison
HIAPI-CM Raw HIAPI-CM Raw Image LIMS Record
Image vs. LIMS Record
Comparison
Plate arrived from external vendor with empty wells backfilled with
DMSO, but accompanying data file showed them as empty. HIAPI-CM was
able to identify this discrepancy.
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35. Practical Examples: Precipitate Analysis
“Normal” screening plate Precipitate filled screening plate
HIAPI-CM automatically identifies plates with high levels of precipitate
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36. Practical Examples: Precipitate Analysis
“Normal” screening plate Precipitate filled screening plate
HIAPI-CM automatically identifies plates with high levels of precipitate
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37. Practical Examples: Precipitate Analysis
A
HIAPI-CM helps to identify solubility
issues when analyzing samples from
sublibraries …
% of library
Library containing
precipitate B
Sublibrary A 0.1%
Sublibrary B 2.5%
Sublibrary C 0.8%
… providing a useful dataset when
communicating problems with
suppliers, collaborators and CM staff
internally.
C
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38. Compound Management Responsibilities & Customers
What operational challenges are
HTS
encountered during these
interactions?
• Quality of external samples &
sample data Medicinal DMPK &
Chemistry Pharm
• Degradation of samples over
time
• Enforcing internal QA/QC
standards Compound
Management
• Tracking sample properties &
genealogy in a way that can
be easily audited in the
future Compound External
Vendors Collaborator
• Managing large sample
libraries which are constantly
in flux (multiple
copies, samples becoming Therapeutic
Areas
depleted, new
acquisitions, etc.)
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39. Compound Management Responsibilities & Customers
What operational challenges are
encountered during these • HIAPI-CM enables external
interactions? samples to be quickly QC‟d
• Quality of external samples & and compared against sample
sample data data upon arrival
• Degradation of samples over • HIAPI-CM enables monitoring
time of compound library health
• Enforcing internal QA/QC over time
standards • HIAPI-CM allows CM staff to
• Tracking sample properties & enforce QA/QC business rules
genealogy in a way that can by alerting them to problems
be easily audited in the • HIAPI-CM creates a snapshot
future of a plate in time and allows
• Managing large sample users to track samples over
libraries which are constantly time
in flux (multiple • HIAPI-CM makes QC of large
copies, samples becoming libraries more manageable by
depleted, new automating time intensive
acquisitions, etc.) visual inspections
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40. HIAPI-CM Summary
• CM staff is able to proactively capture
and address problems early on and
prevent them from propagating
downstream. HIAPI-CM allows CM staff to
capture errors in real-time.
• Time saved from not having to visually
inspect plates allows CM staff to spend
more time on other important tasks.
• Color detection helps better understand
source of HTS data artifacts and allows
us to track compound plating fidelity
over time.
• Analysis of HIAPI-CM data can reveal
interesting trends. Do plates from one
vendor have more artifacts (precipitate?)
than another?
Additional information, including HIAPI-CM Pilot Screen results, can be found in “Monitoring of
HTS compound library quality via a high-resolution image acquisition and processing
instrument”. Baillargeon P, Scampavia L, Einsteder R, Hodder P. J Lab Automation, June 2011
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41. One Final Thought…
“We now have the technical ability to get
the wrong answers with unprecedented
speed. If you put the wrong stuff into the
front end of our analytical pipeline, we
will not only lose the war on cancer, we’ll
pollute the scientific literature with
incorrect data that will take us a long time
to sort out. This is a crisis that requires
disruptive innovation.”
Carolyn Compton – Director, Office of
Biorepositories and Biospecimen
Research at National Cancer Institute
Wired Magazine article on
Biobanking, May 2010
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42. Acknowledgements
Scripps Florida
Funding Corporation
http://hts.florida.scripps.edu bpierre@scripps.edu
Lead Identification:
Peter Hodder
Pierre Baillargeon
Peter Chase
Joseph Datsko
Christina Eberhart
Imarhia Enogieru
Ross Einsteder
Katharine Emery
Virneliz Fernandez-Vega
Lina DeLuca
Franck Madoux
Becky Mercer
Christine Pinello
Louis Scampavia
Timothy Spicer
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