steven van helden - fhi · 1 building an efficient automated screening facility dr. steven van...
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Building an efficient automated screening facility
Dr. Steven van Helden
Life Sciences Park Oss
Eindhoven, 3 april 2012
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Outline
►Introduction Discovery & Screening►The process►Users
►Flexibility►Benchmarking
►Conclusion
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Declining Output of New Molecular Entities
0
50
100
150
200
250
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007*
Year
Inde
xed
to 1
997
R&D expenditure Development times NME output Sales
2008 © Thomson Reuters.
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In Vitro Testing in R&D
Compoundcollection
HTS
AssaysChemistry
HitOptimization
HitsBiology
LeadOptimization
TargetID
HTSHit
OptimisationLead
OptimisationDevelopmentCandidate
DevelopmentProcess
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Scale of in-vitro screening
LibrariesHO HTS
Plates1000
1
10
100
AD LOHO
A utomation inS creening and
P harmacologyI ntegration of the
R esearch E nvironment
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Automation: Screening Islands
“HTS”
“Plate Prep” “Reader”
“Stand-alone”
• Flexible• Modular• Scalable• User-friendly• Proven Technology
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The Result: 6 Islands in a Lab
2 screening islands
Fully automated assays
2 reader islandsParts of assays, dispensing
2 plate preparation islandsPrepare plates, serial dilutions
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Outline
►Introduction Discovery & Screening►The process►Users
►Flexibility►Benchmarking
►Conclusion
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Our Process
►Collect ideas►Write User Requirement Specification (URS)►Call for proposals
►Select vendor►Write Functional Design Specification (FDS)
►Implement project
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User Requirement Specification
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Our Process
►Collect ideas►Write User Requirement Specification (URS)►Call for proposals
►Select vendor►Write Functional Design Specification (FDS)
►Implement project
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Docking Units – Think about Custom Design
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Outline
►Introduction Discovery & Screening►The process►Users
►Flexibility►Benchmarking
►Conclusion
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Involve Users
►Involve users throughout project►Listen to user
� It is not what they say, but what they do not say…
►Automate the new situation►Quality Awareness
►Support in the lab� Dedicated people
� Not a job for IT departmentDev iat ion of volum e per well , com pared t o average volum e of plate >5% < -5%
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23A -1.3% -0. 2% -0. 1% -1.0% -1. 4% -0. 4% -0.4% -1.2% -0. 1% 0. 9% -0.4% -1. 3% -1. 9% -1.2% -1. 6% -0. 1% -2.2% -2.1% -0. 3% -1. 0% 0.7% -0. 8% -2. 2%B 1.6% -1. 6% -0. 8% 0.7% -1. 6% -3. 3% 0.0% -2.3% -1. 4% -0. 8% -1.5% 0. 7% 0. 3% 1.3% -0. 1% 0. 0% -0.4% 0.5% -0. 5% -0. 9% -2.4% -1. 2% -1. 0%C 2.2% -0. 6% 0. 1% -0.9% 0. 1% -0. 1% 1.1% -1.3% 0. 3% -1. 1% 0.9% 0. 3% -0. 8% 1.7% 1. 6% 1. 8% -0.3% 0.9% 0. 0% 0. 4% 0.1% 0. 6% -1. 0%D 2.3% 0. 7% 0. 5% 0.6% 1. 4% -0. 2% 0.8% -1.1% 0. 9% 0. 8% 0.9% -0. 2% 0. 1% 1.7% 1. 1% 1. 8% -1.0% 2.3% 0. 3% 0. 6% -1.1% 1. 3% 0. 1%E 3.8% 0. 9% 0. 9% -2.5% 1. 7% -1. 4% -0.4% 2.4% -0. 2% 0. 0% 2.2% 1.8% 1. 0% 1.8% 0. 6% 1. 4% 0.1% -1.9% 0. 9% 1. 0% -0.1% 0. 6% -0. 8%F 1.7% -1. 0% 0. 1% 0.5% 0. 7% 0. 4% -0.3% -0.9% 0. 4% 0. 1% 2.3% 0. 0% 1. 7% 1.3% 1. 5% 0. 4% 1.3% -0.4% 0. 0% 1. 5% 1.0% 0. 5% 0. 0%G 2.8% 1. 1% -1. 3% -3.0% -0. 3% -1. 5% -0.8% -2.0% -1. 1% -2. 4% -0.8% -2. 0% -4. 4% -0.9% -1. 0% -1. 0% -12.7% -6.0% -2. 1% -0. 4% -2.3% -2. 1% -1. 8%H -4.8% -5. 0% -3. 9% -4.4% -4. 2% -5. 3% -4.7% -4.8% -3. 7% -3. 8% -4.3% -3. 8% -2. 8% -3.1% -3. 2% -2. 8% -4.8% -2.5% -3. 5% -3. 4% -4.5% -3. 8% -3. 0%I 2.6% 1. 0% 1. 0% 0.9% 1. 9% 1. 5% 2.2% 1.3% 1. 9% 4. 4% 2.4% 1. 3% 1.6% 1.7% 1. 5% 1. 8% 0.9% 1.5% 0. 9% 1. 0% 0.8% 1. 4% 0. 0%J 0.3% 0. 1% 1. 1% 1.5% 1. 4% 1. 8% 2.6% 1.8% 2. 9% 2. 0% 2.0% 2. 2% 1.8% 1.9% 1. 8% 2. 2% 0.7% 1.1% 0. 9% 0. 8% 0.9% 0. 4% -0. 5%K 0.6% -3. 3% 1. 1% -1.4% -3. 8% -1. 0% -1.2% -1.8% -0. 9% -1. 3% -3.2% -1. 4% -0. 1% -1.0% -1. 2% -0. 6% -1.9% -0.6% -1. 0% -1. 2% -1.3% -0. 9% -1. 6%L -1.5% -1. 8% -0. 9% -0.9% -1. 1% -1. 3% -1.1% -0.5% -0. 4% -0. 3% 0.0% -0. 4% -0. 2% 0.6% 0. 5% 0. 9% -0.6% -0.6% -0. 6% -1. 2% -0.9% -1. 1% -1. 2%M 1.6% 0. 3% -3. 4% 1.1% -0. 4% 0. 4% 0.9% 0.7% 0. 7% 0. 8% 1.0% 0. 7% 0. 6% 1.0% 0. 7% 1. 6% 1.1% 0.9% 0. 3% 0. 6% 0.6% 0. 7% 0. 0%N 0.4% 0. 8% 0. 7% 1.0% 1. 1% 0. 9% 0.9% 1.0% 1. 6% 1. 5% 1.3% 0. 8% 1.3% 1.0% 1. 7% 1. 4% 1.6% 0.5% 2. 2% 1. 1% 1.0% 1. 0% 0. 7%O -0.1% 1. 0% 2. 0% -0.8% 2. 4% 1. 8% 1.4% 1.3% 1. 1% 1. 3% 1.7% 1. 3% 1. 0% 2.2% 1. 3% 2. 2% 1.1% 1.4% 1. 5% 1. 5% 0.8% 1. 0% 0. 5%P 1.5% 0. 4% -0. 2% 1.0% 0. 3% 0. 5% 0.7% 1.5% 1. 3% 1. 9% 1.9% 2. 4% 3. 0% 2.5% 2. 9% 2. 8% 2.4% 1.9% 1. 9% 1. 9% 0.9% 0. 9% 0. 7%
Deviati on of vol ume per well, compared to average volume of plate >5% < -5%1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
A 6.7% -9.2% 11.4% -2.3% 0.7% 1.5% -6.0% 5.1% -3.6% -0.7% 3.7% -8.7% 6.9% -2.9% -2.5% 4.8% -9.2% 6.4% -1.8% -4.0% 5.5% -5.9% -1.4%B 7.3% -9.3% 11.3% -0.8% -3.3% 3.9% -8.1% 8.1% -2.3% -1.5% 4.4% -11.1% 7.7% -1.2% -3.8% 6.7% -9.3% 7.6% -0.7% -4.8% 5.5% -6.6% -1.3%C 4.6% -7.2% 6.9% 4.7% -5.4% 5.6% -8.2% 5.1% 0.1% -4.4% 6.7% -9.9% 6.6% -0.1% -4.8% 7.4% -11.8% 5.7% 1.4% -4.8% 5.6% -7.3% -2.2%D 7.0% -7.8% 7.9% 0.0% -1.9% 2.4% -6.4% 3.8% -2.8% -1.1% 2.7% -9.3% 4.6% -1.4% -1.8% 2.7% -8.7% 5.2% -0.7% -4.4% 3.2% -5.4% -3.5%E 8.2% -7.1% 7.8% 1.6% -3.4% 4.8% -6.7% 5.6% -0.6% -2.2% 4.8% -7.8% 5.2% 0.4% -2.3% 4.5% -7.5% 4.1% 1.2% -4.0% 4.4% -5.0% -1.9%F 5.9% -6.5% 7.9% -1.4% 2.2% -1.8% -6.0% 3.1% -2.5% 1.2% 2.0% -7.4% 6.2% -3.4% -1.0% 0.8% -4.9% 3.4% -1.2% -3.0% 2.3% -4.1% -2.9%G 7.0% -6.3% 6.6% 3.4% -6.6% 6.8% -7.7% 4.7% 0.9% -4.9% 5.4% -8.1% 4.0% 2.4% -4.0% 4.8% -8.2% 2.9% 2.0% -3.8% 4.5% -6.0% -1.8%H 5.5% -3.6% 6.6% 1.1% 0.3% 0.0% -3.6% 3.2% -1.3% 1.1% 1.4% -4.5% 3.7% -0.6% 0.2% 1.0% -3.6% 3.6% 0.0% -1.8% 2.0% -2.6% -2.5%I 7.1% -4.4% 5.3% 3.9% -3.6% 4.9% -4.7% 2.9% 1.9% -2.9% 3.4% -3.7% 2.5% 3.1% -1.9% 2.7% -4.8% 2.5% 3.0% -3.0% 3.3% -3.6% -2.2%J 5.1% -2.9% 0.9% 1.6% 0.8% -2.6% -1.4% 0.7% -0.3% 6.0% -0.5% -2.2% 1.9% -1.8% 2.5% -1.8% -1.3% 2.4% -0.3% -0.6% -0.3% -0.7% -3.3%K 5.3% -3.5% 3.7% 6.2% -6.9% 6.6% -4.7% 0.8% 3.8% -4.3% 3.8% -4.0% -1.1% 4.7% -0.7% 1.5% -3.0% 0.3% 4.0% -3.3% 1.4% -1.7% -3.2%L 4.5% -1.9% 2.4% 3.4% -1.4% 0.0% -0.8% 0.7% 1.1% 0.2% 0.7% -1.2% 0.7% 1.0% 1.7% -1.1% -0.4% 0.3% 1.8% -0.6% 1.4% -1.9% -3.8%M 2.5% -3.6% 3.1% 3.8% -3.0% 2.6% -1.8% -0.8% 3.1% -2.1% 0.2% -1.4% -1.1% 2.9% -0.4% -0.1% -1.5% 0.0% 2.4% -2.5% 1.6% -2.2% -4.4%N 0.3% 0.8% 0.0% 3.1% 1.5% -2.3% 1.0% -1.7% 2.3% 0.5% -1.3% 1.4% -0.4% 2.7% 2.9% -3.5% 2.7% -0.3% 1.4% 0.5% 0.3% -0.5% -2.7%O 1.6% -0.5% -0.6% 5.6% -1.1% 0.3% 0.8% -3.3% 2.4% 0.0% -0.6% 0.0% -2.9% 2.9% 0.0% -2.1% 0.5% -1.0% 1.8% -1.1% 0.0% -1.4% -5.0%P 1.9% -1.9% -1.2% 8.1% -5.4% 2.3% 1.0% -4.1% 5.6% -1.9% 1.6% 0.4% -3.6% 5.5% 0.9% -0.8% 0.8% -1.2% 4.0% 0.0% 0.8% -0.8% -3.5%
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Outline
►Introduction Discovery & Screening►The process►Users
►Flexibility►Benchmarking
►Conclusion
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Docking Concept
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Docking Concept
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Standardization
►Quality of data� Consistency of data
� Interpretation of data
� Cross project/site comparison
� Automated quality control procedures
►Efficiency of process� Maintenance of methods in the (automated) lab
� Maintenance of data processing tools and corporate databases
� Less training required
Conc-10 -8 -6
Ef f ect
-20
-10
0
10
20
30
40
50
60
70
80
90
100
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Ultimate Flexibility: Change of Company
►Open Access Screening Facility
►High Throughput Screening (100K compounds)
► In-vitro testing
►Pharma, Agro, Food, …
►Chemicals & Biologicals
► “Closed” Pharma Research Facility
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Outline
►Introduction Discovery & Screening►The process►Users
►Flexibility►Benchmarking
►Conclusion
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Benchmarking
Introduction ASPIRE
Q4 2009 not included
►Output
►Quality
►Cost
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Conclusion
Successful lab automation depends on
people, the process and your organisation,
not just on robots
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Acknowledgement
►The ASPIRE team in Oss and Newhouse� J.vd Broek, JW Boiten, C. Kuil, W. Kuijpers
� J.Connick, S.Komesli, G. McVey, J.Roberts, A.Pate
►The specialists in Oss� H. Jansen, G.Rovers, R.Geurts, W.Kop
►The experienced users in Oss� M.v Amstel, S. Ruygrok, M. Timmerman, A. v Driel, T. Lam, S. Lobregt,
►All users in Oss►The Beckman Coulter team