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Robotic Implementation of Assays: Tissue-Nonspecific Alkaline Phosphatase (TNAP) Case Study

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Phosphatase Modulators

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1053))

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Abstract

Laboratory automation and robotics have “industrialized” the execution and completion of large-scale, enabling high-capacity and high-throughput (100 K–1 MM/day) screening (HTS) campaigns of large “libraries” of compounds (>200 K–2 MM) to complete in a few days or weeks. Critical to the success these HTS campaigns is the ability of a competent assay development team to convert a validated research-grade laboratory “benchtop” assay suitable for manual or semi-automated operations on a few hundreds of compounds into a robust miniaturized (384- or 1,536-well format), well-engineered, scalable, industrialized assay that can be seamlessly implemented on a fully automated, fully integrated robotic screening platform for cost-effective screening of hundreds of thousands of compounds. Here, we provide a review of the theoretical guiding principles and practical considerations necessary to reduce often complex research biology into a “lean manufacturing” engineering endeavor comprising adaption, automation, and implementation of HTS. Furthermore we provide a detailed example specifically for a cell-free in vitro biochemical, enzymatic phosphatase assay for tissue-nonspecific alkaline phosphatase that illustrates these principles and considerations.

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References

  1. Macarron R, Banks MN, Bojanic D et al (2011) Impact of high-throughput screening in biomedical research. Nat Rev Drug Discov 10:188–195

    Article  PubMed  CAS  Google Scholar 

  2. Houston JG, Banks MN, Binnie A et al (2008) Case study: impact of technology investment on lead discovery at Bristol-Myers Squibb, 1998-2006. Drug Discov Today 13:44–51

    Article  PubMed  Google Scholar 

  3. Houston JG, Banks M (1997) The chemical-biological interface: developments in automated and miniaturised screening technology. Curr Opin Biotechnol 8:734–740

    Article  PubMed  CAS  Google Scholar 

  4. Macarrón R, Hertzberg R (2011) Design and implementation of high throughput screening assays. Mol Biotechnol 47:270–285

    Article  PubMed  Google Scholar 

  5. Roy A, McDonald PR, Sittampalam S et al (2010) Open access high throughput drug discovery in the public domain: a Mount Everest in the making. Curr Pharm Biotechnol 11: 764–778

    Article  PubMed  CAS  Google Scholar 

  6. Silverman L, Campbell R, Broach JR (1998) New assay technologies for high-throughput screening. Curr Opin Chem Biol 2:397–403

    Article  PubMed  CAS  Google Scholar 

  7. Banks MN, Cacace AM, O’Connell J, Houston JG (2005) High-throughput screening: evolution of technology and methods. In: Gad WC (ed) Drug discovery handbook. John Wiley & Sons 559–602

    Google Scholar 

  8. Burbaum JJ, Sigal NH (1997) New technologies for high-throughput screening. Curr Opin Chem Biol 1:72–78

    Article  PubMed  CAS  Google Scholar 

  9. Comley JCW, Binnie A, Bonk C et al (1997) A 384-HTS for human factor VIIa: comparison with 96- and 864-well formats. J Biomol Screen 2:171–178

    Article  CAS  Google Scholar 

  10. Rogers MV (1997) Light on high-throughput screening: fluorescence-based assay technologies. Drug Discov Today 2:156–160

    Article  CAS  Google Scholar 

  11. Sittampalam GS, Kahl SD, Janzen WP (1997) High-throughput screening: advances in assay technologies. Curr Opin Chem Biol 1:384–391

    Article  PubMed  CAS  Google Scholar 

  12. Hertzberg RP, Pope AJ (2000) High-throughput screening: new technology for the 21st century. Curr Opin Chem Biol 4:445–451

    Article  PubMed  CAS  Google Scholar 

  13. Entzeroth M, Flotow H, Condron P (2009) Overview of high-throughput screening. Curr Protoc Pharmacol Chapter 9, Unit 9 4

    Google Scholar 

  14. Eglen RM, Singh R (2003) Beta galactosidase enzyme fragment complementation as a novel technology for high throughput screening. Comb Chem High Throughput Screen 6:381–387

    Article  PubMed  CAS  Google Scholar 

  15. Fan F, Wood KV (2007) Bioluminescent assays for high-throughput screening. Assay Drug Dev Technol 5:127–136

    Article  PubMed  CAS  Google Scholar 

  16. Ormand J, Bruner J, Birkemo L et al (2000) A centralized global automation group in a decentralized organization. J Autom Methods Manag Chem 22:195–198

    Article  PubMed  CAS  Google Scholar 

  17. Fox S (2006) High-throughput screening: update on practices and success. J Biomol Screen 11:864–869

    Article  PubMed  Google Scholar 

  18. Hamilton SD (1991) Managing an automation development group. J Autom Chem 13:23–27

    Article  CAS  Google Scholar 

  19. Janzen WP, Popa-Burke IG (2009) Review: advances in improving the quality and flexibility of compound management. J Biomol Screen 14:444–451

    Article  PubMed  CAS  Google Scholar 

  20. Matson SL, Chatterjee M, Stock DA et al (2009) Best practices in compound management for preserving compound integrity and accurately providing samples for assays. J Biomol Screen 14:476–484

    Article  PubMed  CAS  Google Scholar 

  21. Radu C, Adrar HS, Alamir A et al (2012) Designs and concept reliance of a fully automated high-content screening platform. J Lab Autom 17:359–369

    PubMed  Google Scholar 

  22. Cuatrecasas P (2006) Drug discovery in jeopardy. J Clin Invest 116:2837–2842

    Article  PubMed  CAS  Google Scholar 

  23. Frantz S (2007) Pharma faces major challenges after a year of failures and heated battles. Nat Rev Drug Discov 6:5–7

    Article  PubMed  CAS  Google Scholar 

  24. Gribbon P, Andreas S (2005) High-throughput drug discovery: what can we expect from HTS? Drug Discov Today 10:17–22

    Article  PubMed  Google Scholar 

  25. Macarron R (2006) Critical review of the role of HTS in drug discovery. Drug Discov Today 11:277–279

    Article  PubMed  Google Scholar 

  26. Williams K, Scott JE (2009) Enzyme assay design for high-throughput screening. In: Janzen WP, Bernasconi P (eds) High throughput screening. Methods Mol Biol 565: 107–126

    Google Scholar 

  27. Inglese J, Johnson RL, Simeonov A et al (2007) High-throughput screening assays for the identification of chemical probes. Nat Chem Biol 3:466–479

    Article  PubMed  CAS  Google Scholar 

  28. Frearson JA, Collie IT (2009) HTS and hit finding in academia—from chemical genomics to drug discovery. Drug Discov Today 14:1150–1158

    Article  PubMed  Google Scholar 

  29. Baker M (2010) Academic screening goes high-throughput. Nat Methods 7:787–792

    Article  CAS  Google Scholar 

  30. Devanarayan V, Sawyer BD, Montrose C et al (2012) Glossary of quantitative biology terms. http://www.ncbi.nlm.nih.gov/books/NBK92002/ In: Sittampalam GS, Gal-Edd N, Arkin M et al (eds) Assay guidance manual. Bethesda (MD): Eli Lilly & Company and the National Center for Advancing Translational Sciences. http://www.ncbi.nlm.nih.gov/books/NBK53196/

  31. Houston JG (1999) HTS: productivity or oblivion? J Biomol Screen 4:229–230

    Article  PubMed  Google Scholar 

  32. Sills MA (1997) Integrated robotics vs task-oriented automation. J Biomol Screen 2:137–138

    Article  Google Scholar 

  33. SLAS (2004) http://www.thefreelibrary.com/ANSI Approves Microplate Standards Drafted by SBS Committee; New...-a0112221338

  34. Millán J (2006) Alkaline phosphatases. Purinergic Signal 2:335–341

    Article  PubMed  Google Scholar 

  35. Sergienko EA, Millan JL (2010) High-throughput screening of tissue-nonspecific alkaline phosphatase for identification of effectors with diverse modes of action. Nat Protoc 5:1431–1439

    Article  PubMed  CAS  Google Scholar 

  36. Sergienko E, Su Y, Chan X et al (2009) Identification and characterization of novel tissue-nonspecific alkaline phosphatase inhibitors with diverse modes of action. J Biomol Screen 14:824–837

    Article  PubMed  CAS  Google Scholar 

  37. Wu J (2002) Comparison of SPA, FRET, and FP for kinase assays. In: Janzen W (ed) High throughput screening. Humana, pp 65–85

    Google Scholar 

  38. Zhang JH, Chung TD, Oldenburg KR (1999) A simple statistical parameter for use in evaluation and validation of high throughput screening assays. J Biomol Screen 4:67–73

    Article  PubMed  Google Scholar 

  39. Gupta S, Indelicato SR, Jethwa V et al (2007) Recommendations for the design, optimization, and qualification of cell-based assays used for the detection of neutralizing antibody responses elicited to biological therapeutics. J Immunol Methods 321:1–18

    Article  PubMed  CAS  Google Scholar 

  40. Smith T, Ho P-i, Yue K, Itkin Z, MacDougall D, Paolucci M, Hill A, Auld DS (2013) Comparison of compound administration methods in biochemical assays: effects on apparent compound potency using either assay-ready compound plates or pin tool-delivered compounds. J Biomol Screen 18:14–25

    Google Scholar 

  41. Ryan AJ, Gray NM, Lowe PN et al (2003) Effect of detergent on “promiscuous” inhibitors. J Med Chem 46:3448–3451

    Article  PubMed  CAS  Google Scholar 

  42. Knowles J, Gromo G (2003) Target selection in drug discovery. Nat Rev Drug Discov 2:63–69

    Article  PubMed  CAS  Google Scholar 

  43. McGovern SL, Helfand BT, Feng B et al (2003) A specific mechanism of nonspecific inhibition. J Med Chem 46:4265–4272

    Article  PubMed  CAS  Google Scholar 

  44. Feng BY, Shelat A, Doman TN et al (2005) High-throughput assays for promiscuous inhibitors. Nat Chem Biol 1:146–148

    Article  PubMed  CAS  Google Scholar 

  45. Feng BY (2007) A high-throughput screen for aggregation-based inhibition in a large compound library. J Med Chem 50:2385–2390

    Article  PubMed  CAS  Google Scholar 

  46. Sundberg SA (2000) High-throughput and ultra-high-throughput screening: solution- and cell-based approaches. Curr Opin Biotechnol 11:47–53

    Article  PubMed  CAS  Google Scholar 

  47. Smith C (2011) Cell-based kinase assays: many routes to the same information. Biocompare http://www.biocompare.com/Editorial-Articles/41838-Cell-based-Kinase-Assays-Many-Routes-to-the-Same-Information/

  48. Iversen PW, Eastwood BJ, Sittampalam GS et al (2006) A comparison of assay performance measures in screening assays: signal window, Z′ factor, and assay variability ratio. J Biomol Screen 11:247–252

    Article  PubMed  CAS  Google Scholar 

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Acknowledgments

This work was supported by the NIH Roadmap Molecular Libraries Program Grant U54 HG005033 and the Conrad Prebys Center for Chemical Genomics at the Sanford-Burnham Medical Research Institute. The referenced example TNAP assay was originally supported by the NIH Roadmap Initiative U54 HG003916, NIH Grant RC1 HL101899, and NIH Grant R03 MH077602-01.

The author wishes to thank Dr. Fu-Yue Zeng and Mr. Carlton Gasior for providing the examples of the programming interface, example schedule, and 10-plate run simulations on the robotic screening system from the GUI of the HRB, Cellario™ system software. The author also thanks Dr. Eduard Sergienko for his thorough reading and useful comments and for his guidance on the assay and HTS history of the TNAP project.

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Authors and Affiliations

  1. Conrad Prebys Center for Chemical Genomics, Sanford-Burnham Medical Research Institute, La Jolla, CA, USA

    Thomas D. Y. Chung

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  1. Thomas D. Y. Chung
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Editors and Affiliations

  1. Sanford Children's Health Research Ctr., Sanford-Burnham Medical Research Inst., North Torrey Pines Road 10901, La Jolla, 92037, California, USA

    José Luis Millán

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Chung, T.D.Y. (2013). Robotic Implementation of Assays: Tissue-Nonspecific Alkaline Phosphatase (TNAP) Case Study. In: Millán, J. (eds) Phosphatase Modulators. Methods in Molecular Biology, vol 1053. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-62703-562-0_4

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  • DOI: https://doi.org/10.1007/978-1-62703-562-0_4

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  • Publisher Name: Humana Press, Totowa, NJ

  • Print ISBN: 978-1-62703-561-3

  • Online ISBN: 978-1-62703-562-0

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