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Review

HTS Assay Validation

Philip W. Iversen  1 , Benoit Beck  2 , Yun-Fei Chen  1 , Walthere Dere  3 , Viswanath Devanarayan  4 , Brian J Eastwood  1 , Mark W. Farmen  1 , Stephen J. Iturria  5 , Chahrzad Montrose  1 , Roger A. Moore  6 , Jeffrey R. Weidner  7 , G. Sitta Sittampalam  8
Sarine Markossian  1 , Abigail Grossman  1 , Hannah Baskir  1 , Michelle Arkin  2 , Douglas Auld  3 , Christopher Austin  4 , Jonathan Baell  5 , Kyle Brimacombe  1 , Thomas D.Y. Chung  6 , Nathan P. Coussens  7 , Jayme L. Dahlin  8 , Viswanath Devanarayan  9 , Timothy L. Foley  10 , Marcie Glicksman  11 , Kirill Gorshkov  12 , Stefan Grotegut  13 , Matthew D. Hall  1 , Samuel Hoare  14 , James Inglese  1 , Philip W. Iversen  15 , Madhu Lal-Nag  16 , Zhuyin Li  12 , Jason R. Manro  13 , James McGee  17 , Allison Norvil  13 , Mackenzie Pearson  13 , Terry Riss  18 , Peter Saradjian  19 , G. Sitta Sittampalam  20 , Michael A. Tarselli  21 , O. Joseph Trask Jr.  22 , Jeffrey R. Weidner  23 , Mary Jo Wildey  24 , Kelli Wilson  1 , Menghang Xia  1 , Xin Xu  1
, editors.
In: Assay Guidance Manual [Internet]. Bethesda (MD): Eli Lilly & Company and the National Center for Advancing Translational Sciences; 2004.
[updated ].
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Review

HTS Assay Validation

Philip W. Iversen et al.
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Excerpt

Assays employed in HTS and lead optimization projects in drug discovery should be rigorously validated both for biological and pharmacological relevance, as well as for robustness of assay performance. This chapter addresses the essential statistical concepts and tools needed in assay performance validation developed in the pharmaceutical industry, specifically for higher throughput assays run exclusively in 96-, 384- and 1536-well formats using highly automated liquid handling and signal detection systems. In this context, it is assumed that the biological and pharmacological validation of the assay system has already been established, and the high through put performance characteristics requires validation. This is an essential chapter for these who design and implement HTS and lead optimization assays to support SAR projects in pre-clinical drug discovery.

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References

    1. Sittampalam GS, Iversen PW, Boadt JA, Kahl SD, Bright S, Zock JM, Janzen WP, Lister MD. Design of Signal Windows in High Throughput Screening Assays for Drug Discovery. J Biomol Screen. 1997;2:159–169.
    1. Zhang J-H, Chung TDY, Oldenburg KR. A simple statistical parameter for use in evaluation and validation of high throughput screening assays. J Biomol Screen. 1999;4:67–73. - PubMed
    1. Taylor PB, Stewart FP, Dunnington DJ, Quinn ST, Schulz CK, Vaidya KS, Kurali E, Tonia RL, Xiong WC, Sherrill TP, Snider JS, Terpstra ND, Hertzberg RP. Automated Assay Optimization with Integrated Statistics and Smart Robotics. J. Biomol Screen. 2000;5:213–225. - PubMed
    1. Iversen PW, Eastwood BJ, Sittenpalam GS. A Comparison of Assay Performance Measures in Screening Assays: Signal Window, Z’-Factor and Assay Variability Ratio. J of Biomol Screen. 2006;11:247–252. - PubMed
    1. Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet. 1986;I:307–310. - PubMed

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