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Risk Based Monitoring in Clinical Trial: An Application with Neural Networking

Author

Listed:
  • Atanu B

    (Centre for Cancer Epidemiology, Tata Memorial Centre, India)

  • Savanur S

    (Department of Biometrics, Chiltern Clinical Research Ltd, India)

  • Suman K

    (Department of Biostatistics, Quintiles IMS,India)

Abstract

There are limited literature on statistical methods to deal with Risk based monitoring (RBM) in clinical trial. Recently, it is becoming one of the emerging areas where a party has limited resources for completion of new approaches to trial oversight. This paper is dedicated to provide the application of neural network-ing as a choice to maintain the RBM in clinical research. It is expected that pharmaceutical industries will adopt this procedure in near future for continuous assessment of RBM in their routine clinical trial.

Suggested Citation

  • Atanu B & Savanur S & Suman K, 2017. "Risk Based Monitoring in Clinical Trial: An Application with Neural Networking," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 3(5), pages 155-160, November.
    • Handle: RePEc:adp:jbboaj:v:3:y:2017:i:5:p:155-160
    DOI: 10.19080/BBOAJ.2017.03.555624
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    References listed on IDEAS

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    1. Venet, David & Doffagne, Erik & Burzykowski, Tomasz & Beckers, Francois & Tellier, Yves & Genevois-Marlin, Eric & Legrand, Catherine, 2012. "A statistical approach to central monitoring of data quality in clinical trials," LIDAM Reprints ISBA 2012033, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
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