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Data mining in pharmacovigilance: lessons from phantom ships

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Notes

  1. Using WebVDME 4.0 by Lincoln Technologies (Waltham, MA)

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Acknowledgement

We would like to thank Barbara J. Stephenson RN, MSC (Epi & Biostats) for her help in critical review of this article.

Author information

Authors and Affiliations

  1. Risk Management Strategy, Pfizer Inc, New York, NY, USA

    Manfred Hauben & Lester Reich

  2. Departments of Pharmacology and Community and Preventive Medicine, New York Medical College, Valhalla, NY, USA

    Manfred Hauben

  3. Department of Medicine, New York University, School of Medicine, New York, NY, USA

    Manfred Hauben

  4. School of Information Systems, Computing and Mathematics, Brunel University, West London, UK

    Manfred Hauben

  5. Netherlands Pharmacovigilance Centre Lareb’s-Hertogenbosch, Groningen, The Netherlands

    Eugène P. Van Puijenbroek

  6. Department of Global Pharmacoepidemiology and Health Outcomes Research, Takeda Global Research and Development Inc, Lincolnshire, IL, USA

    Charles M. Gerrits

  7. Pharmacoepidemiology, Global Drug Safety, Amylin Pharmaceuticals, San Diego, CA, USA

    Vaishali K. Patadia

Authors
  1. Manfred Hauben
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  2. Lester Reich
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  3. Eugène P. Van Puijenbroek
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  4. Charles M. Gerrits
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  5. Vaishali K. Patadia
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Corresponding author

Correspondence to Vaishali K. Patadia.

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Hauben, M., Reich, L., Van Puijenbroek, E.P. et al. Data mining in pharmacovigilance: lessons from phantom ships. Eur J Clin Pharmacol 62, 967–970 (2006). https://doi.org/10.1007/s00228-006-0181-4

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  • DOI: https://doi.org/10.1007/s00228-006-0181-4

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