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When good drugs go bad

Author

Listed:
  • Kathleen M. Giacomini

    (University of California, San Francisco)

  • Ronald M. Krauss

    (Ronald M. Krauss is at the Childrens Hospital Oakland Research Institute)

  • Dan M. Roden

    (Dan M. Roden is at the Vanderbilt University School of Medicine)

  • Michel Eichelbaum

    (Michel Eichelbaum is at the Stuttgart Institut Klinische Pharmakologie)

  • Michael R. Hayden

    (Michael R. Hayden is at the University of British Columbia)

  • Yusuke Nakamura

    (Yusuke Nakamura is at the University of Tokyo.)

Abstract

How can we best reduce the risk of severe adverse reactions to marketed drugs? An international group of scientists argues that a global research network is needed to identify genetically at-risk populations.

Suggested Citation

  • Kathleen M. Giacomini & Ronald M. Krauss & Dan M. Roden & Michel Eichelbaum & Michael R. Hayden & Yusuke Nakamura, 2007. "When good drugs go bad," Nature, Nature, vol. 446(7139), pages 975-977, April.
    • Handle: RePEc:nat:nature:v:446:y:2007:i:7139:d:10.1038_446975a
    DOI: 10.1038/446975a
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    Cited by:

    1. Sile Wang & Xiaorui Su & Bowei Zhao & Pengwei Hu & Tao Bai & Lun Hu, 2023. "An Improved Graph Isomorphism Network for Accurate Prediction of Drug–Drug Interactions," Mathematics, MDPI, vol. 11(18), pages 1-16, September.
    2. Niccolò Pancino & Yohann Perron & Pietro Bongini & Franco Scarselli, 2022. "Drug Side Effect Prediction with Deep Learning Molecular Embedding in a Graph-of-Graphs Domain," Mathematics, MDPI, vol. 10(23), pages 1-15, December.
    3. Riad Alharbey & Jong In Kim & Ali Daud & Min Song & Abdulrahman A. Alshdadi & Malik Khizar Hayat, 2022. "Indexing important drugs from medical literature," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(5), pages 2661-2681, May.

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