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Use of big data in drug development for precision medicine: an update.

Tongqi QianShijia ZhuYujin Hoshida
Published in: Expert review of precision medicine and drug development (2019)
In the near future, much larger volumes and complex datasets for precision medicine will be generated, e.g., individual and longitudinal multi-omic, and direct-to-consumer datasets. Closer collaborations between experts with different backgrounds would also be required to better translate analytic results into prognosis and treatment in the clinical practice. Meanwhile, cloud computing with protected patient privacy would become more routine analytic practice to fill the gaps within data integration along with the advent of big-data. To conclude, integration of multitudes of data generated for each individual along with techniques tailored for big-data analytics may eventually enable us to achieve precision medicine.
Keyphrases
  • big data
  • clinical practice
  • artificial intelligence
  • machine learning
  • primary care
  • rna seq
  • case report
  • current status
  • deep learning
  • single cell
  • data analysis