Literature DB >> 27873357

Use of big data for drug development and for public and personal health and care.

Lada Leyens1, Matthias Reumann1,2, Nuria Malats3, Angela Brand1,4.   

Abstract

The use of data analytics across the entire healthcare value chain, from drug discovery and development through epidemiology to informed clinical decision for patients or policy making for public health, has seen an explosion in the recent years. The increase in quantity and variety of data available together with the improvement of storing capabilities and analytical tools offer numerous possibilities to all stakeholders (manufacturers, regulators, payers, healthcare providers, decision makers, researchers) but most importantly, it has the potential to improve general health outcomes if we learn how to exploit it in the right way. This article looks at the different sources of data and the importance of unstructured data. It goes on to summarize current and potential future uses in drug discovery, development, and monitoring as well as in public and personal healthcare; including examples of good practice and recent developments. Finally, we discuss the main practical and ethical challenges to unravel the full potential of big data in healthcare and conclude that all stakeholders need to work together towards the common goal of making sense of the available data for the common good.
© 2016 WILEY PERIODICALS, INC.

Entities:  

Keywords:  bioinformatics; cognitive computingzzm321990; comparative effectiveness research, knowledge visualization; data commons; drug development; health policy; health systems; healthcare; personalized medicine; public health; public health genomics; safety monitoring; structured data; unstructured data

Mesh:

Year:  2016        PMID: 27873357     DOI: 10.1002/gepi.22012

Source DB:  PubMed          Journal:  Genet Epidemiol        ISSN: 0741-0395            Impact factor:   2.135


  6 in total

Review 1.  Nutritional Genomics and Direct-to-Consumer Genetic Testing: An Overview.

Authors:  Marta Guasch-Ferré; Hassan S Dashti; Jordi Merino
Journal:  Adv Nutr       Date:  2018-03-01       Impact factor: 8.701

Review 2.  How can natural language processing help model informed drug development?: a review.

Authors:  Roopal Bhatnagar; Sakshi Sardar; Maedeh Beheshti; Jagdeep T Podichetty
Journal:  JAMIA Open       Date:  2022-06-11

3.  Potentials and Challenges of the Health Data Cooperative Model.

Authors:  Ilse van Roessel; Matthias Reumann; Angela Brand
Journal:  Public Health Genomics       Date:  2018-06-22       Impact factor: 2.000

4.  Neural side effect discovery from user credibility and experience-assessed online health discussions.

Authors:  Van-Hoang Nguyen; Kazunari Sugiyama; Min-Yen Kan; Kishaloy Halder
Journal:  J Biomed Semantics       Date:  2020-07-08

Review 5.  What Makes Artificial Intelligence Exceptional in Health Technology Assessment?

Authors:  Jean-Christophe Bélisle-Pipon; Vincent Couture; Marie-Christine Roy; Isabelle Ganache; Mireille Goetghebeur; I Glenn Cohen
Journal:  Front Artif Intell       Date:  2021-11-02

Review 6.  The application of artificial intelligence in lung cancer: a narrative review.

Authors:  Huixian Zhang; Die Meng; Siqi Cai; Haoyue Guo; Peixin Chen; Zixuan Zheng; Jun Zhu; Wencheng Zhao; Hao Wang; Sha Zhao; Jia Yu; Yayi He
Journal:  Transl Cancer Res       Date:  2021-05       Impact factor: 1.241

  6 in total

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