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Bioinformatics Tools and Data Mining for Therapeutic Drug Analysis

  • Juan Manuel Pérez Agudelo
  • Néstor Jaime Castaño Pérez
  • Jhon Fredy Betancur Pérez
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 232)

Abstract

Purpose: To identify issues derived from medication usage. Methods: Pharmacological therapeutics analysis generated by a Health Care Institution in Colombia (n= 400); Type of analysis: MATLAB® 7.10.0.499 (R2010a) based data mining over the following variables: “origin”, “category”, “level”, “type of pharmacological interaction”, “pharmacogenetic relation” and “chance of adverse reaction to medications”. Results: General inadequate medical prescription was found in 3.9% of the cases, while inadequate cardiovascular prescription was found in 37.6% of the cases. 63.6% of the events where catalogued as moderate interactions in the general case when compared with 95.5 % in the cardiovascular case. A significant relation between the type of pharmacokinetic interaction and the chance of having adverse reaction to medication was found. Conclusions: Data mining allows us to get a closer look into under-explored issues related to global analysis such as the interactions derived from pharmacogenetic aspects on the use of medication.

Keywords

Data Mining drug therapy drug interactions 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Juan Manuel Pérez Agudelo
    • 1
  • Néstor Jaime Castaño Pérez
    • 2
  • Jhon Fredy Betancur Pérez
    • 2
  1. 1.Grupo de Investigación BIOSALUDUniversidad de CaldasManizalesColombia
  2. 2.Grupo de Investigación en Ciencias Biomédicas de la Universidad de ManizalesManizalesColombia

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