Prediction of atorvastatin plasmatic concentrations in healthy volunteers using integrated pharmacogenetics sequencing

Omar Fernando Cruz-Correa, Rafael Baltazar Reyes León-Cachón, Hugo Alberto Barrera-Saldaña, Xavier Soberón

Research output: Contribution to journalArticle

9 Citations (Scopus)


© 2017 Future Medicine Ltd. Aim: To use variants found by next-generation sequencing to predict atorvastatin plasmatic concentration profiles (AUC) in healthy volunteers. Subjects & methods: A total of 60 healthy Mexican volunteers were enrolled in this study. We used variants with a predicted functional effect across 20 genes involved in atorvastatin metabolism to construct a regression model using a support vector approach with a radial basis function kernel to predict AUC refining it afterwards in order to explain a greater extent of the variance. Results: The final support vector regression model using 60 variants (including six novel variants) explained 94.52% of the variance in atorvastatin AUC. Conclusion: An integrated analysis of several genes known to intervene in the different steps of metabolism is required to predict atorvastatin's AUC.
Original languageEnglish
Pages (from-to)121-131
Number of pages11
Publication statusPublished - 1 Jan 2017


All Science Journal Classification (ASJC) codes

  • Molecular Medicine
  • Genetics
  • Pharmacology

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