© 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.
All Science Journal Classification (ASJC) codes
- Molecular Medicine
Cruz-Correa, O. F., León-Cachón, R. B. R., Barrera-Saldaña, H. A., & Soberón, X. (2017). Prediction of atorvastatin plasmatic concentrations in healthy volunteers using integrated pharmacogenetics sequencing. Pharmacogenomics, 121-131. https://doi.org/10.2217/pgs-2016-0072