A Bayesian Estimation Framework for Pharmacogenomics Driven Warfarin Dosing: A Comparative Study

Oztaner, Serdar Murat
Taşkaya Temizel, Tuğba
Erdem, S. Remzi
ÖZER, Mahmut
The incorporation of pharmacogenomics information into the drug dosing estimation formulations has been shown to increase the accuracy in drug dosing and decrease the frequency of adverse drug effects in many studies in the literature. In this paper, an estimation framework based on the Bayesian structural equation modeling, which is driven by pharmacogenomics, is proposed. The results show that the model compares favorably with the linear models in terms of prediction and explaining the variations in warfarin dosing.


A Bayesian modeling and estimation framework for pharmacogenomics driven warfaring dosing
Öztaner, Serdar Murat; Taşkaya Temizel, Tuğba; Erdem, Remzi; Department of Medical Informatics (2014)
Recent studies have shown that the incorporation of genomics information into the drug dosing prediction formulations increases the accuracy of the drug dosing while decreasing the frequency of adverse drug effects. The current clinical approaches for drug dosing which are supported by the best pharmacogenomics algorithms explain only some percentage of the variance in dosing. The main objective of this study is to enhance the accuracy and efficacy of the warfarin dosing algorithms by using advanced methods...
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Citation Formats
S. M. Oztaner, T. Taşkaya Temizel, S. R. Erdem, and M. ÖZER, “A Bayesian Estimation Framework for Pharmacogenomics Driven Warfarin Dosing: A Comparative Study,” IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, pp. 1724–1733, 2015, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/32170.