Introducing pharmacogenomic decision support for medication risk assessment in people with polypharmacy

Polypharmacy has been shown to be a source of multiple adverse drug events. Recent studies demonstrated that pharmacogenomic testing may be instrumental in optimizing medication regimen. However, majority of current pharmacogenomic decision support tools provide assessment only of single drug-gene i...

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Vydáno v:2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) s. 1803 - 1808
Hlavní autoři: Jiazhen Liu, Finkelstein, Joseph
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.11.2017
Témata:
Additives
adverse drug events
Biochemistry
decision support
Drugs
Genetics
Inhibitors
pharmacogenomics
polypharmacy
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Shrnutí:Polypharmacy has been shown to be a source of multiple adverse drug events. Recent studies demonstrated that pharmacogenomic testing may be instrumental in optimizing medication regimen. However, majority of current pharmacogenomic decision support tools provide assessment only of single drug-gene interactions without taking into account complex drug-drug and drug-drug-gene interactions which are prevalent in people with polypharmacy and were shown to be a significant source of adverse drug events. The main objective of this project is development of comprehensive pharmacogenomic decision support for medication risk assessment in people with polypharmacy. To achieve this goal, the project addressed two aims: (1) development of comprehensive knowledge repository of actionable pharmacogenes; (2) introduction of scoring approaches reflecting potential adverse effect risk levels of complex medication regimens accounting for pharmacogenomic polymorphisms and multiple drug metabolizing pathways. After pharmacogenomic knowledge repository was introduced, additive and multiplicative algorithms for medication risk assessment have been implemented. An initial prototype assessment demonstrated feasibility of our approach and identified steps for improving risk scoring algorithms.
DOI:10.1109/BIBM.2017.8217934