MedCassandra : Personalized drug and ADR ranking forecast system based on personal genome variations

Abstract

Introduction: As the advancement of genome sequencing technology, there are some trials for pharmacogenomics interpretation. But traditional interpretation based on relationships of variant-drug response is simply annotating and listing variations and associated pharmacogenomic traits, not estimation and summarization of the total risk for each individual. So I develop MedCassandra, a system that forecast drug and ADR rank based on personal genome variations. Methods & Results: MedCassandra consist of two parts. First I develop the algorithm for calculation of drug and ADR ranks. Second, I integrate drug information which requires for rank calculation from multi drug databases. When individuals input their genome variations, MedCassandra recommends the rank of drugs and ADRs that need to be cautious. As result of Asian individuals drug and ADR ranking, I confirm individual-specific drugs that individual should take more carefully. And overall individuals drug rank is reasonable when I compare highly ranked drugs to existing pharmacogenomics knowledge. Conclusions: As MedCassandra recommend the alert list of drugs and ADRs, it can help that individual choose right drug which they can use more safely and prepare and manage the ADR outbreak previously.