Abstract
Adverse drug reactions are a serious problem, causing millions of death. According to report, adverse drug reaction is one of the main failure causes in industries such as drug withdrawal and development when a drug has been distributed to the market. Adverse drug reaction is the fourth leading cause of death in the United States, causing 100,000 deaths each year; nevertheless, adverse drug reactions occur depending on the individual. According to reports(1)(2)(3), it is nsSNP that has the highest possibility to determine whether a person will suffer adverse drug reaction when taking certain drugs. In our work, we designed a flow that incorporates the databases(SIDER, DART, dbSNP) and amino acid substitution prediction tool(SIFT) to make predictions about what nsSNPs might have the correlation with certain adverse drug reactions, and thus bio-techies may have these candidates to do clinical experiments. Before our work, there hasn’t been any methodology or flow proposed for the correlation between adverse drug reactions and nsSNPs. We hope our work can help improve the efficiency in bio-techies’ research on the adverse drug reactions.