This research is aimed to: (1) design and implement a mechanism that extracts keywords and facts from drug descriptions via natural language processing and information retrieval techniques, (2) develop an algorithm which will identify potential interaction between drugs, and (3) use the data to visually present the relationships using an interactive graph-based interface.

This research project is supported by Alberta Innovates: "Discovery of Interactions among Drugs via Text Mining and Natural Language Processing Techniques (File No: 23417)" under the supervision of Dr. Maiga Chang, Professor at the School of Computing and Information Systems, Athabasca University.

Site Map

• DDI-Search — A tool designed to show the relationship of drugs using interactive graphs (which will also enable certain users to manage the drug relationships).
• Administration
  • Database Administration — A portal designed for administrators to upload data and monitor the status of the system.
  • User Administration — A portal designed for administrators to manage user accounts.

Project Summary

To be filled with brief information about the research's background, methodologies used (especially in the development of the text mining algorithm), results, conclusions, and further work.

Cited References

1. Assempour N, Chin L, Cummings R, et al. DrugBank 5.0: a major update to the DrugBank database for 2018. Nucleic Acids Res. 2018;46(D1):D1074-D1082. doi:10.1093/nar/gkx1037.
2. Ayvaz S, Boyce RD, Brochhausen M, et al. Toward a complete dataset of drug-drug interaction information from publicly available sources. J Biomed Inform. 2015;55:206-217. doi:https://doi.org/10.1016/j.jbi.2015.04.006