UT Doctoral Candidate Analyzes Network- and Domain-Based Calculation Method for Anticipating Side Effect Profile of Drugs

According to the report published by the UT Institute of Biochemistry and Biophysics, the adverse effects of drugs are a matter of great concern to patients and constitute the primary reason behind drug recalls and market withdrawals. On average, it takes five to ten years for a new medicine to finish its costly journey from initial discovery to mass production.

The process requires animal and clinical trials, at each stage of which the occurrence of any serious side effects would terminate production.

Furthermore, many of the adverse effects will be discovered years after the launch of the medicine onto the market, the corollary of which would be the failure and subsequent discontinuation of the production of that medicine. In view of the foregoing and other possible complications, the need for a calculation method for predicting the side effect profiles of drugs becomes evident. 

Accordingly, the suggested network- and domain-based algorithm (NDDSA) can anticipate potential side effects of new drug candidates in early stages solely based on the chemical formula of the drug. Soheila Shabani’s dissertation demonstrates that this method performs faster and more efficiently than other existing methods. 

These findings are the results of Soheila Shabani Mashcool’s doctoral dissertation entitled “A Network- and Domain-Based Method for Predicting Drug Side Effect Associations.” Dr. Sajjad Gharaghani, Assistant Professor of Bioinformatics at the UT Institute of Biochemistry and Biophysics, and Dr. Seyyed Amir Marashi, Associate Professor of Bioinformatics at the UT College of Science, supervised Shabani’s dissertation.