Detection of adverse drug reactions is recognized as a measure of quality in drug detection. Although the side effects of drugs are studied at various laboratory stages, these tests are costly and time-consuming. Therefore, computational methods were proposed as an alternative to laboratory methods in studying adverse drug effects. Computational and machine learning techniques can effectively analyze drug features and adverse reactions to predict adverse drug reactions.
In this seminar, we will examine the main challenges in this issue and the solutions that can be useful in solving them.