Machine and Deep Learning Models for Prediction of Small Molecule-Biotech Drug Pair's Interactions

The pharmaceutical industry plays a crucial role in treating diseases. Combining different drugs and using them simultaneously is common in disease treatment. However, adding a new drug can affect the action or effectiveness of another drug. Therefore, predicting the interaction between drug pairs in medical prescriptions is important. Nowadays, two types of drugs are prevalent in the health industry: small molecules and biotech drugs, each with unique properties. Predicting interactions between small molecules and biotech drugs is a challenging and significant process. In this study, we propose a prediction model to identify drug interactions, especially when the types of drugs differ. We utilize various machine learning models and a deep learning model. The results demonstrate that our proposed model performs exceptionally well. The deep learning model outperforms the other methods and achieves the best overall performance.