AI-Powered Drug Discovery: Predicting Molecular Toxicity with RDKit and scikit-learn

This research showcases an exciting application of AI in drug discovery, using open-source tools like RDKit and scikit-learn to predict molecular toxicity. The pipeline offers a significant advancement in efficiency for pharmaceutical companies, as it uses computational methods to pre-screen potential drug candidates before costly experiments.

• •The study builds a curated dataset of over 200 compounds with known toxicity data.
• •It employs RDKit for calculating molecular descriptors and Morgan fingerprints.
• •The pipeline utilizes machine learning models and cross-validation for toxicity classification.