Essential AI Tools for Modern Drug Discovery

🎓 About the Workshop

Artificial intelligence is rapidly transforming modern drug discovery by enabling faster and more efficient analysis of molecular data. Instead of relying solely on traditional experimental screening, researchers can now use computational tools to predict molecular properties, explore chemical similarities, and prioritize potential drug candidates through data-driven approaches. Understanding how to apply these AI-based techniques is becoming increasingly important for scientists working in bioinformatics, cheminformatics, and pharmaceutical research.

This 3-day mentor-guided, hands-on online workshop introduces participants to essential AI tools used in molecular analysis and early-stage drug discovery. Using platforms such as RDKit, DeepChem, and web-based ADMET prediction tools, participants will learn how to visualize molecules, calculate molecular properties, run pre-trained machine learning models, and interpret prediction results. Through guided demonstrations and practical exercises using real molecular datasets, participants will gain foundational skills for applying AI-driven workflows in modern drug discovery.

📚 3-Day Hands-on Online Workshop | 🗓️ March 23–25, 2026 | ⏱️ 9:30 PM IST / 11:00 AM CDT

👨‍🏫 Faculty and Instructors

The workshop will be delivered by experienced OmicsLogic mentors with strong expertise in artificial intelligence, computational drug discovery, and molecular data analysis. The instructors have extensive experience conducting live, hands-on training sessions and guiding participants through practical workflows using AI-powered tools such as RDKit, DeepChem, and web-based molecular prediction platforms. Through interactive demonstrations and guided exercises, participants will learn how to analyze molecular structures, perform property prediction, and interpret AI-generated results, ensuring a practical and industry-relevant learning experience in modern drug discovery workflows.

👉 Who Should Attend?

This workshop is suitable for students, graduates, researchers, and professionals in life sciences who are interested in understanding how artificial intelligence can be applied in modern drug discovery and molecular analysis. It is particularly beneficial for learners from fields such as bioinformatics, computational biology, chemistry, and pharmaceutical sciences who want hands-on exposure to AI-assisted molecular analysis, property prediction, and computational workflows using tools like RDKit, DeepChem, and web-based ADMET platforms for early-stage drug discovery research.

🧑‍💻 Learning Tools and Technologies Covered

Participants will gain hands-on experience with widely used AI-enabled molecular analysis tools and cheminformatics platforms relevant to modern drug discovery workflows. The workshop introduces open-source tools such as RDKit and DeepChem, along with web-based platforms like ADMETlab and SwissADME, enabling learners to load and visualize molecular structures, calculate physicochemical properties, perform molecular similarity searches, and run pre-trained machine learning models for molecular property prediction.

Through guided exercises using Google Colab notebooks and real molecular datasets, participants will learn how to interpret prediction outputs, understand model confidence and limitations, and integrate multiple AI-based tools within a structured analysis workflow. The workshop emphasizes practical learning through demonstrations, curated examples, and a guided mini-project that helps participants apply AI-powered molecular analysis techniques in modern drug discovery research.

👉 For more details about the program, reach out to us using the form link: https://forms.gle/YskP9ckSXDuPnKVX8