Learn · Artificial Intelligence in Drug Discovery and Development
Lecture 21 of 60Week 05
Introduction & Approches to Virtual Screening
Prof. Rajnish Kumar · IIT (BHU) Varanasi
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- Artificial Intelligence in Drug Discovery and Development, IIT (BHU) Varanasi (at NPTEL)
- Licence
- CC BY-NC-SA, as NPTEL states it. Non-commercial use only.
- Attribution
- NPTEL states: "Distributed under Creative Commons Attribution-ShareAlike / CC BY - NC - SA", beside a BY-NC-SA badge. Coordinated by IIT Madras.
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All the lectures
- Drug Discovery & Development
- Overview of Drug Discovery Workflows
- Drug Design Strategies
- Conventional Methods for Drug Discovery
- Riddles in Drug Discovery
- History & Evolution of AI in Drug Discovery
- Overview of AI Technologies
- Key Application of AI Across the Pipeline
- Available AI Tools & Platforms
- Advantages of AI Integration in Drug Discovery
- Introduction to Machine Learning Concepts
- Overview of Neural Networks
- Feature Engineering & Data Preprocessing
- Evaluation Metrics for AI Models
- Introduction to Python Libraries for AI in Drug Discovery
- introduction to Drug Targets
- Basic of Target Identification and Validation
- Omics Data Integration for Target Discovery
- Binding Site and Proteins Structure Prediction with AI
- Hands on Tutorial Protein Structure Prediction
- Introduction & Approches to Virtual Screening
- AI Tools for Virtual Screening
- AI Assisted Molecular Docking
- Workflow of High Throughput Virtual Screening
- Hands on Tutorial - AI Assited Molecular Docking
- Basics of Lead Optimization
- AI for Drug Target Interaction Studies
- QSAR Modelling
- Introduction to Molecular Dynamic MDSimulation
- Hands on Tutorial MD Analysis
- Introduction to ADMET Properties
- Importance of ADMET & Its Prediction in Lead Optimization
- Conventional Methods for ADMET Prediction
- Openly Available Resources for ADMET Prediction
- Hands on Tutorial AI Enabled ADMET Prediction
- Overview of Clinical Trials
- Patient Recruitment, Stratification & Retention
- Clinical Trial Protocol Design & Optimization
- Predicting Outcomes of Clinical Trials with AI
- Data Collection & Monitoring for Regulatory Submissions
- Introduction to Generative AI in Drug Design
- Deep Generative Models for Drug Design
- Benchmarking Generative Models for Drug Design
- Molecule Optimization with Generative AI
- Hands on Tutorial GNN Based De Novo Drug Design
- AI in Genomics for Personalized Treatment
- AI in Real Time Monitoring & Feedback
- Overview & Data Sources for AI in Drug Repurposing
- Integrating Multi Target Drug Discovery
- network Pharmacology with AI
- Public AI Resources for Drug Discovery
- Success Case Studies of AI in Drug Discovery
- Challenges in Modern Drug Discovery Realm
- Regularory Considerations for AI Implementation
- Future Outlook Explainable Artificial Intelligence XAI & Other Emerging Technologies in Drug Di
- Molecular Structure Representation
- Solubility Prediction Using Machine Learning
- Bioactivity Prediction
- Pharmacophore Based Virtual Screening
- Similarity Based Screening