Course Outline
Fundamentals of AI in Drug Discovery
- Examination of conventional drug discovery workflows
- How AI is transforming the drug discovery landscape
- Case studies: Notable AI-driven drug discovery successes
Machine Learning Applications in Molecular Modeling
- Core concepts of molecular modeling and simulation
- Using machine learning to anticipate molecular characteristics
- Creating predictive models for drug-target interactions
Deep Learning for Virtual Screening
- Overview of deep learning methods in drug discovery
- Deploying deep neural networks for virtual screening tasks
- Case studies: AI-driven virtual screening implementations in pharma
AI in Lead Optimization and Drug Design
- Strategies for refining lead compounds
- Predicting ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) properties using AI
- Embedding AI into the drug design pipeline
AI in Clinical Trials
- The impact of AI on clinical trial design and execution
- Forecasting patient reactions and side effects via AI models
- Case studies: AI utilization in clinical trial settings
Ethical Implications and Obstacles in AI-Driven Drug Discovery
- Ethical dimensions of AI in drug discovery
- Addressing data privacy, bias, and model transparency issues
- Approaches to resolving ethical and regulatory challenges
Conclusion and Future Directions
Requirements
- Proficiency in drug discovery and development workflows
- Practical experience in Python programming
- Working knowledge of machine learning principles
Target Audience
- Scientists in the pharmaceutical industry
- AI experts
- Biotechnology researchers
Testimonials (2)
The training was organized and well-planned out, and I come out of it with systematized knowledge and a good look at topics we looked at
Magdalena - Samsung Electronics Polska Sp. z o.o.
Course - Deep Learning with TensorFlow 2
I really liked the end where we took the time to play around with CHAT GPT. The room was not set up the best for this- instead of one large table a couple of small ones so we could get into small groups and brainstorm would have helped
