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コース概要
Introduction to AI in Drug Discovery
- Overview of traditional drug discovery processes
- The role of AI in revolutionizing drug discovery
- Case studies: Successful AI-driven drug discovery projects
Machine Learning in Molecular Modeling
- Basics of molecular modeling and simulations
- Applying machine learning to predict molecular properties
- Building predictive models for drug-target interactions
Deep Learning for Virtual Screening
- Introduction to deep learning techniques in drug discovery
- Implementing deep neural networks for virtual screening
- Case studies: AI-driven virtual screening in pharmaceutical companies
AI for Lead Optimization and Drug Design
- Techniques for optimizing lead compounds
- Using AI to predict ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) properties
- Integrating AI into the drug design pipeline
AI in Clinical Trials
- The role of AI in clinical trial design and management
- Predicting patient responses and adverse effects using AI models
- Case studies: AI applications in clinical trials
Ethical Considerations and Challenges in AI-Driven Drug Discovery
- Ethical issues in AI applications for drug discovery
- Challenges in data privacy, bias, and model interpretability
- Strategies for addressing ethical and regulatory concerns
Summary and Next Steps
要求
- An understanding of drug discovery and development processes
- Experience with programming in Python
- Familiarity with machine learning concepts
Audience
- Pharmaceutical scientists
- AI specialists
- Biotech researchers
21 時間
お客様の声 (2)
Organization, adhering to the proposed agenda, the trainer's vast knowledge in this subject
Ali Kattan - TWPI
コース - Natural Language Processing with TensorFlow
Very updated approach or CPI (tensor flow, era, learn) to do machine learning.
