Green Biotec UG Bremen Germany
Artificial Intelligence in Phamaceutical Industry
| Artificial Intelligence in Pharmaceuticals | |
|---|---|
| Course Description | This comprehensive course explores the transformative role of Artificial Intelligence (AI) in the pharmaceutical industry. Students will learn how AI is revolutionizing drug discovery, development, and patient care. The course covers a wide range of AI applications across the pharmaceutical value chain, from accelerating drug discovery to enhancing drug safety monitoring and personalizing treatments. |
| Key Focus Areas | – Fundamentals of AI and its relevance to pharmaceutical research and development – Machine learning techniques for drug discovery and lead optimization – Deep learning applications in medical image analysis and diagnostic support – AI-driven approaches to clinical trial design and patient recruitment – Predictive modeling for drug efficacy and safety assessment – Natural language processing for mining scientific literature and patient records – AI in pharmacovigilance and post-market surveillance – Ethical considerations and regulatory challenges in AI-driven pharmaceutical innovation |
| Course Learning Outcomes | After completing this course, students will be able to: 1. Understand the fundamental concepts of AI and their applications in pharmaceuticals 2. Apply machine learning and deep learning techniques to pharmaceutical data 3. Develop AI models for drug discovery, clinical trials, and patient care 4. Evaluate the ethical and regulatory implications of AI in pharmaceuticals 5. Analyze emerging trends and future prospects of AI in the pharmaceutical industry |
| Assessment System | Assignments: 40% Midterm Project: 25% Final Project: 35% |
| S.No. | Topic | Assessment |
|---|---|---|
| 1 | Introduction to Artificial Intelligence in Pharmaceuticals | |
| 2 | Python for AI: Basics, Control Structures, Functions, and Modules | Assignment 1 |
| 3 | Machine Learning with Python: Supervised, Unsupervised, and Reinforcement Learning | |
| 4 | Machine Learning in the Pharma Industry | Quiz 1 |
| 5 | Deep Learning: Neural Networks, CNNs, Data Preprocessing | |
| 6 | Deep Learning in the Pharma Industry | |
| 7 | Ethical, Legal, and Regulatory Aspects of AI in Pharmaceuticals | Assignment 2 |
| 8 | Emerging Trends and Future of AI in Pharmaceuticals | |
| 9 | Data Visualization and Reporting Tools | Quiz 2 |
| 10 | Big Data and Data Management Strategies | |
| 11 | Data Analytics for Business Insights | |
| 12 | Business Intelligence Tools and Software | Assignment 3 |
| 13 | AI in Pharmaceutical Marketing and Sales | |
| 14 | Optimization of Human Capital in Biotech Companies | Quiz 3 |
| 15 | Final Project Presentations |
