Module 1: AI Foundations for Pharma
- 1.1 AI and Machine Learning Basics
- 1.2 AI Algorithms and Models
- 1.3 Use Case: Predictive Modeling for Adverse Drug Reactions and Drug-Drug Interactions Using Historical Patient Datasets
- 1.4 Hands-on: Build Predictive Models Using No-Code Tool (Teachable Machine)
Module 2: AI in Drug Discovery and Development
- 2.1 AI in Molecular Drug Design
- 2.2 AI in Drug Repurposing
- 2.3 Use Case: AI-Driven Drug Repurposing Successes (COVID-19 Therapeutics)
- 2.4 Hands-On: Practical AI-Driven Molecular Design and Drug Repurposing Using Orange Data Mining Tool
- 2.5 Hands-On 2: Exploring Disease-Drug Associations with EpiGraphDB
Module 3: Clinical Trials Optimization with AI
- 3.1 AI-Enhanced Patient Recruitment
- 3.2 Clinical Data Management and Monitoring
- 3.3 Use Case: Pfizer’s AI-Driven Analytics for Optimizing Clinical Trials
- 3.4 Hands-on: Implementing Clinical Data Analytics Using No-Code Platforms (KNIME)
Module 4: Precision Medicine and Genomics
- 4.1 Personalized Treatment Strategies
- 4.2 Biomarker Discovery
- 4.3 Case Study: AI-Assisted Biomarker Discovery and Validation in Cancer Treatments
- 4.4 Hands-on: Hands-On Genomic Analysis – Exploring AI-Driven Genomic Interpretation Using CBioPortal
Module 5: Regulatory and Ethical AI in Pharma
- 5.1 Ethical Considerations and AI Governance
- 5.2 AI Compliance and Regulatory Frameworks
- 5.3 Case Study: Analyzing Ethical and Regulatory Challenges Encountered in Major AI-Driven Pharma Initiatives
- 5.4 Hands-on: Developing AI Governance Strategies Based on Ethical Frameworks
- 5.5 Hands-on: Literature Mining with LitVar 2.0
Module 6: Implementing AI in Pharma Projects
- 6.1 AI Project Management
- 6.2 Evaluating AI Tools and ROI
- 6.3 Hands-On: Practical AI Project Management Using Airtable for Tracking, Collaboration, and Management
Module 7: Future Trends and Sustainability in Pharma AI
- 7.1 Emerging AI Technologies in Pharma
- 7.2 AI for Sustainable Healthcare
- 7.3 Case Study: Analysis of Sustainability Initiatives Driven by AI in Pharmaceutical Industry Leaders
- 7.4 Hands-on: Scenario Planning and Predictive Analytics Using Dashboards for Future-Focused Decision Making
Module 8: Capstone Project
- 8.1 Capstone Project 1: Predictive Modeling for Adverse Drug Reactions in Polypharmacy
- 8.2 Capstone Project 2: AI-Enhanced Clinical Trial Recruitment and Retention
- 8.3 Capstone Project 3: AI-Powered Drug Design for Rare Diseases
- 8.4 Capstone Project Evaluation Scheme
Tools you will explore
- Python
- TensorFlow
- PyTorch
- Scikit-learn
- Pandas
- NumPy
- SQL
- Jupyter Notebooks
- MLflow
- DataBricks
- RDKit
- DeepChem
- Biopython
- Hugging Face Transformers for Biomedical NLP
- spaCy / Clinical NLP Toolkits
- Apache Spark for Healthcare Data
- Power BI / Tableau for Clinical Dashboards
