| Section Title | Description | Sample Topics |
| Generative AI in Statistical Programming | Explores the use of generative AI, large language models (LLMs), and AI agents to enhance statistical programming workflows, quality, efficiency, and regulatory compliance. | - AI-assisted code generation and migration
- ADaM/SDTM automation
- AI-driven QC and validation
- Documentation and metadata generation
- AI coding agents and workflow orchestration
- Prompt engineering for regulated environments
|
| AI Applications Development in Clinical Science | Focuses on the application of artificial intelligence (AI), machine learning (ML), and data science to support clinical development, evidence generation, decision-making, regulatory submission and addressing agency requests. | - Machine learning for clinical trial optimization
- AI applications for Real-world data (RWD) and real-world evidence (RWE) analytics
- Synthetic data generation and evaluation
- Feature engineering and data preparation for AI/ML models
- Explainable AI and model interpretability
- Biomarker discovery and risk prediction applications
- AI-enabled signal detection and safety monitoring
- AI applications in epidemiology and observational studies
- Clinical decision support and evidence generation
- Integration of clinical, omics, and external data sources
- Regulatory considerations for AI/ML in drug development
|
| Advanced Programming Foundations | Covers advanced programming techniques, best practices, validation methods, and performance optimization. | - Macro development and management
- Log analysis and debugging
- Defensive programming
- Code optimization and efficiency
- Validation strategies
- Programming standards and governance
|
| Advanced Programming Applications & Automation | Addresses practical programming solutions and automation frameworks supporting clinical research and regulatory deliverables. | - TLF automation
- PRO and COA programming
- define.xml generation
- Metadata-driven programming
- SAS, R, and Python integration
|
| Advanced Statistical Methods and Quantitative Pharmacology | Highlights innovative statistical methods and quantitative pharmacology applications in drug development. | - Survival and time-to-event analyses)
- Bayesian and adaptive designs)
- Sensitivity analyses)
- Causal inference and propensity scores)
- External control arms)
- Population PK/PD modeling)
- Exposure-response modeling)
- Model-informed drug development (MIDD)
|
| Big Data, Real-World Evidence, and Emerging Data Sources | Focuses on large-scale and non-traditional data sources used in clinical research and healthcare analytics. | - Real-world data and evidence
- Observational study analytics
- Genomics data analysis
- Data linkage and privacy protection
- Digital health and wearable data
- Scalable analytics platforms
- Distributed and cloud computing
- Data quality assessment for large datasets
|
| Data Standards & Metadata Management | Addresses implementation, governance, and evolution of data standards and metadata-driven processes. | - SDTM, ADaM, and SEND implementation
- Metadata repositories
- Traceability and compliance
- Controlled terminology
- Standards automation
- Interoperability and data exchange
- CDISC implementation strategies
- Metadata-driven workflows
|
| Data Visualization and Reporting | Covers techniques for creating clear, effective, and actionable visualizations and reports. | - Interactive dashboards
- Patient profiles
- Safety visualizations
- Advanced graphics
- Dynamic reporting
- Data storytelling
- Visual analytics for clinical review
- Interactive regulatory review tools
|
| e-Posters | Showcases concise visual presentations featuring innovative solutions, case studies, tools, and process improvements across all PharmaSUG disciplines. | - Case studies
- Automation solutions
- AI applications
- Standards implementation
- Visualization techniques
- Process improvements
|
| Hands-On Training | Interactive training sessions focused on practical skills, tools, technologies, and industry standards. | - SAS, R, and Python programming
- AI and LLM applications
- CDISC implementation
- Git and CI/CD workflows
- Data visualization
- Regulatory programming practices
|
| Leadership and Professional Development | Focuses on leadership, communication, collaboration, and career growth in the pharmaceutical and biotechnology industries. | - Leadership and team development
- Mentoring and coaching
- Career progression
- Strategic thinking
- Communication skills
- Leading in the AI era
- Change management
- Building high-performing teams
|
| Open Source Languages & Tools (R, Python, etc.) | Explores the use of open-source technologies to support clinical research, analytics, and regulatory submissions. | - R and Python applications
- Package development and validation
- Reproducible research
- CDISC implementation
- Open-source analytics
- Migration from legacy systems
- Statistical computing frameworks
- R/Shiny and Python application development
|
| Modern Development Practices & Platforms (GitHub, CI/CD, etc.) | Covers software engineering practices that improve quality, scalability, compliance, and collaboration. | - Git and GitHub
- CI/CD pipelines
- DevSecOps
- Cloud platforms
- Containerization
- Multilingual development environments
- GxP-compliant development practices
- Automated testing and deployment
|
| Study Data Integration and Global Submission Standards | Addresses integrated analyses and preparation of regulatory submissions for global health authorities. | - ISS/ISE development
- Multi-study integration
- Submission readiness
- eCTD preparation
- Global regulatory requirements
- Traceability and compliance
- Integrated efficacy and safety analyses
- Health authority submission strategies
|
| Tools, Tech & Innovation | Showcases practical technologies and innovative solution development that improve productivity, quality, and efficiency. | - Automation tools
- Custom utilities
- Cloud-based solutions
- Productivity frameworks
- Emerging technologies
- Innovative problem-solving approaches
- Low-code/no-code solutions
- Enterprise technology adoption
|
| Water Cooler Chats (Invitation Only) | Facilitated discussions that encourage networking, knowledge sharing, and community engagement in an informal setting. | - AI and future trends
- Career experiences
- Leadership challenges
- Programming best practices
- Industry perspectives
- Community networking
|
