Leveraging Real-World Evidence (RWE) in Clinical Trial Design: Statistical Challenges and Opportunities
Source category: Real-world Evidence & Data Visualisation
Author collections: Muhammed Farzan K
THE COMMUNITY ARCHIVE
Clinical Programming Papers and PresentationsPage 7
Clinical programming connects study data, standards, analysis and reporting. Explore implementation papers on clinical trials, validation and repeatable workflows, then follow a focused topic for a particular dataset or deliverable.
981 papers · Showing 121–140
LLM-Powered Clinical Data Flow with Traceability – From Siloed Pipelines to a Semantic Fabric
Source category: Submissions & Agencies
Author collections: Pankaj Attri · Matt Becker
Macro-Powered Clinical Reporting in SAS: Automating Workflows with Automatic Macro Variables, ODS TRACE, and Reusable Table-Building Macros
Source category: Hands-On Workshops
Author collections: Chary Akmyradov
Mapping Minimal Residual Disease (MRD) Biomarker Data in Haematologic Malignancies: Clinical Significance and Data Standards in SDTM and ADaM
Source category: Data Standards, Governance & Implementation
Author collections: Jyothi Nelakurthi
MetaSuite: Empowering Network Meta-Analysis in Clinical Research Through Interactive Visualisations and User-Friendly Evidence Synthesis Tools
Source category: Poster Presentations
Mixed Models and Measured Outcomes: R Tips from the Clinical Trenches
Source category: Coding Tips & Tricks
mkheader: An R Package for Automated Generation and Management of Program Headers in Clinical Trial Programming
Source category: Emerging Technologies (R, Python, GitHub etc.)
Author collections: Gabriela Piasecki · Laura Frederick
mkheader: An R Package for Automated Generation and Management of Program Headers in Clinical Trial Programming
Source category: Open Source Technologies
Author collections: Laura Frederick · Gabriela Piasecki
Modernizing Clinical Research Analytics with Cloud‑Optimized SAS Procedures
Source category: Advanced Programming
Author collections: Jim Box · Mary Dolegowski
Navigating the Statistical Programming Strategies for Cytokine Release Syndrome (CRS) and ICANS in Oncology Clinical Trials.
Source category: Data Standards Implementation (CDISC, SEND, ADaM, SDTM)
Author collections: Murali Kanakenahalli · Vamsi Kandimalla
Next-Gen Statistical Programming in Clinical Trials: Driving Faster, Reliable and Smarter Outcomes
Source category: Professional Development
Author collections: Shashikant Kumar · Mrityunjay Kumar
Open-Source Frameworks for Scalable Data Quality Orchestration in Clinical Data Pipelines
Source category: Emerging Trends & Open Source Technologies
Author collections: Pavan Kumar Reddy Sakam
Operationalizing Generative AI in Regulated Analytics: Applied Implementation Patterns for Enterprise Deployment
Source category: AI in Pharma, Biotech and Clinical Data Science
Author collections: Lida Gharibvand
Optimizing Clinical TFL Review with Python and Power BI: A Reproducible Workflow to Reduce QC Time and Improve Traceability
Source category: Submission Standards for Global Health Authorities
Author collections: Latha Donapati
Orchestrating Efficiency: Symphony and Composer in Clinical Reporting
Source category: Emerging Trends & Innovation
Author collections: Margaret Wishart · Karma Tarap
Path to Consistent Clinical Graphics: An R Shiny Gallery
Source category: Data Visualization & Interactive Analytics
Author collections: Austin Taylor
Patient-Level, Dose-Stratified Swimmer Plots for Comparative Adverse Event Time-Course Assessment in Clinical Trials Using SAS® PROC TEMPLATE
Source category: Advanced Programming
Author collections: Zhaoyu Xie · Ji Qi
Performance-Driven Risk Oversight for AI Agents in Clinical Research
Source category: Artificial Intelligence, Machine Learning and Large Language Models
Author collections: Laxmiraju Kandikatla
PHUSE White Paper Presentation: Protecting Commercially Confidential Information (CCI) Under the EU Clinical Trials Regulation
Source category: Pavilion
Author collections: Sanjay Bagani
Practical Lessons in AI-Assisted Metadata Conversion: From Database Specs to EDC and SDTM — Successes, Pitfalls, and Practical Implementation
Source category: AI in Pharma, Biotech and Clinical Data Science