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CDISC Papers and PresentationsPage 3

Browse practical discussions of clinical data standards, from collected observations to analysis datasets and supporting metadata. Use the more focused ADaM, SDTM and Define-XML collections to follow a particular stage of the workflow.

856 papers · Showing 41–60

PharmaSUG · 2026Paper DS-341PharmaSUG 2026

DOSEON: Fuzzy Matching DOSE Date Intervals ON Analysis Dates Across SAS (PROC SQL, SAS Macro, DATA Step, and PROC FCMP)

Inka Leprince; Troy Hughes

Source category: Data Standards Implementation (CDISC, SEND, ADaM, SDTM)

Author collections: Inka Leprince · Troy Hughes

PHUSE · 2026Paper ML10PHUSE APAC Connect 2026

Elevating Transparency in Data Standardisation: Applying XAI in SDTM, ADaM, and TFL Generation

Shakila Jagadeesan

Source category: Machine Learning, AI & Large Language Models, Data Handling & Data Engineering

PHUSE · 2026Paper DS11PHUSE US Connect 2026

Enabling Innovation: Lessons from the CDISC AI Innovation Challenge

Julie Smiley

Source category: Data Standards, Governance & Implementation

Author collections: Julie Smiley

PHUSE · 2026Paper PP20PHUSE US Connect 2026

End-to-End Workflow for CDISC Estimand Framework in Clinical Trials

Hiral Raval; Simon Luo

Source category: Poster Presentations

Author collections: Hiral Raval · Simon Luo

PharmaSUG · 2026Paper PK-310PharmaSUG 2026

Enhancing ADaM PK Datasets to Automate PK TFLs Generation

Jianli Ping; Karthik Sankepelli

Source category: PK/PD/ADA and Quantitative Pharmacology

Author collections: Jianli Ping

PharmaSUG · 2026Paper AI-125PharmaSUG 2026

Enhancing ADaM Specification Validation and Generation of SAS Codes Using LLM through Amazon Bedrock: A Practical Framework

Pavan Kumar Tatikonda; Ryo Nakaya; Sravan Kongara

Source category: AI in Pharma, Biotech and Clinical Data Science

Author collections: Pavan Kumar Tatikonda · Ryo Nakaya

PharmaSUG · 2026Paper PO-433PharmaSUG 2026

Enhancing CDISC Standards Implementation (SDTM and ADaM) with PROC FCMP, PROC IML and Macro Loop Integration in Oncology Clinical Trials.

Ajay Gupta; Misikir Tesfaye

Source category: ePosters

Author collections: Ajay Gupta · Misikir Tesfaye

PHUSE · 2026Paper ML14PHUSE APAC Connect 2026

Enhancing Clinical Data Standardisation Through Intelligent Mapping of eCRF Forms and Items to SDTM

Saransh Khandelwal; Kedar Deshpande

Source category: Machine Learning, AI & Large Language Models, Data Handling & Data Engineering

Author collections: Kedar Deshpande

PHUSE · 2026Paper DH04PHUSE US Connect 2026

Enhancing Clinical Trial Dataset Mapping with AI/ML Techniques: An Approach for CDISC Variable Prediction

Parveen Kumar

Source category: Data Handling & Engineering

Author collections: Parveen Kumar

PharmaSUG · 2026Paper HT-447PharmaSUG 2026

Following Your Footsteps: Maintaining Traceability in ADaM Datasets

Nancy Brucken; Karl Miller

Source category: Hands-On Training

Author collections: Nancy Brucken · Karl Miller

PharmaSUG · 2026Paper DS-196PharmaSUG 2026

Friction to Flow: LLM-Based Automation of Clinical Data Workflows

Pankaj Attri; Matt Becker

Source category: Data Standards Implementation (CDISC, SEND, ADaM, SDTM)

Author collections: Pankaj Attri · Matt Becker

PHUSE · 2026Paper DV12PHUSE US Connect 2026

From Black Box to Glass Box: A Context-Aware Approach to SDTM Mapping Automation with Interactive Visual Validation

Rostislav Markov; Jacques Lanoue

Source category: Data Visualisations

Author collections: Rostislav Markov · Jacques Lanoue

PharmaSUG · 2026Paper SS-307PharmaSUG 2026

From Data Flood to Insight: Efficient SDTM Validation for High-Frequency Sources

Seiko Yamazaki

Source category: Submission Standards for Global Health Authorities

Author collections: Seiko Yamazaki

PHUSE · 2026Paper SM05PHUSE APAC Connect 2026

From Document to Derivation: Automating ADaM Variable and Endpoint Code Generation Using Study Specifications and Clinical Documents

Alisha D; Sruthy Biju

Source category: Scripts, Macros & Automation

PharmaSUG · 2026Paper DS-280PharmaSUG 2026

From Manual to Automated”: An SAS® and R-Based Toolkit for Scalable SDTM Generation

Hardik Sheth; Eldho Alias

Source category: Data Standards Implementation (CDISC, SEND, ADaM, SDTM)

Author collections: Hardik Sheth

PharmaSUG · 2026Paper DS-440PharmaSUG 2026

From Specification to SDTM at Speed: Deploying the SDTM Engine in Production

Lynn Xiuling Zhang; Jacques Lanoue; Ulf Nielsen

Source category: Data Standards Implementation (CDISC, SEND, ADaM, SDTM)

Author collections: Jacques Lanoue · Ulf Nielsen

PharmaSUG · 2026Paper ET-279PharmaSUG 2026

Goodbye SAS, Hello R: Practical Workflows for CDISC Standards

Madeleine Penniston; Alyssa Wittle

Source category: Emerging Technologies (R, Python, GitHub etc.)

Author collections: Madeleine Penniston · Alyssa Wittle

PharmaSUG · 2026Paper DS-372PharmaSUG 2026

Handling multiple screenings and multiple enrollments in SDTM: CDISC and FDA Guidance

Laura Williams; Andrea Gardani

Source category: Data Standards Implementation (CDISC, SEND, ADaM, SDTM)

Author collections: Laura Williams

PHUSE · 2026Paper OS17PHUSE US Connect 2026

Harmonising gsm and the pharmaverse: Orchestrating SDTM, ADaM, TFLs and ARS in a Unified R Workflow

Zelos Zhu

Source category: Open Source Technologies

PHUSE · 2026Paper ML23PHUSE US Connect 2026

Harnessing LLM-Augmented Automation for ADaM Dataset Generation

Anil Mogha; Ghourav Garg

Source category: Artificial Intelligence, Machine Learning and Large Language Models