| PharmaSUG |
2026 |
SDTMIG v4.0: Are You Ready For It? |
Kristin Kelly |
source |
12 |
| PHUSE US |
2026 |
Bridging Patient- and Trial-Level Insights |
Catharina Dahlbo, Eva Kelty |
source poster source |
5 |
| PHUSE US |
2026 |
Building Sustainable RBQM Frameworks: Challenges, Metrics and Real-World Results |
Nicole Stansbury |
source poster source |
7 |
| PHUSE US |
2026 |
Closing the Gap: Identifying Missing Tumour Assessments in Oncology Studies |
Ke Xiao |
source presentation source |
8 |
| PHUSE US |
2026 |
From Oversight to Insight - Rethinking Risk-Based Quality Management |
Madhumita Ghosh, Eva Kelty |
source presentation source |
5 |
| PHUSE US |
2026 |
SDTMIG v4.0: Are You Ready For It? |
Kristin Kelly |
source presentation source |
10 |
| PHUSE APAC |
2026 |
AI-Driven Protocol Review: Accelerating and Simplifying Review |
Aditya Moogi |
source poster source |
14 |
| PHUSE APAC |
2026 |
Beyond Code: Elevating NextGen Statistical Programmers through Cross-Functional Learnings |
Saumil Tripathi |
source presentation source |
7 |
| PHUSE APAC |
2026 |
Critical & Sensitive Information (CSI) Paper AS02 Revolutionizing Clinical Quality: A Frontier Approach with Quality by Design (QbD), Infrastructure Modernization and Data-Driven Analytics |
Priti Gupta, Deepa Balaji |
source presentation source |
12 |
| PHUSE APAC |
2026 |
Embracing the Semantic Shift: SDTMIG 4.0 and the Rise of Intelligent Clinical Data Standards |
Binitha Sathyabhama, Venkateswarlu Layam |
source presentation source |
6 |
| PHUSE APAC |
2026 |
End-to-End Continuous Integration and Deployment Pipeline for Multi Language Analytics Applications: A Clinical Data Management Case Study |
Avinash Patnaik, Varun Sethuraman |
source presentation source |
7 |
| PHUSE APAC |
2026 |
From Information to Insights: Harnessing Centralized Monitoring in RBQM to proactively identify and mitigate risks in Clinical Trials |
Bismita Borkakoty, Priyangshu Chowdhury |
source presentation source |
12 |
| PHUSE APAC |
2026 |
Innovating Clinical Signal Surveillance: Real-Time Dashboards for Protocol and PK Deviation Monitoring |
Rubina Pathan, Jinu J. Nair |
source poster source |
7 |
| PHUSE EU |
2025 |
Collaborative Industry Open-Source Solutions for Clinical Trial Quality Management |
Björn Koneswarakantha, Frederik Collin |
source presentation source |
9 |
| PHUSE EU |
2025 |
Revolutionising Clinical Trial Monitoring and Data Analysis with AR- and VR-Driven Immersive Analytics |
Tej Narayan Yadav, Saurabh Das |
source presentation source |
7 |
| SESUG |
2025 |
Statistical Programmer's role in Bioresearch Monitoring (BIMO) package creation |
Sampath Madanu |
|
25 |
| PHUSE US |
2025 |
An Integrated Approach to Protocol Deviation Management |
Jason Konn |
source poster source |
3 |
| PHUSE US |
2025 |
Harnessing the Power of R Shiny in a GxP-Compliant and Validated Manner for Clinical Trial Use |
Sanyogeeta Andhale, Shilpa Sood |
source presentation source |
13 |
| PHUSE US |
2025 |
Key Metrics for Success: Measuring Project Performance and Impact in the Face of Complex Clinical Trials |
Kavya Yachamaneni, Hayley MacKenzie |
source presentation source |
9 |
| PHUSE US |
2025 |
The Olympics of Data Ingestions |
Cathryn Herbst |
source presentation source |
8 |
| PHUSE US |
2025 |
The Right Tool for the Job: Enhancing Risk-Based Monitoring and Data Cleaning |
Casey Higgins |
source presentation source |
4 |
| PHUSE EU |
2024 |
Coral Reef- A FAIR metadata layer to provide clinical study data at your fingertips |
Javier D. Fernández, Nelia Lasierra |
source presentation source |
5 |
| PHUSE EU |
2024 |
Failed Clinical Trials: How to Benefit From Negative Experience |
Anna Amosova |
source presentation source |
13 |
| PHUSE EU |
2024 |
Perl Regular Expressions in SDTM and ADaM Programming: Live Study Examples |
Pavol Valovic |
source presentation source |
7 |
| PharmaSUG CN |
2024 |
Fighting with Special Characters in Data Management Programmer's Daily Work |
Fei Guo |
source |
20 |
| PharmaSUG |
2024 |
Cultivating Success with Non-standard Investigator-sponsored Trial Data for FDA Submissions |
Jai Deep Mittapalli, Jinit Mistry, Venkatesulu Salla |
source |
9 |
| PharmaSUG |
2024 |
Deep Dive into the BIMO (Bioresearch Monitoring) Package Submission |
Mathura P. Ramanathan, Nancy Brucken |
source |
8 |
| PharmaSUG |
2024 |
Design Considerations for ADaM Protocol Deviations Dataset in Vaccine Studies |
Rashmi Gundaralahalli Ramesh, Jeffrey Lavenberg |
source |
12 |
| PHUSE EU |
2023 |
Data Managers and R Programming: The Unlikely Pair |
Anaelle Perretti (Bonetta) |
source presentation source |
9 |
| PHUSE EU |
2023 |
Look to the Sky: Introducing COMET - the COncomitant MEdication review Tool |
Neville Cope |
source presentation source |
7 |
| PharmaSUG |
2023 |
BIMO Package: Challenges and Perspectives while keeping up with the upgrades in the BIMO Technical Conformance Guide and the BDRG Guidelines |
Mathura P. Ramanathan, Sowmya Gabbula |
source |
18 |
| PharmaSUG |
2023 |
Recent updates in BIMO Technical conformance guidance and use case scenario |
Vaibhav Garg, Sreedhar Bodepudi |
source |
4 |
| PharmaSUG |
2023 |
Using R to Automate Clinical Trial Data Quality Review |
Melanie Hullings, Emily Murphy, Derek Lawrence, Michelle Cohen, Andrew Burd |
source |
6 |
| PHUSE US |
2023 |
A Programmer's Point of View of Current and Future PD Detection T ools |
Meng Li |
source presentation source |
6 |
| PHUSE EU |
2022 |
Protocol Deviation Programming [presentation] |
Oussama Zineddine, Caroline Pelckmans |
source video |
25 |
| PharmaSUG |
2022 |
Avoid Common Mistakes in Preparing the BIMO Deliverables |
Chintan Pandya, Himanshu Patel |
source |
9 |
| PHUSE US |
2022 |
RBM - The New Normal Vigilante for CROs With AI and ML [presentation] |
Vidya Muthukumar |
source |
18 |
| PHUSE EU |
2021 |
New Insights Through Cross-portfolio Risk Analysis [presentation] |
Abdollahi Rouhollah, Julian Ortiz |
source video |
17 |
| PHUSE EU |
2021 |
Standard Implementation: Battling Through the Adversity of a Pandemic [presentation] |
Ana Arques, Vicky Poulsen |
source video |
18 |
| PHUSE EU |
2021 |
Standing Room Only: AR02: The Importance of Being Ernest - The Role of QTLs in QbD [presentation] |
Andrew Lawton |
source |
19 |
| PHUSE US |
2021 |
COVID-19 Presentation: CO01: Harnessing the Power of Shiny to Visualize Missing Data due to the COVID-19 Pandemic [presentation] |
Mark Rothe, Sangeeta Bhattacharya |
source |
13 |
| PHUSE US |
2021 |
The Case for Pandemic-disrupted Studies and Challenges Implementing CDISC and FDA COVID-19 Guidelines for NDA Submissions [presentation] |
Vidya Muthukumar |
source |
44 |
| PHUSE US |
2021 |
Using Central Monitoring to Mitigate Data Quality Risk during the COVID-19 Pandemic [presentation] |
Adrienne Strickler, Anna Wojcik |
source video |
21 |
| PHUSE US |
2021 |
Using Computer Vision to Identify and Extract Tables from Various File Formats [presentation] |
Kanishk Mair, Shashank Pagidimarri |
source video |
22 |
| PHUSE EU |
2020 |
Visualisation of Risk Indicators Using the Shiny App [presentation] |
Kadriye Kaplan |
source video |
10 |
| PharmaSUG |
2020 |
Preparing a Successful BIMO Data Package |
Elizabeth Li, Carl Chesbrough, Inka Leprince |
source |
20 |
| PHUSE US |
2020 |
2020 Syneos Health. All rights reserved |
Working Smarter |
source |
7 |
| PHUSE EU |
2019 |
A Simulation-Based Approach to Establish Quality Tolerance Limits |
Debbie Adkins |
source presentation source |
10 |
| PHUSE EU |
2019 |
Finding the Right Balance - Data Management Surveillance in a Fully Outsourced Partnership Model |
Konstanze Morgenroth |
source presentation source |
11 |
| PharmaSUG |
2019 |
Leveraging Intermediate Data Sets to Achieve ADaM Traceability |
Yun (Julie) Zhuo |
source |
12 |
| PHUSE US |
2019 |
Using Count-based Statistical Models for Key Performance Indicators, Risk Metrics, etc. [presentation] |
Aaron Mackey |
source |
15 |
| PHUSE EU |
2018 |
The Importance of Being Ernest - Risk-based Approach (RBA) |
William Andrew Lawton |
source presentation source |
4 |
| WUSS |
2018 |
How sensitive is your analysis? A case study on addressing it at ADaM level. |
Bhargav Koduru, Balavenkata Pitchuka |
source |
7 |
| PHUSE US |
2018 |
Secure Data Office: An Independent Team that Can Come to the Rescue in Blinded Trials |
Annelies Van Zeveren, Yana Hoorne |
source presentation source |
9 |
| PharmaSUG |
2018 |
ODS/RTF Pagination Revisit |
Ya Huang, Bryan Callahan |
source |
8 |
| SGF |
2018 |
Auto-populating Microsoft PowerPoint Presentations So You Don't Have To |
Kaitie Lawson |
source |
17 |
| SESUG |
2017 |
Statistician's secret weapon: 20 ways of detecting raw data issues |
Lixiang Larry Liu |
source |
8 |
| PHUSE EU |
2017 |
The Secure Data Office Concept |
Annemie Van Dijck |
source presentation source |
9 |
| PharmaSUG |
2017 |
Automated DSMB Presentation in SAS: Yeah, I'd Submit That! How to auto populate PowerPoint presentations so you don't have to |
Brett Jepson, Kaitie Lawson |
source |
17 |
| PharmaSUG |
2017 |
Leveraging Study Data Reviewer-s Guide (SDRG) in Building FDA-s Confidence in Sponsor-s Submitted Datasets |
Xiangchen (Bob) Cui, Min Chen, Letan (Cleo) Lin |
source |
10 |
| PharmaSUG |
2017 |
Statistician's secret weapon: 20 ways of detecting raw data issues |
Lixiang Larry Liu |
source |
8 |
| PharmaSUG |
2016 |
Good versus Better SDTM: Data Listings |
Mario Widel, Henry B. Winsor |
source |
11 |
| PHUSE EU |
2015 |
ADaM - Our Experience |
Rob Wartenhorst |
source presentation source |
5 |
| PharmaSUG |
2014 |
Let Hash SUMINC Count For You |
Joseph W. Hinson |
source |
7 |
| NESUG |
2013 |
Use of SAS for Clinical Trial Management and Risk-Based Monitoring of Multicenter Clinical Trial Data from Electronic Data Capture Tools |
Bob Hall, David Gagnon |
|
14 |
| PHUSE EU |
2011 |
Three Unique Case Studies - On the Trail of the Holy Grail of SDTM Implementation |
Kenneth Stoltzfus |
source presentation source |
6 |
| PharmaSUG |
2011 |
Evolution of SDTMIG 3.1.1 to 3.1.2: A mapping specialist must reference on these changes |
Rachit Desai, Anirudh Gautam, Vikash Jain |
source |
8 |
| PharmaSUG |
2011 |
Truncation, Variable Association, Controlled Terminology, and Some Other Pitfalls in the SDTM Mapping Process |
Na Li, Gary de Jesus, Daniel Bonzo |
source |
8 |