| PharmaSUG |
2026 |
Managing Unblinded Activities Internally: The Independent Statistical Analysis Team (iSAT) Model |
Hong Wang,
Shu Chen,
Chen Li |
source |
4 |
| PharmaSUG |
2026 |
Perspectives on Leading Effectively in Platform Trials: Leadership and Technical Approaches |
Zhen (Laura) Li |
source |
7 |
| PHUSE US |
2026 |
Blind/Unblind Workflows: Secure Separation and Governance in the CDR SCE |
Kala Shivali,
Sachin Walawalkar |
source
presentation source |
11 |
| PHUSE US |
2026 |
From Data Cutoffs to Decision-Making: Programming Futility Analysis in Oncology Clinical Trials |
Mani Mudumba |
source
presentation source |
6 |
| PHUSE US |
2026 |
Optimising Flexibility and Consistency in Statistical Programming for Platform Trials: Practical Approaches to Data Cut, SDTM, ADaM and TFL Setup |
Kelly Fang,
Zhen (Laura) Li |
source
poster source |
6 |
| PHUSE APAC |
2026 |
From Listings to Leadership: Navigating 18 Years of Statistical Programming Outsourcing and the Road Ahead |
Girish Havildar |
source
presentation source |
7 |
| PHUSE EU |
2025 |
Blinded & Coordinated: Aligning People and Processes To Prevent Unblinding |
Monika Bajek,
Dubravka Georgijevic |
source
presentation source |
6 |
| PHUSE EU |
2025 |
Oh Dear, Another Crisis? A Programmers Guide to Surviving and Thriving Through the FDA ODAC |
Zach Dorman |
source
presentation source |
12 |
| PHUSE EU |
2025 |
On the Right Track: Managing Platform Modular Studies with a Central Metadata Switchboard |
Dubravka Georgijevic,
Carla Santillán |
source
presentation source |
7 |
| PHUSE EU |
2025 |
Roadmap to an ODAC: The Journey to and Through an FDA Oncologic Drug Advisory Committee as a Study Lead Programmer |
Charles Wright |
source
poster source |
2 |
| PHUSE EU |
2025 |
Showcasing a Shiny Tool for Evaluating Biomarkers for Derisking Clinical Trials |
Stefan Thoma |
source
presentation source |
9 |
| PharmaSUG |
2025 |
Promising Zone Designs for Sample Size Re-estimation in Clinical Trials: Graphical Approaches Using SAS |
Zhao Yang,
Shivani Nanda |
source |
18 |
| PHUSE US |
2025 |
Fit for Purpose: How to Prepare a Package for Efficient Data Monitoring Committee (DMC) Data Review |
Ke Xiao,
Hong Wang |
source
poster source |
4 |
| PHUSE EU |
2024 |
Failed Clinical Trials: How to Benefit From Negative Experience |
Anna Amosova |
source
presentation source |
13 |
| PharmaSUG |
2023 |
Programmer-s Perspective: Step into Awareness Regarding Clinical Trial Deliverables and Their Impact |
Lyma Faroz,
Jinit Mistry |
source |
10 |
| PharmaSUG |
2023 |
Shifting the drug development paradigm with Adaptive Design and master protocol |
Aman Bahl |
source |
16 |
| PharmaSUG |
2023 |
Study Data Technical Rejection Criteria (TRC) Considerations for Multiple Data Packages in a Single Submission |
Christine S Teng,
Janet Low,
Si Ru Tang |
source |
10 |
| PHUSE US |
2023 |
Handling Multiple Adaptations in One Clinical Trial |
Parvee Kumar,
Shrutimita Pokhariyal |
source
presentation source |
6 |
| PHUSE EU |
2022 |
Adaptive Design - Better Bend Than Break [presentation] |
Albin John,
Athira Sudhakar |
source |
15 |
| PHUSE US |
2022 |
Statistical Programming Operational Review Dashboard [presentation] |
Kathleen J. Harkins,
Shuqi Zhao |
source
video |
16 |
| PHUSE EU |
2021 |
Navigating the Evolving Regulations for Health Canada [presentation] |
Gina Bennet |
source
video |
20 |
| PHUSE EU |
2020 |
A Programmer's Journey Through an Early Oncology Adaptive Platform Trial [presentation] |
Rafi Rahi |
source
video |
20 |
| PHUSE EU |
2020 |
Data Collection Time Point - Challenges with Analysis and Submission [presentation] |
Aayush Bhoraskar,
Sanket Kalyankar |
source
video |
11 |
| SGF |
2020 |
Bayesian Sequential Monitoring of Clinical Trials Using SAS |
Matthew A. Psioda |
source |
13 |
| PharmaSUG |
2020 |
Metadata-driven Modular Macro Design for SDTM and ADaM |
Ellen (Zihui) Lin,
Aditya Tella,
Yeshashwini Chenna,
Michael Hagendoorn |
source |
9 |
| PHUSE US |
2020 |
Sample Size Re-estimation in Action: Design Consideration, Charter Development and Implementation [poster] |
Adam Hamm |
source |
1 |
| PharmaSUG |
2019 |
Practical Perspective in Sample Size Determination |
Bill Coar |
source |
16 |
| PharmaSUG |
2019 |
Raw data sets tracker: Time and project management based on the volume of available clinical data using SAS software |
Girish Kankipati |
source |
10 |
| PHUSE EU |
2018 |
First Aid Kit for an Observational Study |
Yuliia Bahatska,
Vladlen Ivanushkin |
source
poster source |
4 |
| PHUSE EU |
2018 |
Handling CRF Design Changes in a Live Environment |
Andre Snelting,
Nieke De Ruiter |
source
presentation source |
10 |
| PHUSE EU |
2018 |
Implementation of Data Cut Off in Analysis of Clinical Trials |
Ann Croft |
source
presentation source |
13 |
| MWSUG |
2018 |
Avoiding Sinkholes: Common Mistakes During ADaM Data Set Implementation |
Richann J. Watson |
|
15 |
| PHUSE US |
2018 |
Adverse Event Analysis - One step forward! |
Anuja Rasal |
source
presentation source |
11 |
| PHUSE US |
2018 |
Don't Sweat It! Consider Taking the Risk Out of your Outsourced Deliverables |
Jennifer True,
Nancy Haeusser |
source
presentation source |
4 |
| PHUSE US |
2018 |
Interim Survival Analysis Across 3 Platforms |
Venita DePuy |
source
presentation source |
22 |
| PharmaSUG |
2018 |
ADINTDT and ADTTE for Survival Sweep in Oncology Studies |
Christine S Teng,
Wenyu Hu |
source |
6 |
| PharmaSUG |
2018 |
Avoiding Sinkholes: Common Mistakes During ADaM Data Set Implementation |
Richann J. Watson,
Karl Miller |
source |
18 |
| PharmaSUG |
2018 |
Implementation of Data Cut Off in Analysis of Clinical Trials |
Mei Dey |
source |
15 |
| PHUSE EU |
2017 |
Futile or Not? An Interim Analysis Case Study |
Ingrid Franklin |
source
presentation source |
9 |
| WUSS |
2017 |
Avoiding Sinkholes: Common Mistakes During ADaM Data Set Implementation |
Richann J. Watson,
Karl Miller |
source |
15 |
| PharmaSUG |
2017 |
SAS Macro for Derivation of Best Overall Response per RECIST v. 1.1 |
Bob Zhong,
Jiangfan Li,
Hong Xie,
Peter De Porre,
Kenneth Maahs,
Kyounghwa Bae |
source |
9 |
| PharmaSUG |
2017 |
Visualizing Enrollment Over Time |
Laura Gruetzner |
source |
11 |
| SESUG |
2016 |
Surviving the Interim: Insights Into Interim Survival Analyses |
Venita DePuy |
source |
31 |
| PHUSE EU |
2016 |
EnForeSys - An Advanced Patient Enrolment Forecaster with Monte Carlo Simulations |
Ritika Yadav,
Swechhya Bista |
source
presentation source |
12 |
| PHUSE EU |
2016 |
Multiplicity Issues in Clinical Trials - Look at it with a Magnifying Glass! |
Madhusudhan Bandi |
source
presentation source |
6 |
| MWSUG |
2016 |
Frequentist and Bayesian Interim Analysis in Clinical Trials: Group Sequential Testing and Posterior Predictive Probability Monitoring Using SAS |
Kechen Zhao |
|
14 |
| PharmaSUG |
2016 |
Deconstructing ADRS: Tumor Response Analysis Data Set |
Steve Almond |
source |
11 |
| PharmaSUG |
2016 |
Handling Interim and Incomplete Data in a Clinical Trials Setting |
Paul Stutzman |
source |
13 |
| PharmaSUG |
2016 |
Strategic Considerations for CDISC Implementation |
Amber Randall,
William Coar |
source |
6 |
| PHUSE EU |
2015 |
Constructing a Simple Data Repository [presentation] |
Magnus Mengelbier |
source |
19 |
| PHUSE EU |
2015 |
The Highs, Lows and Lessons of a First-Time Study Lead |
Bethan Thomas |
source
presentation source |
7 |
| PharmaSUG CN |
2015 |
Why Statistical Analysis Plan (SAP) should be comprehensive. |
Riddhi Merchant,
Ranjith Prayankotveettil |
|
6 |
| PHUSE EU |
2014 |
Data Challenges in Adaptive Trials |
Claudio Garutti |
source
presentation source |
5 |
| PHUSE EU |
2014 |
PROC EASTMONITOR - A SAS Add-on for Monitoring Adaptive Clinical Trials |
Sheetal Solanki,
Ajay Sathe |
source
presentation source |
15 |
| PHUSE EU |
2013 |
Complex Randomisations Need Not Be Complex |
Fiona Brock |
source
presentation source |
4 |
| PHUSE EU |
2013 |
Organising Deliverables for Clinical Trials - The Concept of Analyses and its Implementation in EXACT |
Hansjörg Frenzel |
source
presentation source |
6 |
| PharmaSUG |
2013 |
SAS Programmer to Clinical SAS Programmer |
Gayatri Karkera,
Nehan Mohan |
source |
7 |
| PHUSE EU |
2012 |
East6: Software for Designing, Simulating and Monitoring Group Sequential Trials |
Hrishikesh Kulkarni,
Sheetal Solanki |
source
presentation source |
12 |
| PHUSE EU |
2012 |
Pooling Clinical Data: Key Points and Pitfalls |
Florence Buchheitt |
source
presentation source |
8 |
| PHUSE EU |
2012 |
Training Statistical Programmers on SAP Review Skills |
Sascha Ahrweiler |
source
presentation source |
7 |
| PharmaSUG CN |
2012 |
Methods to Generate Unavailable Categories in Interim Analysis |
Xiaoran Yin |
|
6 |
| PHUSE EU |
2011 |
Access Control Execution Systems (ACES) |
Shailesh Kulthe,
Eric Silva |
source |
10 |
| PHUSE EU |
2011 |
Architect - A Platform for Design and Analysis Software for Clinical Trials |
Shashank Maratkar |
source |
12 |
| PHUSE EU |
2011 |
Training Statistical Programmers on SAP Review Skills |
Sascha Ahrweiler |
source
presentation source |
7 |
| SCSUG |
2010 |
Impact of model mis-specification on conditional power in interim survival analysis |
Chao L. Chen |
source |
9 |
| PHUSE EU |
2009 |
Clinical Database acceptance: what statistical review checks are necessary to validate a database? |
Genevieve Jehl |
source |
12 |
| PHUSE EU |
2009 |
Medical Research: What should Programmers prepare for? |
Emilie Brennion |
source |
12 |
| PHUSE EU |
2009 |
The role of the statistician in data monitoring committees |
Fritz Schindel |
source |
28 |
| PharmaSUG |
2008 |
Managing Operational Challenges for Interim Analyses |
Mei Dey |
|
10 |
| PharmaSUG |
2007 |
Designing and Building an Administrative Model for SAS Drug Development |
Margaret M. Coughlin |
|
6 |
| NESUG |
2006 |
Designing and Building an Administrative Model for the SAS Drug Development Tool |
Meg Coughlin |
|
6 |
| PharmaSUG |
2006 |
SAS Drug Development: Bringing Innovation to Life Sciences |
David Handelsman |
|
12 |
| SUGI |
2006 |
Version Control on the Cheap. A User-Friendly, Cost-Effective Revision Control System for SAS |
Tim P. Williams |
source |
10 |
| PharmaSUG |
2004 |
Version Control on the Cheap. A User-Friendly, Cost-Effective Revision Control System for SAS |
Tim P. Williams |
|
11 |
| PharmaSUG |
2003 |
Sneak Peek: Previewing Blinded Study Results |
Amy Rhoads Underwood |
|
4 |
| VIEWS |
2001 |
SAS/AF Application in Sequential Clinical Trials |
Tatsuru Matsushita |
|
5 |
| WUSS |
2000 |
Taking Control and Keeping It: Creating and Using Conditionally Executable SAS Code |
Justina M. Flavin,
Arthur L. Carpenter |
source |
4 |
| PharmaSUG |
2000 |
Taking Control and Keeping It: Creating and Using Conditionally Executable SAS Code |
Justina M. Flavin |
|
4 |
| SUGI |
2000 |
Taking Control and Keeping It: Creating and Using Conditionally Executable SAS Code |
Justina M. Flavin,
Arthur L. Carpenter |
source |
4 |
| WUSS |
1993 |
A SAS Program for Sample Size Determination for Equivalence Trials |
Akiko Tomita,
Chul W. Ahn,
Joyce C. Niland |
source |
6 |
| SUGI |
1982 |
Interim Error Handling Strategies in a SAS Based Research Data Management System |
David H. Christiansen,
James D. Hosking |
source |
6 |
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