| PHUSE US |
2026 |
Accelerating Study Insights: Agile Data Visualisation Using R-Shiny |
Lin Yuan,
Heather Howell |
source
presentation source |
6 |
| PharmaSUG |
2025 |
A Customizable Framework in R for Presenting BICR Data in a User-Friendly Format |
Reneta Hermiz,
Jing Ji |
source |
14 |
| PharmaSUG |
2025 |
A Novel ADEFF Design with Varying Baseline Type Selections |
Tingting Tian,
Chao Su,
Fan Wang,
Pengfei Zhu |
source |
6 |
| PharmaSUG |
2025 |
Roadmap to Efficacy Analysis for Early Phase Oncology studies |
Dhruv Bansal,
Christiana Hawn,
Chris Kelly |
source |
23 |
| PHUSE US |
2025 |
Role of PK/PD, Biomarker Analysis in the Expansion of Phase 1 Trials |
Lavanya Peddibhotla |
source
presentation source |
7 |
| WUSS |
2023 |
Waterfall vis a vis Spider plots: Complex oncology efficacy endpoint made simpler. |
Yoganand Budumuru |
source |
21 |
| SESUG |
2021 |
Side by Side Display of Table and Plot, Plot and Plot |
Hengwei Liu |
source |
11 |
| PHUSE US |
2021 |
Python for Visualization in Solid Tumor Studies |
Hengwei Liu |
source
video
presentation source |
10 |
| PharmaSUG |
2021 |
Double Waterfall Plot Creation for Comparing Target Lesions Data |
Anilkumar Anksapur,
Raghava Pamulapati |
source |
9 |
| PHUSE EU |
2020 |
Enabling Novel Digital Endpoints in Clinical Trials for Regulatory Purposes: Bringing Efficiency to the Industry by Creating a Service-based Ecosystem [presentation] |
Bert Hartog,
Kai Langel |
source
video |
14 |
| SESUG |
2019 |
Cutting Out the Middle Man - Bypassing ADaM to Calculate Tumor Response Inputs using RECIST 1.1 Guidelines and Collected Data in SDTM Format |
Response Inputs |
source |
6 |
| PharmaSUG |
2019 |
From Lesion size to Best Response - Implementing RECIST through programming |
Ankit Pathak |
source |
12 |
| PHUSE US |
2019 |
Efficacy Endpoint Visualization of Investigational Products for Cancer Patients Using R Shiny |
Beverly Martinez,
Mukul K Mittal |
source
presentation source |
12 |
| PHUSE EU |
2018 |
The Oncology-specific Domains TU, TS and RS: What to Know as a Statistical Analyst |
Frieder Wolff,
Vitali Gering |
source
presentation source |
8 |
| PharmaSUG |
2018 |
Leveraging Standards for Effective Visualization of Early Efficacy in Clinical Trial Oncology Studies |
Kelci J. Miclaus,
Lili Li |
source |
12 |
| PharmaSUG |
2012 |
"Analysis-ready" - Considerations, Implementations, and Real World Applications |
Ellen (Zihui) Lin,
Beiying Ding |
source |
6 |
| PharmaSUG |
2012 |
Graphical Outputs for Efficacy Analyses Using SAS/GRAPH SG Procedures |
David A Collins |
source |
7 |
| NESUG |
2011 |
PROC REPORT: Various Reporting Layouts in Clinical Study Reports and Advance Techniques |
Santosh Bari |
|
6 |
| PharmaSUG |
2010 |
Using SAS to Compute Partial Correlation |
Jianxin Lin,
Aiming Yang,
Arvind Shah |
|
5 |
| PharmaSUG |
2009 |
Modeling the Treatment Effect on a Median of a Percent Change from Baseline in a Log-normal Variable Using SAS PROC NLMIXED |
Aiming Yang |
|
5 |
| SUGI |
2001 |
The FASTCLUS Procedure as an Effective Way to Analyze Clinical Data |
Lev Sverdlov |
source |
7 |
| NESUG |
1999 |
The Results of Cluster Analysis of Clinical Data Using the Fastclus Procedure |
Lev Sverdlov,
John F. Noble,
Gabriela Nicolau |
|
9 |
| NESUG |
1998 |
Fasclus Procedure To Identify Subtypes Within A Study Population Following Treatment With A New Antidepressant Drug |
Lev Sverdlov |
|
5 |
HOME
QUICK SEARCH
AUTHORS
KEYWORDS
HELP
BUGS