PharmaSUG China 2018 Conference Proceedings

Beijing
Aug 30 - Sep 1, 2018


AD - Application Development & TechnicalTechniques

AD01. Practical Uses of the DOW Loop in Pharmaceutical Programming
Richard Allen, Peak Stat

AD07. Varied languages, Universal thought: How to handle multilingual data in SAS
Di Chen, SAS Beijing R&D

AD08. SAS Macros to check and solve common problems in Oncology studies
Zhuo Chen, Hutchison MediPharm Ltd.

AD15. SAS Techniques to Handle Large Files And Shorten Execution times
Kaiqing Fan, Mastech Digital Inc.

AD38. Document Automation using R Markdown
Wenfang Li, Boehringer Ingelheim (China) Investment Co., Ltd

AD39. Best Practices for Interactive Analyses for Decision Making and Submission
Gaoyang Li, Bayer

AD40. Simplifying Your %DO Loop with CALL EXECUTE
Arthur Li, City of Hope National Medical Center

AD41. How Best to Use Macro Quoting Functions
Arthur Li, City of Hope National Medical Center

AD44. A Macro to Automate RFPENDTC Derivation
Dan Li, Sanofi-Aventis

AD49. Combining quality of productivity and efficiency under highly pressure of lacking time – discussion by view of first-time quality
Winkle Lu

AD54. A Macro for checking incorrect format of time variable
Lanlan PENG, Sanofi

AD58. TLF Management Tools: SAS programs to help in managing large numbers of TLFs
Eduard Joseph Siquioco, PPD

AD61. An efficient way to check log issue in SAS EG
sichan Tang, BeiGene

AD62. Decomposition and Reconstruction of TLF Shells - a Simple, Fast and Accurate Shell Designer
Chengeng Tian, dMed Biopharmaceutical Co., Ltd.

AD64. A tool to compare different data transfers
Jun Wang, FMD K&L Inc.

AD71. No Solution to Auto-generating acrf.pdf? Try to Use GROOVY Procedure!
Yin-Jhen Yan, PAREXEL International



CC - Coder's Corner


CC18. Basic SAS® Hash Programming Techniques Applied in Our Daily Work in Clinical Trials Data Analysis
LI FANYU, MSD

CC20. Write Your Dynamic Programming Function with SAS FCMP
Emily Gao, SAS Research and Development (Beijing) Co., Ltd.

CC23. Make your program tracking sheet more powerful - Using VBA
Pengfei Guo, MSD R&D (China) Co., Ltd.

CC32. Opening multiple SAS sessions in Windows PC environment
Rob Howard, Veridical Solutions



CD - Data Standards/CDISC & Regulatory Submission

CD03. Knock Knock!!! Who's There??? - Challenges faced while pooling data and studies for FDA submission
Amit Baid, CLINPROBE, LLC

CD09. Every second counts! Save time on developing Trial Summary Specification.
Mei-Chen Chu, PAREXEL

CD24. Common Pinnacle 21 Report Issues: Shall we Document or Fix?
Ajay Gupta, PPD

CD36. What is RE domain?
David Ju, ERT

CD43. Standardize Study Data for Electronic Submission
Qin Li, Regeneron Pharmaceuticals, Inc.

CD57. Some Common Programming Errors and Possible Solutions That Could Impact a Successful NDA/BLA
amos shu, AstraZeneca

CD66. Avoiding Sinkholes: Common Mistakes During ADaM Data Set Implementation
Richann Watson, DataRich Consulting

CD68. Considerations in ADaM Occurrence Data: Handling Crossover Records for Non-Typical Analysis
Richann Watson, DataRich Consulting

CD72. Display the XML Files for Disclosure to Public by Using User-defined XSL
Zhiping Yan, BeiGene

CD77. Programming Support for BIMO deliverable
Rong Zhang, Pfizer (China) Research & Development Co. Ltd.

CD79. My understandings to SDTM and ADaM
Chunpeng Zhao, Boehringer-Ingelheim

DM - Data Validation & Management

DM02. User-defined Functions for Processing Lab Data
Richard Allen, Peak Stat

DM05. Leveraging Metadata when Mapping to CDISC Standards with SAS® Machine Learning
Matt Becker, SAS

DM22. How to do data validation plan autogeneration in clinical trial
David Guo, Proswell

DM45. Standardize Study Data for Electronic Submission
Qin Li, Regeneron Pharmaceutical

DM47. Decision making confidence: the way to make decision by Process Data with BPMN in SAS® LSAF
Emma Liu, SAS Beijing R&D

DM73. Best Practices for E2E DB build process and Efficiency on CDASH to SDTM data
tao yang, FMD&KL



DV - Data Visualization & Graphics

DV04. Leveraging Standards for Effective Visualization of Early Efficacy in Clinical Trial Oncology Studies
Matt Becker, SAS

DV16. Create Cupid Arrow into Two Love Hearts Image Using SAS PROC TEMPLATE --- For the Valentine’s Day
Kaiqing Fan, Mastech Digital Inc.

DV17. Draw statement, more flexibility with GTL(Graph Template Language)
Kuangye Fang, PPD

DV19. Pay Less but Get More, Analyze Medicare Claims Data using SAS® Episode Analytics
Shuang Fu, SAS Research and Development (Beijing) Co., Ltd.

DV25. Advanced Visualization using TIBCO Spotfire® and SAS®
Ajay Gupta, PPD

DV29. V is for Venn Diagrams
Kriss Harris, SAS Specialists Limited

DV34. Using the ODS GRAPHICS® to Create Patients Enrollment Graphs
Yiqian Jiang, Johnson & Johnson (China) Investment Ltd.

DV46. Efficient Graphing of Basic Data Structure - Let Data Decide Scale of Y-Axis for Themselves
KuenHung Lin, PAREXEL International

DV51. Advanced Clinical Graphs using Axis Tables
Sanjay Matange, SAS Institute Inc.

DV52. Multi-Arm CONSORT Diagrams with SAS
Sanjay Matange, SAS Institute Inc.

DV56. Utilize Dummy Variables/Datasets in Graph Generation
amos shu, AstraZeneca

MA - Management & Career Development

MA33. Managing and Retaining Millennials & Generation Z
Margaret Hung, MLW Consulting LLC

MA37. User Experience or Data Driven - the life of METRICS
Charan Kumar K J, Ephicacy Lifescience Analytics Pvt. Ltd.

MA65. How to Take Your Next Step in Your Career
Lei Wang, The Lotus Group



PO - Posters

PO13. How to Create Graphic Images in Assembly Line Way Using PROC TEMPLATE in SAS Enterprise Guide
Kaiqing Fan, Mastech Digital Inc.

PO14. How to automatically cover arbitrary changes Using automatic code generation method in SAS Enterprise Guide
Kaiqing Fan, Mastech Digital Inc.



SP - Statistics & Pharmacokinetics

SP11. Survival Analysis to Cox PH Models with Time-varying Coefficients
Hao Dong, Hutchison MediPharma

SP28. A SAS Macro for Continuous Glucose Monitoring (CGM) Data Analysis
Xiaoran Han, The Chinese University of Hong Kong

SP48. Statistical Programming Analysis of Percentage of Responders in Alzheimer’s Disease
yan liu, MSD

SP63. Sense and Censorability: Learn censoring techniques with ADTTE for your survival
Shilpakala Vasudevan, Ephicacy Lifescience Analytics

SP67. Let’s Get FREQy with our Statistics: Data Driven Approach to Determining Appropriate Test Statistic
Richann Watson, DataRich Consulting

SP75. Several methods to test the proportional hazard assumption before applying cox models
Ying Yao, boehringer-ingelheim

SP81. Introduction to iRECIST
Howard Tien, Sanofi