Philadelphia, Pennsylvania
June 16-19, 2019


Advanced Programming

AP-001. Get Smart! Eliminate Kaos and Stay in Control – Creating a Complex Directory Structure with the DLCREATEDIR Statement
Louise Hadden, Abt Associates Inc.

AP-018. Ensuring Programming Integrity with Python: Dynamic Code Plagiarism Detection
Michael Stackhouse, Covance

AP-038. One Macro to Produce Descriptive Statistic Summary Tables with P-Values
Rajaram Venkatesan, Cognizant Technology Solutions
Harinarayanan Gopichandran, Cognizant Technology Solutions

AP-042. Excel in SAS
Charu Shankar, SAS

AP-047. Confessions of a SAS PROC SQL Instructor
[Additional Materials (ZIP Archive)]
Charu Shankar, SAS

AP-071. Ushering SAS Emergency Medicine into the 21st Century: Toward Exception Handling Objectives, Actions, Outcomes, and Comms
Troy Hughes, Datmesis Analytics

AP-074. Where Is the Information We Are Looking For?
Jeff Xia, Merck & Co., Inc.

AP-114. The Art of Defensive Programming: Coping with Unseen Data
Philip Holland, Holland Numerics Ltd

AP-116. Excel with MS Excel and X Commands: SAS® Programmers’ Quick Tips Guide to Useful Advanced Excel Functions and X Commands.
Shefalica Chand, Seattle Genetics, Inc.

AP-123. Automation of Review Process
Shunbing Zhao, Merck & Co., Inc.

AP-125. Auto-Annotate Case Report Forms with SAS® and SAS XML Mapper
Yating Gu, Seattle Genetics, Inc.

AP-143. PROC SORT (then and) NOW
Derek Morgan, PAREXEL International

AP-154. Unleash the Power of Less Well Known but Useful SAS(r) DATA Step Functions
Timothy Harrington, SAS Programmer

AP-156. Generate Customized Table in RTF Format by Using SAS Without ODS RTF – RTF Table File Demystified
Kai Koo, Abbott Vascular

AP-157. Practices in CDISC End-to-End Streamlined Data Processing
Chengxin Li, Luye Pharma Group

AP-158. Six Useful Data Tool Macros
Ting Sa, Cincinnati Children's Hospital Medical Center

AP-187. Tidyverse for Clinical Data Wrangling
Phil Bowsher, RStudio Inc.

AP-189. From Static ggplot2 Output to Interactive Plotly Visualization to Shiny App
Kelly O'Briant, RStudio

AP-191. Creating In-line Style Macro Functions
Arthur Li, City of Hope

AP-205. Quick Tips and Tricks: Perl Regular Expressions in SAS
Pratap Kunwar, EMMES
Jinson Erinjeri, EMMES

AP-212. Python-izing the SAS Programmer
Mike Molter, Wright Ave Partners

AP-216. Using SAS® ODS EXCEL Destination “Print Features” to Format Your Excel Worksheets for Printing as You Create Them.
William Benjamin, Owl Computer Consultancy LLC

AP-241. Minimally Invasive Surgery to Merge Data
Paul Hamilton

AP-290. PROC SQL to the Rescue: When a Data Step Just Won't Do Anymore
John O'Leary, Department of Veterans Affairs

AP-298. Automating SAS Program Table of Contents for Your FDA Submission Package
Lingjiao Qi, Statistics & Data Corporation
Bharath Donthi, Statistics & Data Corporation



Applications Development

AD-032. Extending the umbrella of compliance: LSAF with R Distributed Computing
Ben Bocchicchio, SAS
Sandeep Juneja, SAS
Rick Wachowiak, SAS

AD-048. Reimagining Statistical Reports with R Shiny
Sudharsan Dhanavel, Cognizant Technology Solutions
Harinarayan Gopichandran, Cognizant Technology Solutions

AD-052. Text Analysis of QC/Issue Tracker Using Natural Language Processing (NLP) Tools
Huijuan Zhang, Columbia University
Todd Case, Vertex Pharmaceuticals Inc.

AD-054. Generating Color Coded Patient ID Spreadsheet (PID list) To Make It Easier for the Reviewers.
Ranjith Kalleda, Pfizer
Ashok Abburi, Pfizer

AD-064. %LOGBINAUTO: A SAS 9.4 Macro for Automated Forward Selection of Log-Binomial Models
Matthew Finnemeyer, Vertex Pharmaceuticals Inc.

AD-077. An Application of Supervised Machine Learning Models on Natural Language Processing: Classifying QC Comments into Categories
Xiaoyu Tang, Vertex Pharmaceuticals Inc.
Todd Case, Vertex Pharmaceuticals Inc.

AD-078. ADME Study PK SDTM/ADaM And Graph
Fan Lin, Gilead Sciences, Inc.

AD-094. A SAS and VBScript cyborg to send emails effectively.
Nikita Sathish, Seattle Genetics, Inc.

AD-104. A Simple SAS Utility to Combine Existing RTF Tables/Figures and Create a Multi-level Bookmark Hierarchy and a Hyperlinked TOC
Lugang Larry Xie, Johnson & Johnson

AD-107. Auto-generation of Clinical Laboratory Unit Conversions
Alan Meier, Cytel

AD-109. Tool Development Methods for Implementing and Converting to New Controlled Terminology in SDTM datasets
Martha O'Brien, Reata Pharmaceuticals
Keith Shusterman, Reata Pharmaceuticals

AD-111. Learning SAS® GTL Basics with Practical Examples
Jinit Mistry, Seattle Genetics, Inc.

AD-118. Automated Dynamic Data Exchange (DDE) Replacement Solution for SAS® GRID
Ajay Gupta, PPD

AD-121. The Application of SAS-Excel Handshake in DDT
Maggie Ci Jiang, Teva Pharmaceuticals

AD-129. Automate the Mundane: Using Python for Text Mining
Nathan Kosiba, Rho, Inc.

AD-136. Why we should learn Python
Kevin Lee, Clindata Insight

AD-159. Automate the Process to Ensure the Compliance with FDA Business Rules in SDTM Programming for FDA Submission
Xiangchen (Bob) Cui, Alkermes Inc.
Hao Guan, Alkermes Inc.
Min Chen, Alkermes Inc.
Letan (Cleo) Lin, Alkermes Inc.

AD-197. Create Interactive Data Visualizations for Clinical Data Review Using Base SAS® and Javascript
Raj Kiran Boddu, Takeda

AD-203. Large-scale TFL Automation for regulated Pharmaceutical trials using CDISC Analysis Results Metatadata (ARM)
Stuart Malcolm, Frontier Science (Scotland) Ltd

AD-208. Define-XML with ARM
Lei Jing, FMD K&L Inc.
Chao Wang, FMD K&L Inc.

AD-211. Validating Hyperlinks in SDTM define.xml Using Python
Brandon Welch, Rho, Inc.
Greg Weller, Rho, Inc.

AD-215. Use of SAS Merge in Adverse Events Reporting for DSUR
Andrew Wang, Celgene

AD-228. User-Defined Multithreading with the SAS® DS2 Procedure: Performance Testing DS2 Against Functionally Equivalent DATA Steps
Troy Hughes, Datmesis Analytics

AD-234. Camouflage your Clinical Trial with Machine Learning and AI
Ajith Baby Sadasivan, Genpro Life Sciences
Limna Salim, Genpro Life Sciences
Akhil Vijayan, Genpro Life Sciences
Anoop Ambika, Genpro Life Sciences

AD-278. Creating a DOS Batch File to Run SAS® Programs
David Franklin, IQVIA

AD-279. Statistical application in Image Processing by Integrating C and SAS
Vidhyavathi Venkataraman, Biomarin Pharmaceuticals
Srinand Ponnathapura Nandakumar, Alder Pharmaceuticals
Anupama Datta, TransUnion

AD-299. Best Practices for ISS/ISE Dataset Development
Bharath Donthi, Statistics & Data Corporation
Lingjiao Qi, Statistics & Data Corporation

AD-316. A Utility to Automate Reconciliation of Report Numbers and Titles
Valerie Williams, ICON Clinical Research
Ganesh Prasad, ICON Clinical Research

AD-326. Interactive TLFs - A Smarter Way to Review your Statistical Outputs
Bhavin Busa, Vita Data Sciences

AD-341. Time Since Last Dose-Anatomy of a SQL Query
Derek Morgan, PAREXEL International



Data Standards

DS-049. Streamlining the Metadata Management Process Using SAS® Life Science Analytics Framework
Alex Ford, SAS

DS-055. Achieving Zen: A Journey to ADaM Compliance
Kjersten Offenbecker, Clinical Solutions Group (CSG)
Alice Ehmann, Clinical Solutions Group (CSG)
Kirsty Lauderdale, Clinical Solutions Group (CSG)

DS-082. Incremental Changes: ADaMIG v1.2 Update
Nancy Brucken, Syneos Health
Brian Harris, MedImmune
Terek Peterson, Covance
Alyssa Wittle, Covance
Deb Goodfellow, Covance

DS-087. Strategy to Evaluate the Quality of Clinical Data from CROs
Charley Wu, Atara Biotherapeutics

DS-088. Pacemaker Guy: De-Mystifying a Business Use Case for SDTM Standard and Medical Device Domains
Carey Smoak, S-Cubed
Donna Sattler, Bristol Myers Squibb
Fred Wood, Data Standards Consulting Group

DS-119. Common Pinnacle 21 Report Issues: Shall we Document or Fix?
Ajay Gupta, PPD

DS-146. Considerations when Representing Multiple Subject Enrollments in SDTM
Kristin Kelly, Pinnacle 21
Mike Hamidi, CDISC

DS-148. 7 Habits of Highly Effective (Validation Issue) Managers
Amy Garrett, Pinnacle 21

DS-151. Bidirectionality to LOINC: Handling the Nitty Gritty of Lab Data
Bhargav Koduru, Seattle Genetics, Inc.

DS-173. Forewarned is forearmed or how to deal with ADSL issues
Anastasiia Oparii, Experis / Intego Group

DS-185. Leveraging Intermediate Data Sets to Achieve ADaM Traceability
Yun (Julie) Zhuo, PRA Health Sciences

DS-196. Practical Guide for Creating ADaM Datasets in Cross-over Studies
Neha Sakhawalkar, Rang Technologies
Kamlesh Patel, Rang Technologies

DS-202. This Paper focuses on CDISC Questionnaires, Ratings and Scales (QRS) supplements and types of FDA Clinical Outcome Assessments
Shrishaila Patil, Quanticate

DS-223. Homogenizing Unique and Complex data into Standard SDTM Domains with TAUGs
Sowmya Srinivasa Mukundan, Ephicacy Lifesciences Analytics
Charumathy Sreeraman, Ephicacy Lifesciences Analytics

DS-239. More Traceability: Clarity in ADaM Metadata and Beyond
Wayne Zhong, Accretion Softworks
Richann Watson, DataRich Consulting
Daphne Ewing, CSL Behring
Jasmine Zhang, Boehringer Ingelheim

DS-250. Timing is Everything: Defining ADaM Period, Subperiod and Phase
Nancy Brucken, Syneos Health

DS-254. Findings About: De-mystifying the When and How
Soumya Rajesh, Syneos Health
Michael Wise, Syneos Health

DS-261. Raising the Bar: CDASH implementation in a biometrics CRO
Julie Barenholtz, Cytel

DS-268. Best Practices in Data Standards Governance
Melissa Martinez, SAS

DS-304. Considerations and Updates in the Use of Timing Variables in Submitting SDTM-Compliant Datasets
Jerry Salyers, TalentMine

DS-308. Using CDISC Standards with an MDR for EDC to Submission Traceability
Paul Slagle, Syneos Health
Eric Larson, Syneos Health

DS-311. What's New in the SDTMIG v3.3 and the SDTM v1.7
Fred Wood, Data Standards Consulting Group

DS-319. Updates on validation of ADaM data
Sergiy Sirichenko, Pinnacle 21

DS-336. Metadata Repository V1.0 – A Case Study in Standards Governance
Aparna Venkataraman, Celgene

DS-344. Panel Discussion: Medical Devices - Implementation Through Submission
Fred Wood, Data Standards Consulting Group
Carey Smoak, S-Cubed
Donna Sattler, Bristol Myers Squibb
Karin Lapann, Takeda
Mike Lozano, Eli Lilly and Company
Karl Miller, Syneos Health

DS-346. Implementing CDISC Standards for Device-Drug Studies
Karin Lapann, Takeda
Wenying Tian, Takeda



e-Posters

PO-020. Tame your SHARE with a PYTHON and SAS
Michael Stackhouse, Covance
Terek Peterson, Covance

PO-022. In the Style Of David Letterman's "Top Ten" Lists, Our "Top Ten" PROC SQL Statements To Use in Your SAS Program
Margie Merlino, Janssen Research and Development

PO-037. Advanced Project Management beyond Microsoft Project, Using PROC CPM, PROC GANTT, and Advanced Graphics
Stephen Sloan, Accenture
Lindsey Puryear, SAS

PO-050. Put on the SAS® Sorting Hat and Discover Which Sort is Best for You!
Louise Hadden, Abt Associates Inc.
Charu Shankar, SAS

PO-066. Using Pinnacle 21 Enterprise for define.xml Creation: Tips and Tricks from a CRO Perspective.
Frank Menius, Covance

PO-108. Developing Analysis & Reporting Standards For Pharmaco-Epidemiology Observational Studies
Bo Zheng, Merck & Co., Inc.
Xingshu Zhu, Merck & Co., Inc.

PO-110. Raw data sets tracker: Time and project management based on the volume of available clinical data using SAS® software
Girish Kankipati, Seattle Genetics, Inc.

PO-130. When biomarker drives primary endpoint: An oncology case study of SDTM design using multiple myeloma.
Girish Kankipati, Seattle Genetics, Inc.
Bhargav Koduru, Seattle Genetics, Inc.

PO-137. A Practical SAS® Macro for Converting RTF to PDF Files
Kaijun Zhang, FMD K&L Inc.
Xiao Xiao, FMD K&L Inc.
Brian Wu, FMD K&L Inc.

PO-144. SDSP (Study Data Standardization Plan) Case Studies and Considerations
Kiran Kundarapu, Merck & Co., Inc.

PO-218. A Cloud-based Framework for Exploring Medical Study Data
Peter Schaefer, VCA-Plus, Inc

PO-221. Why waiting longer to check log file when SAS program in Execution? Lets Find bugs Early!!
Prakash Subramanian, Quartesian Clinical Research
Thamarai Selvan, Quartesian Clinical Research

PO-225. Badge in Batch with Honeybadger: Generating Conference Badges with Quick Response (QR) Codes Containing Virtual Contact Cards (vCards) for Automatic Smart Phone Contact List Upload
Troy Hughes, Datmesis Analytics

PO-253. F2Plots: Visualizing relative treatment effects in cancer clinical trials
Yellareddy Badduri, QUARTESIAN

PO-274. A Macro to Expand Encrypted Zip Files on the SAS LSAF Environment
Steven Hege, Alexion Pharmaceuticals, Inc.

PO-277. Flagging On-Treatment Events in a Study with Multiple Treatment Periods
David Franklin, IQVIA

PO-282. Joining the SDTM and the SUPPxx Datasets
David Franklin, IQVIA

PO-305. Merging Sensor Data with Patient Records in Clinical Trials – Systems and Benefits
Surabhi Dutta, Eliassen Biometrics and Data Solutions
Shubhranshu Dutta, Student at Biomedical Sciences Academy, HCVSD

PO-324. Bayesian Methods for Treatment Design in Rare Diseases
Xuan Sun, Ultragenyx
Ruohan Wang, Ultragenyx



Hands-on Training

HT-063. Developing Custom SAS Studio Tasks for Clinical Trial Graphs
Olivia Wright, SAS
Sanjay Matange, SAS, LinkedIn

HT-067. Integrating SAS and Microsoft Excel: Exploring the Many Options Available to You
Vince Delgobbo, SAS

HT-089. Build Popular Clinical Graphs using SAS
Sanjay Matange, SAS, LinkedIn

HT-145. Hands-on Training for Machine Learning Programming
Kevin Lee, Clindata Insight

HT-171. Value-Level Metadata Done Properly
Sandra Minjoe, PRA Health Sciences
Mario Widel, Independent

HT-177. Sample Size Determination with SAS® Studio
Bill Coar, Axio Research

HT-188. Creating & Sharing Shiny Apps & Gadgets
Phil Bowsher, RStudio Inc.
Kelly O'Briant, RStudio

HT-329. Interactive Graphs
Kriss Harris, SAS Specialists Ltd.
Richann Watson, DataRich Consulting

HT-347. The Shape of SAS® Code
Charu Shankar, SAS



Leadership and Career Development

LD-023. Attracting and Retaining the Best!
Kelly Spak, Covance

LD-106. Considering Job Changes in an Ever-Changing Environment
Kathy Bradrick, Triangle Biostatistics, LLC
Ed Slezinger, Omeros Corporation

LD-150. The human side of programming: Empathetic leaders build better teams.
Bhargav Koduru, Seattle Genetics, Inc.
Balavenkata Pitchuka, Seattle Genetics, Inc.

LD-155. Working from a Home Office Versus Working On-Site
Timothy Harrington, SAS Programmer

LD-174. It’s a wonderful day in this neighbourhood – Managing a large virtual programming team
Victoria Holloway, Covance

LD-200. Find Your Story
Adam Sales, PRA Health Sciences

LD-207. Improving the Relationship between Statisticians and Programmers in Clinical Trial Studies
Mai Ngo, Catalyst Clinical Research, LLC
Mary Grovesteen, Triangle Biostatistics, LLC
Vaughn Eason, Catalyst Clinical Research, LLC

LD-224. Pains and Gains in software development - from PoC to Market
Reshma Rajput, Ephicacy Lifesciences Analytics
Charan Kumar Kuyyamudira Janardhana, Ephicacy Lifesciences Analytics

LD-252. Statistical Programming Roles – Time to Reevaluate Job Profiles & Career Ladders
Vijay Moolaveesala, PPD
Ajay Gupta, PPD

LD-288. Project Management Fundamentals for Programmers and Statisticians
Jennifer Sniadecki, Covance

LD-295. Advance Your Career with PROC TM!
John Labore, Consultant
Josh Horstman, Nested Loop Consulting

LD-296. Time to COMPARE Programmer to Analyst: Examine the Differences and Decide Best Path Forward
Ginger Barlow, UBC
Carol Matthews, UBC

LD-313. Schoveing Series 4: Inspirational Leadership: Grow Yourself into a Class Act and an Unforgettable Leader!
Priscilla Gathoni, AstraZeneca Pharmaceuticals

LD-335. Something Old, Something New: A little programming management can go a long way
Janet Li, Pfizer

LD-342. Panel Discussion: Speaking Data Science, Who is Ready to Listen?
Priscilla Gathoni, AstraZeneca Pharmaceuticals
David D’attilio, TalentMine
Phil Bowsher, RStudio Inc.
Kevin Lee
Faisal Khan, AstraZeneca Pharmaceuticals
Yuri Pinzon, Teradata



Programming Techniques

BP-029. Lit Value Locator: An efficient way to pinpoint data.
Varunraj Khole, Thomas Jefferson University

BP-036. Reducing the space requirements of SAS® data sets without sacrificing any variables or observations
Stephen Sloan, Accenture

BP-039. It’s All About the Base—Procedures
Jane Eslinger, SAS

BP-040. Running Parts of a Program while Preserving the Entire Program
Stephen Sloan, Accenture

BP-057. The Power of PROC FORMAT
Jonas Bilenas, A Bank Near You
Kajal Tahiliani, GlaxoSmithKline

BP-061. Proc Sort Revisited
Alex Chaplin, Bank of America

BP-065. ODS Magic: Using Lesser Known Features of the ODS statement
Michael Stout, Johnson & Johnson Medical Device Companies

BP-079. Performing Analytics on Free-Text Data Fields: A Programer's Wurst Nitemare
Michael Rimler, GlaxoSmithKline
Matt Pitlyk, 1904labs

BP-084. Useful SAS techniques in Efficacy Analysis for Oncology studies
Joy Zeng, Pfizer

BP-105. ADaM 1.1 Compliant ADEVENT and ADTTE development in a Cardiovascular Study
Chao Su, Merck & Co., Inc.

BP-115. Freq Out - Proc Freq’s Quick Answers to Common Questions
Christine Mcnichol, Covance

BP-124. A Quick Way to Cross Check Listing Outputs
Shunbing Zhao, Merck & Co., Inc.

BP-127. Importing EXCEL Data in Different SAS Maintenance Release Version
Huei-Ling Chen, Merck & Co., Inc.
Chao-Min Hoe, Merck & Co., Inc.

BP-128. Implementing Laboratory Toxicity Grading for CTCAE Version 5
Keith Shusterman, Reata Pharmaceuticals
Mario Widel, Independent

BP-132. Code Generators: Friend or Foe
Janet Stuelpner, SAS

BP-133. A SAS® Macro to Provide Survival Functions along with Cox Regression Model Efficiently
Chia-Ling Ally Wu, Seattle Genetics, Inc.

BP-141. The Knight's Tour in 3-Dimensional Chess
John R Gerlach, Dataceutics, Inc.
Scott M Gerlach, Dartmouth College

BP-147. Patient Profile with Color-Coded Track Changes Since Last Review
Himanshu Patel, Merck & Co., Inc.
Jeff Xia, Merck & Co., Inc.

BP-175. Create publication-ready variable summary table using SAS macro
[Additional Materials (ZIP Archive)]
Geliang Gan, Yale Center for Analytical Sciences

BP-181. Sum Fun with Flags! Sum Any Flagged Occurrence Data with FLAGSUM and Report It with FLAGRPT or PROC REPORT.
[Additional Materials (ZIP Archive)]
Brendan Bartley, Harvard T.H. Chan School of Public Health

BP-182. Compare and conquer SDTM coding
Phaneendhar Gondesi, TechData Service Company LLC

BP-194. Macro Templates - Industry Specific SAS® Programming Standardization
Tabassum Ambia, Alnylam Pharmaceuticals, Inc

BP-219. Making the Days Count: Counting Distinct Days in Overlapping or Disjoint Date Intervals
[Additional Materials (ZIP Archive)]
Noory Kim, Synteract

BP-227. From Lesion size to Best Response - Implementing RECIST through programming
Ankit Pathak, Rang Technologies

BP-255. End of Computing Chores with Automation: SAS© Techniques That Generate SAS© Codes
Yun (Julie) Zhuo, PRA Health Sciences

BP-260. SMQ SAS Dataset Macro
Mi Young Kwon, Regeneron, Inc.
Ishan Shah, PRA Health Sciences

BP-286. One More Paper on Dictionary Tables and Yes, I Think it Is Worth Reading
Vladlen Ivanushkin, DataFocus GmbH

BP-289. Let Your Log Do the Work for You
Yuliia Bahatska, PRA Health Sciences
Vladlen Ivanushkin, DataFocus GmbH

BP-302. History Carried Forward, Future Carried Back: Mixing Time Series of Differing Frequencies
Mark Keintz, Wharton Research Data Services

BP-307. An Overview of Three New Output Delivery System Procedures in SAS® 9.4: ODSTABLE, ODSLIST and ODSTEXT
Lynn Mullins, PPD

BP-315. Using the PRXCHANGE Function to Remove Dictionary Code Values from the Coded Text Terms
Lynn Mullins, PPD

BP-340. Programmatically mapping source variables to output SDTM variables based upon entries in a standard specifications Excel file
Frederick Cieri, Clinical Solutions Group (CSG)
Rama Arja, MedImmune
Zev Kahn, Clinical Solutions Group (CSG)
Ramesh Karuppusamy, Theorem Clinical Research



Real World Evidence

RW-179. Using Real-World Evidence to Affect the Opioid Crisis
Sherrine Eid, SAS
Andrea Coombs, SAS

RW-192. Stratified COX Regression: Five-year follow-up of attrition risk among HIV positive adults, Bamako
Mamadou Dakouo, DATASTEPS
Kriss Harris, SAS Specialists Ltd.
Seydou Moussa Coulibaly Coulibaly, HOSPITAL

RW-199. Patterns of risk factors and drug treatments among Hypertension patients
Youngjin Park, SAS

RW-232. Artificial Intelligence and Real World Evidence - it takes two to tango
Charan Kumar Kuyyamudira Janardhana, Ephicacy Lifesciences Analytics

RW-238. Innovative Technologies utilization in 21st Novel Clinical Research programs towards Generation of Real World Data.
Srinivasa Rao Mandava, Merck & Co., Inc.

RW-310. Real-world data as real-world evidence: Establishing the meaning of data as a prerequisite to determining secondary-use value
Jennifer Popovic, RTI International

RW-345. Applications and Their Limitations of Real-World Data in Gene Therapy Trials
Karen Ooms, Quanticate



Reporting and Data Visualizations

DV-002. Order, Order! Four Ways To Reorder Variables with SAS®, Ranked by Elegance and Efficiency.
Louise Hadden, Abt Associates Inc.

DV-003. With a Trace: Making Procedural Output and ODS Output Objects Work For You
Louise Hadden, Abt Associates Inc.

DV-005. Back to the Future: Heckbert's Labeling Algorithm
Chris Smith, Cytel

DV-021. Applying an Experimental GTL Feature to CONSORT Diagrams
Shane Rosanbalm, Rho, Inc.

DV-024. Free Duplicates Here! Get Your Free Duplicates!
Kristen Harrington, Rho, Inc.

DV-090. Effective Graphical Representation of Tumor Data
Sanjay Matange, SAS, LinkedIn

DV-131. An Innovative Efficacy Table Programming to Automate Its Figure Generation to Ensure Both High Quality and Efficiency
Xiangchen (Bob) Cui, Alkermes Inc.
Letan (Cleo) Lin, Alkermes Inc.

DV-164. Heat Map and Map Chart using TIBCO Spotfire®
Ajay Gupta, PPD

DV-169. The Power of Data Visualization in R
Oleksandr Babych, Experis Clinical

DV-184. Figure it out! Using significant figures from reported lab data to format TLF output
Elizabeth Thomas, Everest Clinical Research, Inc.
Lauren Williams, Everest Clinical Research, Inc.

DV-214. DOMinate your ODS Output with PROC TEMPLATE, ODS Cascading Style Sheets (CCS), and the ODS Document Object Model (DOM)
Louise Hadden, Abt Associates Inc.
Troy Hughes, Datmesis Analytics

DV-220. How to Build a Complicated Patient Profile Graph by Using Graph Template Language: Turn Mystery to a LEGO Game
Ruohan Wang, Ultragenyx
Chris Qin, Ultragenyx

DV-276. Not That Dummy Data
Yuliia Bahatska, PRA Health Sciences

DV-285. Forest Plots for Beginners
Savithri Jajam, Chiltern
Olesya Masucci, Chiltern

DV-297. Building Automations for Generating R and SAS Code Supporting Visualizations Across Multiple Therapeutic Areas
Anastasia Alexeeva, Eli Lilly and Company
Mei Zhao, Eli Lilly and Company
William Martersteck, Eli Lilly and Company

DV-323. Fine-tuning your swimmer plot: another example from oncology
Steve Almond, Bayer Inc.

DV-332. Visualize Overall Survival and Progression Free Survival at the Same Time!
Kriss Harris, SAS Specialists Ltd.

DV-349. Power Up Your Reporting Using the SAS® Output Delivery System
Chevell Parker



Statistics and Analytics

ST-058. Logistic and Linear Regression Assumptions: Violation Recognition and Control
Deanna Schreiber-Gregory, Henry M Jackson Foundation for the Advancement of Military Medicine
Karlen Bader, Henry M Jackson Foundation for the Advancement of Military Medicine

ST-059. Regulation Techniques for Multicollinearity: Lasso, Ridge, and Elastic Nets
Deanna Schreiber-Gregory, Henry M Jackson Foundation for the Advancement of Military Medicine
Karlen Bader, Henry M Jackson Foundation for the Advancement of Military Medicine

ST-060. Jump Start your Oncology knowledge
Xiaoyin Zhong, GlaxoSmithKline
Feng Liu, AstraZeneca Pharmaceuticals

ST-081. Let’s Flip: An Approach to Understand Median Follow-up by the Reverse Kaplan-Meier Estimator from a Programmer’s Perspective
Nikita Sathish, Seattle Genetics, Inc.
Chia-Ling Ally Wu, Seattle Genetics, Inc.

ST-091. Equivalence, Superiority and Non-inferiority with Classical Statistical Tests: Implementation and Interpretation
Marina Komaroff, Noven Pharmaceuticals

ST-096. A macro of evaluating the performance of the log-rank test using different weight for enrichment studies
[Additional Materials (ZIP Archive)]
Chuanwu Zhang, University of Kansas
Byron Gajewski, University of Kansas Medical Center
Jianghua(Wendy) He, University of Kansas Medical Center

ST-103. SAS® V9.4 MNAR statement for multiple imputations for missing not at random in longitudinal clinical trials
Lingling Li, Independent

ST-149. Application of R Functions in SAS to Estimate Dose Limiting Toxicity Rates for Early Oncology Dose Finding
Huei-Ling Chen, Merck & Co., Inc.
Zhen Zeng, Merck & Co., Inc.

ST-160. Experiences in Building CDISC Compliant ADaM Dataset to Support Multiple Imputation Analysis for Clinical Trials
Xiangchen (Bob) Cui, Alkermes Inc.

ST-176. Practical Perspective in Sample Size Determination
Bill Coar, Axio Research

ST-183. Cluster Analysis - What it is and How to use it
Alyssa Wittle, Covance
Michael Stackhouse, Covance

ST-213. Statistical Assurance in SAS: An Introduction and User's Guide
Jonathan L Moscovici, IQVIA
Milena Kurtinecz, GlaxoSmithKline

ST-259. Enhancing Randomization Methodology Decision-Making with SAS Simulations
Kevin Venner, Almac Clinical Technologies
Jennifer Ross, Almac Clinical Technologies
Graham Nicholls, Almac Clinical Technologies
Kyle Huber, Almac Clinical Technologies

ST-314. Application of Criterion I2 in Clinical Trials Using SAS®
Igor Goldfarb, Accenture
Mitchell Kotler, Accenture

ST-321. PROC MIXED: Calculate Correlation Coefficients in the Presence of Repeated Measurements
Qinlei Huang, Merck & Co., Inc.
Radha Railkar, Merck & Co., Inc.

ST-325. Machine Learning Approaches to Identify Rare Diseases
Xuan Sun, Ultragenyx
Ruohan Wang, Ultragenyx

ST-339. An Introduction to the Process of Improving a Neural Network
Yuting Tian, Student

ST-348. Comparing SAS® Viya® and SAS® 9.4: How Their Features Complement Each Other
Amy Peters, SAS



Strategic Implementation, Business Administration, Support Resources

SI-017. Avoiding Disaster: Manager’s Guide on How to Rescue a Failing Outsourced Project
Dilip Raghunathan, Insmed

SI-062. Get to the Meat on Machine Learning
Aadesh Shah, GlaxoSmithKline

SI-075. SHIONOGI Global SAS System Renewal Project – How to Improve Statistical Programming Platform
Yura Suzuki, Shionogi & Co., Ltd.
Yoshimi Ishida, Shionogi Digital Science
Malla Reddy Boda, Shionogi Inc.
Yoshitake Kitanishi, Shionogi & Co., Ltd.

SI-099. ISS Challenges and Solutions for a Compound with Multiple Submissions in Parallel
Aiming Yang, Merck & Co., Inc.

SI-142. Sponsor oversight: Proof is in the documents
Shailendra Phadke, Servier US

SI-161. Lessons Learned from Teaching 250+ Life Science Analytics (LSAF) Classes to Our Colleagues at Janssen Research and Development.
Margie Merlino, Janssen Research and Development
Jeanne Keagy, Janssen Research and Development

SI-168. Embedded Processes – evolving face of QUALITY in the world of Robotic Process Automation (RPA).
Charan Kumar Kuyyamudira Janardhana, Ephicacy Lifesciences Analytics

SI-190. Integrating programming workflow into computing environments: A closer look
Tyagrajan Swaminathan, Ephicacy Lifesciences Analytics
Sridhar Vijendra, Ephicacy Lifesciences Analytics

SI-243. Dataset Specifications: Recipes for Efficiency and Quality
Dave Scocca, Rho, Inc.

SI-257. Using freelancers in the programming world – Challenges and opportunities
Vijay Moolaveesala, PPD

SI-292. Throw Away the Key: Blockchain-ed Healthcare Data
Kathy Zhai, GlaxoSmithKline

SI-300. Don’t Just Rely on Processes; Support Local Subject Matter Expertise
Deidre Kreifels, Reata Pharmaceuticals
Steve Kirby, Reata Pharmaceuticals
Mario Widel, Independent

SI-320. Vendor’s Guide to Consistent, Reliable, and Timely CDISC Deliverables
Dharmendra Tirumalasetti, Vita Data Sciences
Santosh Lekkala, Vita Data Sciences
Bhavin Busa, Vita Data Sciences

SI-327. Begin with the End of Validation: Adapting QbD Approach in Statistical Programming to Achieve Quality and Compliance Excellence
Linghui Zhang, PRA Health Sciences



Submission Standards

SS-014. China NMPA (National Medical Products Administration) reform and new regulations/guidelines/requirements
Yi Yang, Novartis

SS-027. Progression-Free Survival (PFS) Analysis in Solid Tumor Clinical Studies
Na Li, Na Li Clinical Programming Services

SS-030. Clinical Development Standards for FDA Bioresearch Monitoring (BIMO) Submissions
Denis Michel, Janssen Research and Development
Julie Maynard, Janssen Research and Development

SS-056. Practical Guidance for ADaM Dataset Specifications and Define.xml
Jack Shostak, DCRI

SS-068. Enforcing Standards in an Organization: A Practical 6 Step-Approach
Priscilla Gathoni, AstraZeneca Pharmaceuticals
Dany Guerendo Christian, STATProg Inc.

SS-092. A Practical Guide to the Issues Summary in the Data Conformance Summary of Reviewer’s Guides
Gary Moore, Moore Computing Services, Inc.

SS-117. Have You Met Define.xml 2.0?
Christine Mcnichol, Covance

SS-120. An Automated, Metadata Approach to Electronic Dataset Submissions
Janette Garner, Kite Pharma, A Gilead Company

SS-126. Considerations in Effectively Generating PK Analysis Input Datasets
Jianli Ping, Gilead Sciences, Inc.

SS-134. Next Innovation in Pharma - CDISC data and Machine Learning
Kevin Lee, Clindata Insight

SS-153. Exploring Common CDISC ADaM Conformance Findings
Trevor Mankus, Pinnacle 21

SS-162. Multiple Studies BIMO Submission Package – A Programmer’s Perspective
Ramanjulu Valluru, Accenture
Harsha Dyavappa, Accenture

SS-172. Pharmacokinetic Parameters for Sparse and Intensive Sampling – Nonclinical and Clinical Studies
Shallabh Mehta, PPD

SS-217. Process optimization for efficient and smooth e-data submissions to both FDA and PMDA
Eri Sakai, Shionogi & Co., Ltd.
Malla Boda, Shionogi Inc.
Akari Kamitani, SHIONOGI & CO., LTD.
Yoshitake Kitanishi, SHIONOGI & CO., LTD.

SS-226. De-Identification of Data & It’s Techniques
Shabbir Bookseller, Quartesian Clinical Research

SS-240. Sponsor Considerations for Building a Reviewer’s Guide to Facilitate BIMO (Bioresearch Monitoring) Review
Kiran Kundarapu, Merck & Co., Inc.
Janet Low, Merck & Co., Inc.
Majdoub Haloui, Merck & Co., Inc.

SS-270. Designing Flexible Data Standards Models
Melissa Martinez, SAS

SS-273. The Need for Therapeutic Area User Guide Implementation
Michael Beers, Pinnacle 21

SS-291. Information Requests During An FDA Review
Hong Qi, Merck & Co., Inc.
Lei Xu, Merck & Co., Inc.
Mary N. Varughese, Merck & Co., Inc.

SS-306. Making Lab Toxicity Tables Less Toxic on Your Brain
Lindsey Xie, Kite Pharma, a Gilead Company
Jinlin Wang, Kite Pharma, a Gilead company
Jennifer Sun, Kite Pharma, a Gilead company
Rita Lai, Kite Pharma, a Gilead company
Richann Watson, DataRich Consulting

SS-309. Expediting Drug Approval: Real Time Oncology Review Pilot Program
Laxmi Samhitha Bontha, Lamar University

SS-317. Non-Clinical (SEND) Reference Guide for Clinical (SDTM) Programmers
Dharmendra Tirumalasetti, Vita Data Sciences
Bhavin Busa, Vita Data Sciences

SS-318. How to use SUPPQUAL for specifying natural key variables in define.xml?
Sergiy Sirichenko, Pinnacle 21

SS-328. Framework for German Dossier Submissions
Kriss Harris, SAS Specialists Ltd.

SS-331. A Standardized Data Sample: Key to Improving the Submission Strategy
Prafulla Girase, Biogen
Joanna Koft, Biogen

SS-334. The Anatomy of Clinical Trials Data: A Beginner’s Guide
Venky Chakravarthy, BioPharma Data Services

SS-337. Do-It-Yourself CDISC! A Case Study of Westat’s Successful Implementation of CDISC Standards on a Fixed Budget
Rick Mitchell, Westat
Rachel Brown, Westat
Jennifer Fulton, Westat
Marie Alexander, Westat
Stephen Black, Westat

SS-343. Panel Discussion: Recent Submission Experiences around the World
Carey Smoak, S-Cubed
Kriss Harris, SAS Specialists Ltd.
Marianne Caramés, Novo Nordisk
Yi Yang, Novartis
David Izard, Chiltern
Karin Lapann, Takeda