Baltimore, Maryland
May 14-17, 2017


Applications Development

AD01. Here Comes The Smart Mock Table: A Novel Way of Creating Clinical Summary Tables Without Any Table Programming (No Kidding!)
*** BEST PAPER ***
Joseph Hinson, inVentiv Health

AD02. Automated Generation of Clinical Study Reports using SAS® and RTF (Literate programming)
Rajaram Venkatesan, Cognizant Technology Solution
Julien Sauser, Nestle Research Center
Carlos Antonio De Castro, Nestle Research Center

AD03. Three Issues and Corresponding Work-Around Solution for Generating Define.xml 2.0 Using Pinnacle 21 Enterprise
Jeff Xia, Merck
Lugang Larry Xie, Merck & Co.
Shari Lisnov, Merck &Co.

AD04. A Vivid and Efficient Way to Highlight Changes in SAS Dataset Comparison
Jeff Xia, Merck
Lugang Larry Xie, Merck & Co.
Shunbing Zhao, Merck & Co.

AD05. An Efficient Solution to Efficacy ADaM Design and Implementation
Chengxin Li, Pfizer
Zhongwei Zhou, Pfizer

AD06. Obtaining an Automated Summary of PROC COMPARE Results: &SYSINFO and VB Script
Umesh Gautam, Trial Runners
Jeff Roberts, Chiltern International

AD07. Work with me here...(or there or anywhere): Practical Cloud Collaboration with JMP Clinical for Clinical Trial Data Reviews
Kelci Miclaus, SAS
Drew Foglia, SAS Institute, Inc.

AD08. Building a Better Dashboard Using SAS® Base Software
Kirk Paul Lafler, Software Intelligence Corporation
Josh Horstman, Nested Loop Consulting
Roger Muller, Data To Events, Inc

AD09. Important and Valuable Things You Can Do with SAS® Metadata DICTIONARY Tables and SASHELP Views
Kirk Paul Lafler, Software Intelligence Corporation

AD10. Laboratory Data Standardization with SAS
*** BEST PAPER ***
Charley Wu, Astellas

AD11. Generating Homeomorphically Irreducible Trees (Solving the Blackboard Problem in the Movie "Good Will Hunting")
John R Gerlach, Dataceutics, Inc.

AD12. Using SAS® ODS EXCEL Destination with SAS University Edition® to send graphs to Excel
William E Benjamin Jr, Owl Computer Consultancy LLC

AD13. Using SAS® for Application Programming Interface Requests
Mike Jadoo, SAS user

AD14. R Shiny Clinical Review Tools on the Horizon (slides)
Jimmy Wong, FDA

AD15. Excel-VBA Tool to Auto-Create Validation log and Review Form using List of TLF's.
Balaji Ayyappan, inVentiv Clinical

AD16. Migration to SAS Grid: Steps, Successes, and Obstacles for Performance Qualification Script Testing
Amanda Lopuski, Chiltern
Yongxuan Mike Tan, Chiltern

AD17. Metadata integrated programming
Jesper Zeth, Novo Nordisk A/S
Jan Skowronski, Novo Nordisk A/S

AD18. Leveraging Centralized Programming Resources Using SAS Integration Technologies
Tony Chang, Global Statistical Programming, Amgen Inc

AD19. SAS Application to Automate a Comprehensive Review of DEFINE and All of its Components
Walter Hufford, Novartis Pharmaceuticals
Vincent Guo, Novartis Pharmaceuticals
Mijun Hu, Novartis Pharmaceuticals

AD20. Challenge for Dramatic Streamlining of TLFs Creation Process with SAS and Java
Yohei Takanami, Takeda Pharmaceutical Company, Ltd.
Fumihiro Yamasaki, Takeda Pharmaceutical Company, Ltd.

AD21. Integration of multiple files into a study report using Word VBA macros
Heather Wood, DCRI
Jack Shostak, DCRI

AD22. A novel method to track mapping of all CRF variables into SDTM datasets.
Aishhwaryapriya Elamathivadivambigai, Seattle Genetics

AD23. Supporting the CDISC Validation Life-Cycle with Microsoft Excel VBA
Eric Crockett, Chiltern International

AD24. SAS Macro for Derivation of Best Overall Response per RECIST v. 1.1
Bob Zhong, Johnson & Johnson
Jiangfan Li, Johnson & Johnson
Hong Xie, Johnson & Johnson
Peter De Porre, Johnson & Johnson
Kenneth Maahs, Johnson & Johnson
Kyounghwa Bae, Johnson & Johnson

AD25. Controlled Terminology Without Excel
Mike Molter, Wright Ave Partners

AD26. Stop waiting - Get notification email at the end of SAS® code execution using SAS® EMAIL Engine
Nirav Darji, GCE Solutions pvt ltd



Beyond the Basics

BB01. One Project, Two Teams: The Unblind leading the Blind
Kristen Harrington, Rho, Inc.

BB02. Making Documents 'Intelligent' with Embedded Macro Calls, DOSUBL and Proc STREAM: An example with the CONSORT Flow Diagram
*** BEST PAPER ***
Joseph Hinson, inVentiv Health

BB03. The REPORT Procedure and ODS Destination for Microsoft Excel: The Smarter, Faster Way to Create First-Rate Excel Reports
Jane Eslinger, SAS Institute

BB04. Reporting Non-Printable and Special Characters for Review in Excel
Abhinav Srivastva, Gilead Sciences

BB05. I've Got to Hand It to You; Portable Programming Techniques
Art Carpenter, CA Occidental Consultants

BB06. Good artists copy;Great artists steal; (implement pseudo R ,Jquery & code in Base SAS without installing R or other Applications
Hui Liu, MSD

BB07. Simplifying Your %DO Loop with CALL EXECUTE
Arthur Li, City of Hope

BB08. Using Hash tables for AE search strategies
Vinodita Bongarala, Seattle Genetics
Liz Thomas, Seattle Geneticd

BB09. Expansion of Opportunities in Programming: DS2 Features and Examples of Usage Object Oriented Programming in SAS
Serhii Voievutskyi, Experis Clinical

BB10. A Macro to carry values through observations forwards or backwards over null values within a by group or a SAS(R) dataset.
Timothy Harrington, SAS Programmer

BB11. SAS Programmer's Guide to Life on the SAS Grid
*** BEST PAPER ***
Eric Brinsfield, Meridian Analytics

BB12. Programming LYRIC Response in Immunomodulatory Therapy Trials
Yang Wang, Seattle Genetics

BB13. Harnessing the Power of the Manifest File in the SAS® Life Science Analytics Framework
Kevin Clark, SAS Institute

BB14. A SAS®sy Study of eDiary Data
Amie Bissonett, inVentiv Health Clinical

BB15. A Case of assessing adverse events of interest based on their grade changes
Sriramu Kundoor, Seattle Genetics

BB16. Don't Get Lost! A High-efficiency, Low-tech Solution for Navigating Your Department's Many-Many-Many SOPs and Guidance Documents
Michael Hagendoorn, Amgen, Inc.
Tim Yerington, Amgen, Inc.

BB17. Writing Efficient Queries in SAS Using PROC SQL with Teradata
Mina Chen, Roche

BB18. Clinical Data Visualization using TIBCO Spotfire® and SAS®
Ajay Gupta, PPD Inc

BB20. Automating Title and Footnote Extraction Using Visual Basic for Applications (VBA) and SAS"
Tony Cardozo, Spaulding Clinical

BB21. Beyond IF THEN ELSE: Techniques for Conditional Execution of SAS® Code
Josh Horstman, Nested Loop Consulting



Career Planning

CP01. Creating a Winning Resume Reflecting Your Skills and Experience With Honesty and Integrity.
Kelly Spak, Chiltern International Ltd.

CP02. The Road Not Often Taken
Janet Stuelpner, SAS

CP03. What Makes a Candidate Stand Out?
*** BEST PAPER ***
Edward Slezinger, Fred Hutchinson Cancer Research Center - SCHARP

CP04. The Elusive Data Scientist: Real-world analytic competencies
Greg Nelson, ThotWave

CP05. Strategies and decisions for marketing yourself as an independent contractor
Kathy Bradrick, Triangle Biostatistics, LLC

CP06. The Road Not Taken: SAS for Pharmacometrics
Vishak Subramoney, Certara Strategic Consulting
Sree Harsha Sreerama Reddy, Certara Strategic Consulting

CP07. Becoming a Successful Manager of SAS® Programmers from an Ex-Programmer's Perspective
Christine Young, Chiltern, International

CP08. Schoveing Series 3: Living by Knowing When to STOP
Priscilla Gathoni, AstraZeneca, Statistical Programming

CP09. Show Me The Job!!!
Richelle Serrano, Clindata Insight
Kevin Lee, Clindata Insight



Data Integrity

DA01. Real Time Clinical Trial Oversight with SAS
Ashok Gunuganti, Trevena

DA02. Let's Check Data Integrity Using Statistical (SAS®) Programmers with SAS®
Harivardhan Jampala, chiltern international Pvt ltd

DA03. Conversion of CDISC specifications to CDISC data - specifications driven SAS programming for CDISC data mapping
Yurong Dai, Eli Lilly
Jameson Cai, Eli Lilly

DA04. Data Change Report
Eric Kammer, Novartis

DA05. Clinical and Vendor Database Harmony; Can't we all just get along?
Brian Armstrong, QST Consultations, Ltd.
Renee Kerwin, QST Consultations, Ltd.

DA06. Check Your Data: Tools for Automating Data Assessment
*** BEST PAPER ***
Paul Stutzman, Axio Research

DA07. Data Integrity: One step before SDTM
Pavan Kathula, Anna University at Chennai
Sonal Torawane, University of Pune



Data Standards

DS-Panel. Gray Areas of ADaM and Ways to Provide Color


DS01. The Untapped Potential of the Protocol Representation Model
Frank Diiorio, CodeCrafters, Inc.
Jeffrey Abolafia, Rho, Inc.

DS02. CDISC's CDASH and SDTM: Why You Need Both!
(No paper available)
Kit Howard, CDISC
Shannon Labout, CDISC

DS03. SDTM - Just a Walk in the (Theme) Park, Exploring SDTM in the Most Magical Place on Earth
Christine Mcnichol, Chiltern International

DS04. The CDISC Trial Design Model (TDM), the EPOCH variable, and the Treatment Emergent Flag: How to Leverage these to Improve Review
Thomas Guinter, Independent

DS05. Implementation of STDM Pharmacogenomics/Genetics Domains on Genetic Variation Data
Linghui Zhang, Merck

DS06. Harmonizing CDISC Data Standards across Companies: A Practical Overview with Examples
Keith Shusterman, Chiltern
Prathima Surabhi, AstraZeneca
Binoy Varghese, MedImmune

DS07. Where Is the Link Broken - Another Look at SDTM Oncology Tumor Packages
*** BEST PAPER ***
Hong Wang, Boehringer Ingelheim
Ke Xiao, Boehringer Ingelheim

DS08. The CDISC SDTM Exposure Domains (EX & EC) Demystified. How EC Helps You Produce A Better (more compliant) EX.
Thomas Guinter, Independent

DS09. RELREC - SDTM Programmer's Bermuda Triangle
Charumathy Sreeraman, Ephicacy Lifescience Analytics

DS10. Ahead of the Curve: Leading with Industry Data Requirements
Maria Dalton, GlaxoSmithKline
Nancy Haeusser, GlaxoSmithKline

DS11. Leveraging metadata when mapping to CDISC Standards with SAS® machine learning in a Results as a Service plus Model (RAAS+)
Ben Bocchicchio, SAS Institute
Sandeep Juneja, SAS Institute
Preetesh Parikh, SAS Institute

DS12. Considerations and Conventions in the Submission of the SDTMIG Tumor and Response Domains
Jerry Salyers, Accenture Life Sciences
Fred Wood, Accenture Life Siences

DS13. Planning to Pool SDTM by Creating and Maintaining a Sponsor-Specific Controlled Terminology Database
Cori Kramer, Chiltern International
Ragini Hari, Chiltern International
Keith Shusterman, Chiltern

DS14. Considerations in Submitting Standardized Electronic Data Under the Animal Rule: The Use of Domains in the SDTMIG and the SENDIG
Fred Wood, Accenture Life Siences

DS15. Common Programming Errors in CDISC data
Sergiy Sirichenko, Pinnacle 21

DS16. ADaM Compliance - Validating your Specifications
Trevor Mankus, PRA Health Sciences
Kent Letourneau, PRA Inernational

DS17. ADaM Grouping: Groups, Categories, and Criteria. Which Way Should I Go?
*** BEST PAPER ***
Jack Shostak, DCRI

DS18. Clarifications About ADaM Implementation Provided in ADaMIG Version 1.1
John Troxell, Accenture

DS19. Standardized, Customized or Both? Defining and Implementing (MedDRA) Queries in ADaM Data Sets
Richann Watson, Experis
Karl Miller, inVentiv Health

DS20. LBTEST/LBSTRESU and ADaM lab parameters: The dilemma of mapping one-to-many or many-to-one
Michelle Barrick, Eli Lilly and Company

DS21. Programming Efficiency in the Creation of ADaM BDS Datasets
Ellen Lin, Amgen Inc

DS22. Deriving Rows in CDISC ADaM BDS Datasets
Sandra Minjoe, Accenture

DS23. The Benefits of Traceability Beyond Just From SDTM to ADaM in CDISC Standards
Maggie Ci Jiang, Teva Pharmaceuticals

DS24. ADQRS: Basic Principles for Building Questionnaire, Rating and Scale Analysis Datasets
Nancy Brucken, inVentiv Health Clinical
Karin Lapann, Shire

DS25. A Critique of Implementing the Submission Data Tabulation Model (SDTM) for Drugs and Medical Devices
Carey Smoak, DataCeutics, Inc.



Data Visualizations & Graphics

DV01. Effective Ways to Perfect the Visualization of Clinical Trial Results
Amos Shu, AstraZeneca

DV02. A Combined AE + CM Graph using SAS
Sanjay Matange, SAS

DV03. Multipage Adverse Event Reports Using PROC SGPLOT
Warren Kuhfeld, SAS
Mary Beth Herring, Rho, Inc.

DV04. Mean and Individual Subject Graphs of Concentration vs. Time Data Using PROC SGPLOT
Pooja Trivedi, Cadila Healthcare Limited

DV05. SAS vs Tableau: Creating Adverse Event/ Concomitant Medication Time line plot
Liling Wei, Pharmacyclics
Kathy Chen, Pharmacyclics, Inc. A Abbvie Company

DV06. Visualizing Enrollment Over Time
Laura Gruetzner, BioStat Solutions, Inc.

DV07. Using Animated Graphics to Show PKPD Relationships in SAS 9.4
Andrew Mccarthy, Eli Lilly

DV08. Bird's eye view of the data, a graphical exploration!
Hrideep Antony, Inventiv Health USA

DV09. Mapping Participants to the Closest Medical Center
David Franklin, Quintiles Real World Late Phase Research

DV10. Automated DSMB Presentation in SAS: Yeah, I'd Submit That! How to auto populate PowerPoint presentations so you don't have to
*** BEST PAPER ***
Brett Jepson, Rho Inc.
Kaitie Lawson, Rho, Inc.

DV11. Translating Statistics into Knowledge by Examples Using SAS Graphic Procedures
Tao Shu, Eli Lilly and Company
Jianfei Jiang, Eli Lilly

DV12. Make it personal: Upgrade your figures by adding individual patient data to the common figure types
Yuliia Bahatska, inVentiv Health Clinical
Christiane Ahlers, Bayer AG

DV13. The basics of Graphics Template Language and output by PROC DOCUMENT
Fangping Chen, UBC

DV14. When one is not enough or multi-celled plots: comparison of different approaches
Vladlen Ivanushkin, inVentiv Health Germany GmbH

DV15. The %NEWSURV Family of Macros: An Update on the Survival Plotting Macro %NEWSURV and an Introduction to Expansion Macros
Jeffrey Meyers, Mayo Clinic



FDA Wednesday

FDA01. Statistical Review and Data Standards: It’s Gettin’ Better All The Time (slides)
Steve Wilson, Dr.P.H., CAPT USPHS, Director, Division of Biometrics III, FDA/OMPT

FDA02. Update on Data Standards (slides)
Ron Fitzmartin, PhD, MBA, Sr. Advisor, Office of Strategic Programs, CDER / FDA

FDA03. Innovation and Regulatory Review: What is JumpStart? (slides)
Alan Shapiro, MD, PhD, FAAP, Medical Officer, Office of Computational Sciences, CDER / FDA



Hands-on Training

HT01. Five Ways to Create Macro Variables: A Short Introduction to the Macro Language
Art Carpenter, CA Occidental Consultants

HT02. Point-and-Click Programming Using SAS® Enterprise Guide®
Kirk Paul Lafler, Software Intelligence Corporation
Mira Shapiro, Senior SAS® Consultant, Capacity Planner and SAS Programmer
Ryan Paul Lafler, High School Student and Software Enthusiast

HT03. Survival 101 - Just Learning to Survive
Leanne Goldstein, City of Hope
Rebecca Ottesen, City of Hope

HT04. New for SAS® 9.4: Including Text and Graphics in Your Microsoft Excel Workbooks, Part 2
Vince Delgobbo, SAS

HT05. SAS Studio - the next evolution of SAS programming environments
(No paper available)
Jim Box, SAS Institute

HT06. Usage of Pinnacle 21 Community Toolset 2.x.x for Clinical Programmers
Sergiy Sirichenko, Pinnacle 21
Michael Digiantomasso, Pinnacle 21

HT07. Single File Deliverables: Next Steps
Bill Coar, Axio Research

HT08. SAS® Life Science Visual Analytics
Pritesh Desai, sas



Healthcare Analytics

HA01. Developing Your Data Strategy
Greg Nelson, ThotWave

HA02. Multinomial Logistic Regression Models With Sas® Proc Surveylogistic
*** BEST PAPER ***
Marina Komaroff, Noven Pharmaceuticals

HA03. Topology-based Clinical Data Mining for Discovery of Hidden Patterns in Multidimensional Data
Sergey Glushakov, Intego Group
Iryna Kotenko, Intego Group / Experis Clinical, Site Lead
Andrey Rekalo, Intego Group, Senior Data Scientist

HA04. Two Roads Diverged in a Narrow Dataset...When Coarsened Exact Matching is More Appropriate than Propensity Score Matching
Aran Canes, Cigna

HA07. Analyzing data from multiple clinical trials using SAS® Real World Evidence
Jay Paulson, SAS Institute
David Olaleye, SAS Institute

HA08. Put the "K" in Your KAB: Know How to Efficiently Program with Knowledge, Attitudes, and Behavior Survey Data
Cara Lacson, United BioSource Corporation
Jasmeen Hirachan, United BioSource Corporation

HA10. Removing the Mask of Average Treatment Effects in Chronic Lyme Disease Research Using Big Data and Sub-Group Analysis
Mira Shapiro, Analytic Designers LLC
Lorraine Johnson, LymeDisease.org

HA12. A Business Solution for Improved Drug Supply Chain Visibility
David Butler, Teradata Corporation
Joy King, Teradata Corporation
Ronald Chomiuk, Teradata Corporation
Richard Neafus, Teradata Corporation



Industry Basics

IB01. A Practical Guide to Healthcare Data: Tips, traps and techniques
Greg Nelson, ThotWave

IB02. Good Programming Practices at Every Level
*** BEST PAPER ***
Maria Dalton, GlaxoSmithKline

IB03. How to define Treatment Emergent Adverse Event (TEAE) in crossover clinical trials
Mengya Yin, Ultragenyx Pharmaceutical
Wen Tan, Ultragenyx Pharmaceutical

IB04. How to find the best MDR solution for your organization
Kevin Lee, Clindata Insight

IB05. SDTM Cartography - Learn To Create SDTM Mapping Specifications
Donna Sattler, Eli Lilly
Mike Lozano, Eli Lilly and Company

IB06. Data Monitoring Committee Report Programming: Considering a Risk-Based Approach to Quality Control
Amber Randall, Axio Research
Bill Coar, Axio Research

IB07. Building a Fast Track for CDISC: Practical Ways to Support Consistent, Fast and Efficient SDTM Delivery
Steve Kirby, Chiltern International Ltd
Mario Widel, Eli Lilly
Richard Addy, Chiltern International Ltd



Management & Support

MS01. A Review of "Free" Massive Open Online Content (MOOC) for SAS® Learners
Kirk Paul Lafler, Software Intelligence Corporation

MS02. The Cross Border Program - Strengthening the Sponsor-Partner Offshore Experience
Kenneth Bauer, Merck
Girish Havildar, Merck

MS03. Stakeholder Management: How to be an effective lead SAS® programmer
Aakar Shah, Pfizer

MS04. Managing conflicts across Cross Functional and Global Virtual Teams
Arun Raj Vidhyadharan, inVentiv Health
Sunil Jairath, Inventiv Health

MS06. Insight into Offsites: creating a productive workflow with remote employees.
Maddy Wilks, Agility Clinical, Inc

MS07. Woops, I Didn't Know! An Elegant Solution to Let Your Entire Department Benefit from Individual Lessons Learned
Michael Hagendoorn, Amgen, Inc.
Annia Way, Amgen, Inc.
Tim Yerington, Amgen, Inc.
Rachel Bowman, Amgen, Inc.

MS08. Mentoring and Oversight of Programmers across Cultures and Time Zones
Chad Melson, Experis

MS09. Beyond "Just fix it!" Application of Root Cause Analysis Methodology in SAS® Programming.
Nagadip Rao, Eliassen Group

MS11. Lead Programmer Needs Help: Dedicated Programming Project Manager to the Rescue!
*** BEST PAPER ***
Gloria Boye, Vita Data Sciences (a division of Softworld, Inc)
Aparna Poona, Softworld, Inc. (Life Sciences)
Bhavin Busa, Vita Data Sciences (a division of Softworld, Inc.)

MS12. Sponsor Oversight of CROs Data Management and Biostatistical Abilities
Lois Lynn, Noven Pharmaceuticals, Inc.



Posters

PO01. CDISC Compliant NCA PK Parameter Analysis When Using Phoenix® WinNonlin®
Renfang Hwang, Celgene Coporation

PO02. Takeaways from Integrating Studies Conducted by Bristol-Myers Squibb (BMS) and ONO
Yan Wang, Bristol-Myers Squibb

PO04. Implementing Patient Report Outcome data in clinical trials analysis
Qi Wang, Amgen

PO05. Data Transparency, de-identification strategies, and platforms available for sharing data
Arun Raj Vidhyadharan, inVentiv Health
Sunil Jairath, Inventiv Health

PO06. Statistician's secret weapon: 20 ways of detecting raw data issues
Lixiang Liu, Eli Lilly

PO07. ClinicalTrials.gov Results: an End of Study Deliverable That Should Be Considered at Study Startup
Maya Barton, Rho
Elizabeth Paynter, Rho

PO08. In-Licensing from a Programming Perspective
Asif Karbhari, AstraZeneca

PO09. AIR Binder: An Automatic Reporting and Data Analysis SAS Application for Cytochrome P450 Inhibition Assay to Investigate DDI
Hao Sun, Covance, Inc.
Kristen Cardinal, Covance, Inc.
Carole Kirby, Covance, Inc.
Richard Voorman, Covance, Inc.

PO10. Charting Your Path to Using the "New" SAS® ODS and SG Graphics Successfully - Interactively Generate the Code
Roger Muller, Data To Events, Inc

PO11. Facebook Data Analysis with SAS® Visual Analytics
*** BEST PAPER ***
Prasoon Sangwan, TATA Consultancy Services Ltd
Vikrant Bisht, TATA Consultancy Services Ltd
Piyush Singh, TCS
Ghiyasuddin Mohammed Faraz Khan, Sapphire Software Solutions Inc.

PO13. Developing ADaM Dataset for Cardiovascular Outcome Studies
Joanne Zhou, GSK
Rakesh Kumar, Mr.
David Wade, Mr.
David Chen, Mr.

PO14. Mindfulness at Work: Handling Stress and Changes Gracefully and Be the Leader You Were Born To Be
*** BEST PAPER ***
Helena Ho, Astrazeneca

PO15. Pilot Meta-Analysis of HPA Axis Suppression Studies on Topical Corticosteroids using ADaM Datasets derived from Legacy Data
Lillian Qiu, FDA
Hon-Sum Ko, FDA

PO16. A Precision-strike Approach to Submission Readiness: How to Prepare Your Filing Teams for Consistent Excellence
Michael Hagendoorn, Amgen, Inc.
Tony Chang, Amgen, Inc.

PO17. Power of Interleaving and RETAIN Combination in Data Manipulation
Zongming Pan, ConnectiveRx

PO18. A custom ADaM domain for time to event analysis in adverse events
John Saida Shaik, Seattle Genetics Inc.

PO19. Analyzing Singly Imputed Utility Based Weighted Scores Using EQ-5D for Determining Patients' Quality of Life in Oncology Studies
Vamsi Krishna Medarametla, Seattle Genetics
Liz Thomas, Seattle Genetics
Gokul Vasist, Seattle Genetics

PO20. Dealing with alignment of statistics: Beyond the decimal point.
Eric Pedraza, INC Research

PO21. Metadata of Titles, Footnotes, and Proc Report Details
Julius Kirui, SCRI

PO22. SAS and R Playing Nice Together
David Edwards, Amgen, Inc.
Bella Feng, Amgen, Inc
Brian Schultheiss, Amgen, Inc.

PO24. A Guide To Programming Patient Narratives
Renuka Tammisetti, PRA Health Sciences
Karthika Bhavadas, PRA Health Sciences

PO26. REDCAP Ins and Outs
Leanne Goldstein, City of Hope

PO27. Roadmap for Managing Multiple CRO Vendors
Veena Nataraj, Shire
Karin Lapann, Shire



Quick Tips

QT01. Remove the Error: Variable length is too long for actual data
Eric Larson, inVentiv Health

QT02. Importing CSV Data to All Character Variables
Art Carpenter, CA Occidental Consultants

QT03. What Are Occurrence Flags Good For Anyway?
Nancy Brucken, inVentiv Health Clinical

QT04. Is There a Date In That Comment? Use SAS To Find Out.
*** BEST PAPER ***
Keith Hibbetts, Eli Lilly and Company

QT05. My bag of SAS lifehacks
Dmytro Hasan, Experis

QT06. Generating Colors from the Viridis Color Scale with a SAS® Macro
Shane Rosanbalm, Rho, Inc

QT07. PROC DOC III: Self-generating Codebooks Using SAS®
Louise Hadden, Abt Associates Inc.

QT09. Basic SDTM House-Keeping
Emmy Pahmer, inVentiv Health

QT10. Everyone can use a little Currency - when dependent data set updates silently make your analysis data set out of date.
Scott Worrell, PAREXEL

QT11. Multi-Dimensional Arrays: Add Derived Parameters
Siddharth Kumar Mogra, GCE Solutions Inc

QT12. Same statistical method different results? Don't panic the reason might be obvious.
Iryna Kotenko, Experis Clinical A Manpower Group Company

QT14. Visual Basic for Applications: A Solution for Handling Non-ASCII Removal and Replacement
Eric Crockett, Chiltern International

QT15. How to Create a Journal-Quality Forest Plot with SAS® 9.4
John O'Leary, Department of Veterans Affairs
Warren Kuhfeld, SAS

QT16. Common mistakes by programmers & Remedies
Sairam Veeramalla, GCE SOLUTIONS



Statistics & Pharmacokinetics

SP01. Multiple Imputation: A Statistical Programming Story
*** BEST PAPER ***
Chris Smith, Cytel Inc.
Scott Kosten, DataCeutics Inc.

SP02. Multiplicity Controlled Analyses Using SAS/IML
Xingxing Wu, Eli Lilly and Company
Hangtao Xu, Eli Lilly and Company

SP04. Population PK/PD Analysis - SAS® with R and NONMEM® Make Customization Easy
Sharmeen Reza, Cytel Inc.

SP05. Combining Survival Analysis Results after Multiple Imputation of Censored Event Times
Jonathan L Moscovici, QuintilesIMS
Bohdana Ratitch, QuintilesIMS

SP06. Adverse Event Data over Time
Kriss Harris, SAS Specialists Ltd



Submission Standards

SS-Panel. Submission Musings


SS01. How will FDA Reject non-CDISC submission?
Kevin Lee, Clindata Insight

SS02. Preparing Analysis Data Model (ADaM) Data Sets and Related Files for FDA Submission
Sandra Minjoe, Accenture

SS03. Use of Traceability Chains in Study Data and Metadata for Regulatory Electronic Submission
Tianshu Li, Celldex

SS04. Good versus better SDTM: Including Screen Failure Data in the Study SDTM?
Henry Winsor, Relypsa Inc.
Mario Widel, Eli Lilly

SS05. Good Data Validation Practice
Sergiy Sirichenko, Pinnacle 21
Max Kanevsky, Pinnacle 21

SS06. Awareness from Electronic Data Submission to PMDA and FDA -- Lesson & Learnt from hands-on experiences --
*** BEST PAPER ***
Yuichi Nakajima, Novartis
Takashi Kitahara, Novartis
Ryan Hara, Novartis AG

SS07. Overview and Application of the HCV Vertical Resistance Analysis Template
Yan Xie, Abbvie

SS08. Creating Define-XML version 2 including Analysis Results Metadata with the SAS® Clinical Standards Toolkit
Lex Jansen, SAS Institute Inc.

SS09. Leveraging Study Data Reviewer's Guide (SDRG) in Building FDA's Confidence in Sponsor's Submitted Datasets
Xiangchen (Bob) Cui, Alkermes, Inc
Min Chen, Alkermes
Letan (Cleo) Lin, Alkermes Inc.

SS10. The Do's/Don'ts, An SDTM Validation Perspective. The should/shouldn't when explaining issues in the Study Data Reviewers Guide
Thomas Guinter, Independent

SS11. Documenting Traceability for the FDA: Clarifying the Legacy Data Conversion Plan & Introducing the Study Data Traceability Guide
David Izard, Chiltern
Kristin Kelly, Merck
Jane Lozano, Eli Lilly

SS12. Quality Check your CDISC Data Submission Folder Before It Is Too Late!
Bhavin Busa, Vita Data Sciences (a division of Softworld, Inc.)



Techniques & Tutorials

TT01. SAS® and ISO8601: A practical approach
Derek Morgan, PAREXEL

TT02. Building Intelligent Macros: Using Metadata Functions with the SAS® Macro Language
Art Carpenter, CA Occidental Consultants

TT03. SAS® Debugging 101
Kirk Paul Lafler, Software Intelligence Corporation

TT04. SAS® Studio: We Program
Jim Box, SAS Institute

TT05. Special Symbols in Graphs: Multiple Solutions
Abhinav Srivastva, Gilead Sciences

TT06. Check Please: An Automated Approach to Log Checking
Richann Watson, Experis

TT07. Converting Non-Imputed Dates for SDTM Data Sets With PROC FCMP
Noory Kim, CROS NT

TT08. Clinical Trials Data: It's a Scary World Out There! or Code that Helps You Sleep at Night
Scott Horton, United BioSource

TT09. Hashtag #Efficiency! An Exploration of Hash Tables and Other Techniques
Lakshmi Nirmala Bavirisetty, Independent SAS User
Kaushal Chaudhary, Independent SAS User
Deanna Schreiber-Gregory, Henry M Jackson Foundation for the Advancement of Military Medicine

TT10. Data Quality Control: Using High Performance Binning to Prevent Information Loss
Deanna Schreiber-Gregory, Henry M Jackson Foundation for the Advancement of Military Medicine
Lakshmi Nirmala Bavirisetty, Independent SAS User
Kaushal Chaudhary, Independent SAS User

TT11. Tips and Best Practices using SAS® Analytics
Tho Nguyen, Teradata
Paul Segal, colleague

TT12. Application of Deming Regression in Molecular Diagnostics using a SAS® Macro
Merlin Njoya, Roche
Pari Hemyari, Roche

TT13. The Proc Transpose Cookbook
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TT14. Defensive Programming -- Tips and Techniques for Producing that Dataset, Table, Listing or Figure First Time
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TT15. Merge With Caution: How to Avoid Common Problems when Combining SAS Datasets
Josh Horstman, Nested Loop Consulting

TT16. Dear Dave, Please See the .LST File for Our Validation Differences. Thanks, Bad Validation Programmer
*** BEST PAPER ***
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