Applications Development Beyond the Basics Coders Corner Career Planning Data Visualization and Graphics Data Standards Healthcare Analytics

Hands-On Training Industry Basics JMP Management and Support Posters Statistics & Pharmacokinetics Techniques & Tutorials: Foundations

Applications Development

AD01. Converting Multiple Plain DOC Files to RTF Files in SAS®
William Wu, Herodata LLC, San Jose, CA
Xiaoxian Dai, Pharmacyclics, Inc., Sunnyvale, CA
Linda Gau, Pharmacyclics, Inc., Sunnyvale, CA

AD02. Creating Define.xml v2 Using SAS® for FDA Submissions
Qinghua (Kathy) Chen, Exelixis, Inc. South San Francisco, CA
James Lenihan, Exelixis, Inc. South San Francisco, CA

AD03. Table Lookup Techniques: From the Basics to the Innovative
Arthur L. Carpenter, California Occidental Consultants, Anchorage, AK

AD04. Deploying a User-Friendly SAS® Grid on Microsoft Windows
Houliang Li, Frederick, MD

AD05. The SAS® LOCALE Option: Win an international passport for your SAS code
Xiaojin Qin, Covance Pharmaceutical R&D Co., Ltd., Beijing, China

AD06. Automatic Access Control via SAS: More Efficient and Smart
Yuichi Koretaka, SHIONOGI & CO., LTD., Japan
Masakazu Fujiwara, SHIONOGI & CO., LTD., Japan
Yuki Yoshida, SHIONOGI & CO., LTD., Japan
Yoshitake Kitanishi, SHIONOGI & CO., LTD., Japan

AD07. Techniques for managing (large!) batches of statistical output
Brian Fairfield-Carter, inVentiv Health Clinical, Cary, NC
Tracy Sherman, inVentiv Health Clinical, Cary, NC

AD08. Challenges in Moving to a Multi-tier Server Platform
Carey Smoak, Roche Molecular Systems, Inc., Pleasanton, CA

AD09. Macro Programming via Parameter Look-Up Tables
Joseph Hinson, Accenture Life Sciences, Berwyn, PA

AD10. DefKit : A Micro Framework for CDISC Define-XML Application Development
Lei Zhang, Celgene Corp., Summit, NJ

AD11. Dealing with Missing Data in Clinical Trials
Lucheng Shao, Ivantis, Inc, Irvine, CA

AD12. MACUMBA - The log belongs to the program
Michael Weiss, Bayer Pharma AG, Berlin, Germany

AD13. Let SAS© Improve Your CDISC Data Quality
*** BEST PAPER ***
Wayne Zhong, Accenture, Berwyn, PA

AD14. Add Dropdowns and Redirects to Your SAS® Output
Barbara Ross, Advance America, Spartanburg, SC

AD17. The New Tradition: SAS® Clinical Data Integration
Vincent J. Amoruccio, Alexion Pharmaceuticals, Inc., Cheshire, CT
Janet Stuelpner, SAS, Cary, NC

AD18. Don’t Type, Talk SAS®
Vikas Gaddu, Anova Groups, Cary, NC
Smitha Madhu, Anova Groups, Cary, NC

AD19. Tips for Creating SAS®-Based Applications for Oracle Clinical
Kunal Agnihotri, PPD LLC, Morrisville, NC
Ken Borowiak, PPD LLC, Morrisville, NC

AD20. Managing bulk SAS job submissions with post execution analysis and notification
Bruce Kayton, Simulstat Inc., San Diego, CA

AD21. Clinical Trial Data Integration: The Strategy, Benefits, and Logistics of Integrating Across a Compound
Natalie Reynolds, Eli Lilly and Company, Indianapolis, IN
Keith Hibbetts, Inventiv Health Clinical, Indianapolis, IN

AD22. Automation of Appending TLFs
William Coar, Axio Research, Seattle, WA

AD23. Managing the Organization of SAS® Format and Macro Code Libraries in Complex Environments Including PC SAS, SAS® Enterprise Guide®, and UNIX SAS
Roger D. Muller Ph.D., Data-To-Events, Inc., Carmel, IN

AD24. Moving to SAS Drug Development 4
Magnus Mengelbier, Limelogic AB, Malmö, Sweden

AD26. Validating Analysis Data Set without Double Programming - An Alternative Way to Validate the Analysis Data Set
Linfeng Xu, Novartis, East Hanover, NJ
Christina Scienski, Novartis, East Hanover, NJ

AD27. Expediting Access to Critical Pathology Data
Rebecca Ottesen, City of Hope, Duarte, CA
Leanne Goldstein, City of Hope, Duarte, CA
Julie Kilburn, City of Hope, Duarte, CA
Joyce Niland, City of Hope, Duarte, CA

Beyond the Basics

BB01. Indexing: A powerful technique for improving efficiency
Arun Raj Vidhyadharan, inVentiv Health, Somerset, NJ
Sunil Mohan Jairath, inVentiv Health, Somerset, NJ

BB02. Understanding and Applying the Logic of the DOW-Loop
Arthur Li, City of Hope National Medical Center, Duarte, CA

BB03. That SAS®sy Lab Data
Amie Bissonett, inVentiv Health Clinical, Minneapolis, MN

BB04. D is for Dynamic, putting Dynamic back into CDISC (A simple macro utilizing PROC SQL which auto-formats continuous variables for lab tables)
Steven Black, SynteractHCR, Carlsbad, CA

BB05. I Object: SAS® Does Objects with DS2
Peter Eberhardt, Fernwood Consulting Group Inc., Toronto, ON
Xue Yao, Winnipeg Regional Health Authority, Winnipeg, MB

BB07. Five Ways to Flip-Flop Your Data
*** BEST PAPER ***
Joshua M. Horstman, Nested Loop Consulting, Indianapolis, IN

BB08. Express Yourself! Regular Expressions vs SAS Text String Functions
*** BEST PAPER ***
Spencer Childress, Rho®, Inc., Chapel Hill, NC

BB10. Using the Power of SAS SQL
Jessica Wang, Regeneron Pharmaceuticals Inc., Basking Ridge, NJ

BB11. XML in a SAS® and Pharma World
Mike Molter, d-Wise, Raleigh, NC

BB12. Basics of Macro Processing - ‘Q’ Way
Usha Kumar, inVentiv Health Clinical, Pune, Maharashtra, India

BB13. Kaplan-Meier Survival Plotting Macro %NEWSURV
Jeffrey Meyers, Mayo Clinic, Rochester, MN

BB14. A SAS® Macro Utility to Modify and Validate RTF Outputs for Regional Analyses
Jagan Mohan Achi, PPD, Austin, TX
Joshua N. Winters, PPD, Rochester, NY

BB15. Atypical Application of PROC SUMMARY
John Henry King, Ouachita Clinical Data Services, Inc., Caddo Gap, AR

BB16. Automated Validation – Really?
Sneha Sarmukadam, inVentiv Health Clinical, Pune, India
Seeja Shetty, inVentiv Health Clinical, Mumbai, India

BB17. Come Out of Your Shell: A Dynamic Approach to Shell Implementation in Table and Listing Programs
Paul Burmenko, PRA International, Lenexa, KS
Tony Cardozo, PRA International, Lenexa, KS

BB18. Risk-Based Approach to Identifying and Selecting Clinical Sites for Sponsor’s Preparation for FDA/EMA Inspection
Xiangchen (Bob) Cui, Alkermes, Inc, Waltham, MA

BB19. Defensive Programming, Avoiding the Big Mistakes
David Franklin, TheProgrammersCabin.com, Litchfield, NH

BB20. Efficient SQL for Pharma… and Other Industries
Chris Olinger, d-Wise, Morrisville, NC

Career Planning

CP01. What's Hot, What's Not: Skills for SAS® Professionals
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA
Charles Edwin Shipp, Consider Consulting Corporation, San Pedro, CA

CP02. Show Your SAS® Off: Personal Branding and Your Online Portfolio
*** BEST PAPER ***
Barbara Ross, Advance America, Spartanburg, SC

CP03. Creating a Career GPS to Enhance Your Opportunities: Ten Steps to Improve Your Value by Strengthening Your Planning
Bill Donovan, Ockham Source, Cary, NC
Shridhar Patel, Sorrento Therapeutics, Cary, NC

CP04. Pharma Company Questions and Answers
J.J. Hantsch, Chicago, IL

CP05. Call me Maybe? Using LinkedIn to make sure you get the call for the job
Tara Potter, Ockham, Cary, NC
Adel Lesniak, Ockham, Cary, NC

CP06. Enhancing your Career by Bringing Consultants Into Your Organization
Roger D. Muller, Ph.D., Data-To-Events, Inc., Carmel, IN
Gregory S. Nelson, Thotwave Technologies, Chapel Hill, NC

CP07. Careers in Biostatistics and Clinical SAS® Programming: An Overview for the Uninitiated
Justina M. Flavin, Independent Consultant, San Diego, CA

CP08. Pick Me, Pick Me
Deloris Jones, Green Key Resources, Orlando, FL
Richard Harbin, Green Key Resources, Orlando, FL
Monique Gainey, Green Key Resources, Orlando, FL

CP09. Career Planning –How to Make it Work for You? – Tips for Programmers, Managers, and Senior Leaders
Vijay Moolaveesala, ACI Clinical, Bala Cynwyd, PA

CP10-SAS. Negotiation: Getting the Best Out of an Offer
(No paper available)
Janet Stuelpner, SAS, Cary, NC

Coders Corner

CC01. How to Keep Multiple Formats in One Variable after Transpose
Mindy Wang, Independent Consultant, North Potomac, MD

CC02. Let Hash SUMINC Count For You
Joseph Hinson, Accenture Life Sciences, Berwyn, PA

CC03. Quotes within Quotes: When Single (‘) and Double (“) Quotes are not Enough
Arthur L. Carpenter, California Occidental Consultants, Anchorage, AK

CC04. Standardization of Confidence Intervals in PFS Tables - a Macro Approach
John Saida Shaik, Seattle Genetics, Inc., Bothell, WA
Boxun Zhang, Seattle Genetics, Inc., Bothell, WA

CC05. Having Fun with RACE Derivation in DM Domain
Chunxia Lin, InVentiv Health Clinical, Ossining, NY
Deli Wang, Tarrytown, NY

CC06. Tips to Manipulate the Partial Dates
Deli Wang, Ossining, NY
Chunxia Lin, InVentiv Health Clinical, Ossining, NY

CC07. Preserving Line Breaks When Exporting to Excel
Nelson Lee, Genentech, South San Francisco, CA

CC08. Additional Metadata for Common Catalog Entry Types
Kenneth W. Borowiak, PPD, Morrisville, NC

CC09. An Alternative Way to Detect Invalid Reference Records in Supplemental Domains
Steven Wang, inVentiv Health Clinical, Indianapolis, IN

CC10. Automating the Number of Treatment Columns for a Dose Escalation Study
Catherine DeVerter, Novella Clinical, Morrisville, NC
Sonali Garg, Alexion Pharmaceuticals, Cheshire, CT

CC11. Streamline the Dual Antiplatelet Therapy Record Processing in SAS® by Using Concept of Queue and Run-Length Encoding
Kai Koo, Abbott Vascular, Santa Clara, CA

CC12. A Macro to Automate Symbol Statements in Line Plots
Deli Wang, Ossining, NY
Chunxia Lin, InVentiv Health Clinical, Ossining, NY

CC13. WHERE, Oh, WHERE Art Thou? A Cautionary Tale for Using WHERE Statements and WHERE= Options
*** BEST PAPER ***
Britney D. Gilbert, Juniper Tree Consulting, Porter, OK

CC14. A Toolkit to Check Dictionary Terms in SDTM
Huei-Ling Chen, Tech Data Services, Bridgewater, NJ
Helen Wang, Sanofi, Bridgewater, NJ

CC15. Cleaning up your SAS log: Overwritten Variable Info Messages
Jennifer Srivastava, Quintiles Transnational Corporation, Durham, NC

CC16. Need for Speed in Large Datasets – The Trio of SAS® INDICES, PROC SQL and WHERE CLAUSE is the Answer
Kunal Agnihotri, PPD LLC, Morrisville, NC

CC18. Macro to check Audit compliance and standards of SAS® programs
Seeja Shetty, inVentiv Health Clinical, Mumbai, India

CC19. Let Chi-Square Pass Decision to Fisher’s Programmatically
Linga Reddy Baddam, inVentiv Health Clinical, Hyderabad, India
Sudarshan Reddy Shabadu, inVentiv Health Clinical, Hyderabad, India

CC20. BreakOnWord: A Macro for Partitioning Long Text Strings at Natural Breaks
Richard Addy, Rho, Chapel Hill, NC
Charity Quick, Rho, Chapel Hill, NC

CC21. Automating Production of the blankcrf.pdf
Walter Hufford, Novartis, East Hanover, NJ

CC22. A SAS® Macro Tool for Visualizing Data Comparison Results in an Intuitive Way
Hui Wang, Biogen Idec, Boston, MA
Weizhen Ying, Biogen Idec, Boston, MA

CC23. Need to Review or Deliver Outputs on a Rolling Basis? Just Apply the Filter!
*** BEST PAPER ***
Tom Santopoli, Accenture, Berwyn, PA

CC25. SCAN and FIND “CALL SCAN”
Usha Kumar, inVentiv Health Clinical, Pune, Maharashtra, India

CC29. Quickly Organize Statistical Output for Review
Bradford J. Danner, inVentiv Health Clinical, TN

CC30. Times Can Be Tough: Taming DATE, TIME and DATETIME Variables
Sajeet Pavate, PPD, Wilmington, NC

CC31. Let the CAT Catch a STYLE
Yanhong Liu, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
Justin Bates, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH

CC32. 1 of N Methods to Automate the Y- Axis
Sanjiv Ramalingam, Biogen Idec

CC33. QC made easy using macros
Prashanthi Selvakumar, Percept Pharma Services, Bridgewater, NJ

CC36. Macro Makes Final Documentation Quick and Easy
Indrani Sarkar, inVentiv Health Clinical, Indianapolis, IN
Jean Crain, inVentiv Health Clinical, Indianapolis, IN

CC37. Reducing Variable Lengths for Submission Dataset Size Reduction
Sandra VanPelt Nguyen, inVentiv Health Clinical

CC38. Let SAS® Do That For You
Emmy Pahmer, inVentiv Health Clinical, Montreal, QC, Canada

CC40. Inserting MS Word Document into RTF Output and Creating Customized Table of Contents Using SAS® and VBA Macro
Haining Li, Neurological Clinical Research Institute, Mass General Hospital, Boston, MA
Merit E. Cudkowicz, Neurological Clinical Research Institute, Mass General Hospital, Boston, MA
Hong Yu, Neurological Clinical Research Institute, Mass General Hospital, Boston, MA

CC41. PRELOADFMT comes to your rescue, it brings missing categories to life in summary reports
Niraj J. Pandya, Independent Consultant, CT
Ramalaxmareddy Kandimalla, KRL Solutions, CT

CC43. Give me EVERYTHING! A macro to combine the CONTENTS procedure output and formats
Lynn Mullins, PPD, Cincinnati, OH

CC44. A Macro to Create Occurrence Flags for Analysis Datasets
Ed Lombardi, Agility Clinical, Inc., Carlsbad, CA

CC45. Self-fulfilling Macros Generating Macro Calls and Enabling Automation from a Specification
Y. Christina Song, Rho, Inc, Chapel Hill, NC

CC47. It’s not the Yellow Brick Road but the SAS PC FILES SERVER® will take you Down the LIBNAME PATH= to Using the 64-Bit Excel Workbooks
William E Benjamin Jr, Owl Computer Consultancy, LLC, Phoenix AZ

CC48. Creating PDF Reports using Output Delivery System
Shubha Manjunath, eClinical Solutions, Mansfield, MA
Shirish Nalavade, Eliassen Group Inc., Somerset, NJ

CC49. A Shout-out to Specification Review: Techniques for an efficient review of Programming Specifications
Sajeet Pavate, PPD, Wilmington, NC
Jhelum Naik, PPD, Wilmington, NC

CC50. What do you mean 0.3 doesn't equal 0.3? Numeric Representation and Precision in SAS and Why it Matters
Paul Stutzman, Axio Research LLC, Seattle, Washington

Data Standards

DS01. Discover Define-XML
Mark Wheeldon, Formedix, Burlington, MA
Kevin Burges, Formedix, Burlington, MA

DS02. Forging New SDTM Standards for In-Vitro Diagnostic (IVD) Devices: A Use-Case
Carey Smoak, Roche Molecular Systems, Inc., Pleasanton, CA
Smitha Krishnamurthy, Roche Molecular Systems, Inc., Pleasanton, CA
Mansi Singh, Roche Molecular Systems, Inc., Pleasanton, CA
Sy Truong, Meta-Xceed, Inc., Fremont, CA

DS03. Considerations in Creating SDTM Trial Design Datasets
Jerry Salyers, Accenture Life Sciences, Berwyn, PA
Richard Lewis, Accenture Life Sciences, Berwyn, PA
Kim Minkalis, Accenture Life Sciences, Berwyn, PA
Fred Wood, Accenture Life Sciences, Berwyn, PA

DS04. Considerations in the Submission of Exposure Data in SDTM-Based Datasets
Fred Wood, Accenture Life Sciences, Wayne, PA
Jerry Salyers, Accenture Life Sciences, Wayne, PA
Richard Lewis, Accenture Life Sciences, Wayne, PA
Kristin Kelly, Accenture Life Sciences, Wayne, PA

DS05. Data Standards Development for Therapeutic Areas: A Focus on SDTM-Based Datasets
Fred Wood, Accenture Life Sciences, Wayne, PA
Diane Wold, Glaxo SmithKline, Research Triangle Park, NC
Rhonda Facile, CDISC, Austin, TX
Wayne Kubick, CDISC

DS06. Referencing Medical Device Data in Standard SDTM domains
Timothy L Bullock, Allergan, Santa Barbara, CA
Ramkumar Krishnamurthy, Allergan, Santa Barbara, CA

DS07. Applying ADaM BDS Standards to Therapeutic Area Ophthalmology
Songhui Zhu, A2Z Scientific Inc., East Brunswick, NJ

DS08. Challenges of Processing Questionnaire Data from Collection to SDTM to ADaM and Solutions Using SAS
Karin LaPann, PRA International, Horsham, PA
Terek Peterson, MBA, PRA International, Horsham, PA

DS09. An ADaM Interim Dataset for Time-to-Event Analysis Needs
Tom Santopoli, Accenture, Berwyn, PA
Kim Minkalis, Accenture, Berwyn, PA
Sandra Minjoe, Accenture, Berwyn, PA

DS10. Developing ADaM Specifications to Embrace Define-XML 2.0.0 Requirements
Lin Yan, Celgene Corporation, 300 Connell Drive, Berkeley Heights, NJ

DS11. A Guide to the ADaM Basic Data Structure for Dataset Designers
Michelle Barrick, Eli Lilly and Company, Indianapolis, IN
John Troxell, John Troxell Consulting LLC, Bridgewater, NJ

DS12. Effective Use of Metadata in Analysis Reporting
Jeffrey Abolafia, Rho Inc., Chapel Hill, NC

DS13. How Valued is Value Level Metadata?
*** BEST PAPER ***
Shelley Dunn, d-Wise, Morrisville, NC

DS14. CDISC Electronic Submission
*** BEST PAPER ***
Kevin Lee, Accenture Life Sciences, Berwyn, PA

DS15. A Road Map to Successful CDISC ADaM Submission to FDA: Guidelines, Best Practices & Case Studies
Vikash Jain, Accenture Life Sciences, Berwyn, PA
Sandra Minjoe, Accenture Life Sciences, Berwyn, PA

DS16. OpenCDISC Validator Implementation: A Complex Multiple Stakeholder Process
Terek Peterson, MBA, PRA International, Horsham, PA
Gareth Adams, PRA International, Swansea, United Kingdom

DS17. Update: Development of White Papers and Standard Scripts for Analysis and Programming
Nancy Brucken, inVentiv Health Clinical, Ann Arbor, MI
Michael Carniello, Takeda Development Center Americas, Inc., Deerfield, IL
Mary Nilsson, Eli Lilly and Company, Indianapolis, IN
Hanming Tu, Accenture, Wayne, PA

DS18. An Alternative Way to Create Define.XML for ADaM with SAS Macro Automation
Yiwen Li, Gilead Sciences, Foster City, CA

DS19. SAS® as a Tool to Manage Growing SDTM+ Repository for Medical Device Studies
Julia Yang, Medtronic Inc. Mounds View, MN

DS20-SAS. A How-To Guide for Extending Controlled Terminology Using SAS Clinical Data Integration
(No paper available)
Melissa Martinez, SAS Institute, Cary, NC

DS21-SAS. Round Trip Ticket – Using the Define.xml file to Send and Receive your Study Specifications
Julie Maddox, SAS Institute Inc., Cary, NC

DS22-SAS. An Integrated platform to manage Clinical data, Metadata and Data Standards
(No paper available)
Romain Rutten, Janssen Research and Development
Peter Wang, Janssen Research and Development
Sharon Trevoy, SAS Institute, Cary, NC

DS23-SAS. Creating Define-XML version 2 with the SAS® Clinical Standards Toolkit 1.6
Lex Jansen, SAS Institute Inc., Cary, NC

Data Visualization and Graphics

DG01. Techniques of Preparing Datasets for Visualizing Clinical Adverse Events
Amos Shu, Endo Pharmaceuticals., Malvern, PA
Qinghua (Kathy) Chen, Exelixis Inc., South San Francisco, CA

DG02. Graphical Representation of Patient Profile for Efficacy Analyses in Oncology
William Wu, Herodata LLC, San Jose, CA
Xiaoxian Dai, Pharmacyclics, Inc., Sunnyvale CA
Linda Gau, Pharmacyclics, Inc., Sunnyvale CA

DG03. Developing Graphical Standards: A Collaborative, Cross-Functional Approach
*** BEST PAPER ***
Mayur Uttarwar, Seattle Genetics, Inc., Bothell, WA
Murali Kanakenahalli, Seattle Genetics, Inc., Bothell, WA

DG05. JMP® Visual Analytics®
Charles Edwin Shipp, Consider Consulting Corp, Los Angeles, CA

DG06. Want to Conquer the Fear of Annotation? Start Using the NOTE Statement
Madhuri Aswale, Inventive Health Clinical, Pune, Maharashtra, India

DG07. Swimmer Plot: Tell a Graphical Story of Your Time to Response Data Using PROC SGPLOT
Stacey D. Phillips, Inventiv Health Clinical, Princeton, NJ

DG08. Napoleon Plot for PharmaSUG
Kriss Harris, SAS Specialists Ltd, Hertfordshire, United Kingdom

DG09. Clinical Data Dashboards for Centralized Monitoring Using SAS® and Microsoft® SharePoint®
Jagan Mohan Achi, PPD, Austin TX

DG10. ODS EPUB: SAS® Output at Hand
Erica Goodrich, Grand Valley State University/Priority Health, Grand Rapids, MI
Daniel Sturgeon, Priority Health, Grand Rapids, MI

DG12. Automate the Process of Image Recognizing a Scatter Plot: An Application of Non-parametric Cluster Analysis in Capturing Data from Graphical Output
Zhaojie Wang, Celgene Corporation, Summit, NJ

DG13. I Am Legend
Kriss Harris, SAS Specialists Ltd, Hertfordshire, United Kingdom

DG14-SAS. Up Your Game with Graph Template Language Layouts
Sanjay Matange, SAS Institute, Cary, NC

DG15-SAS. Quick Introduction to ODS DOCUMENT
(No paper available)
Cynthia L. Zender, SAS Institute, Inc., Cary, NC

Hands-On Training

HT01. Programming With CLASS: Keeping Your Options Open
Arthur L. Carpenter, California Occidental Consultants, Anchorage, AK

HT02-SAS. Practically Perfect Presentations
Cynthia L. Zender, SAS Institute, Inc., Cary, NC

HT03. Hands-On ADaM ADAE Development
Sandra Minjoe, Accenture Life Sciences, Wayne, PA
Kim Minkalis, Accenture Life Sciences, Wayne, PA

HT04. A Hands-on Introduction to SAS® Dictionary Tables
Peter Eberhardt, Fernwood Consulting Group Inc., Toronto, ON, Canada

HT05. Survival 101 - Just Learning to Survive
Leanne Goldstein, City of Hope, Duarte, CA
Rebecca Ottesen, City of Hope, Duarte, CA

HT06. So You're Still Not Using PROC REPORT. Why Not?
Ray Pass, inVentiv Health Clinical, St Louis, MO
Daphne Ewing, Gilead Sciences, Inc., Foster City, CA

HT07. SDTM, ADaM and define.xml with OpenCDISC®
Angela Ringelberg, Ockham Onocology, Cary, NC
Tracy Sherman, inVentiv Health Clinical, Cary, NC

HT08-SAS. Creating Multi-Sheet Microsoft Excel Workbooks with SAS®: The Basics and Beyond Part 1
Vincent DelGobbo, SAS Institute Inc., Cary, NC

Healthcare Analytics

HA01. Reporting Healthcare Data: Understanding Rates and Adjustments
Gregory S. Nelson, ThotWave Technologies, Chapel Hill, NC

HA02. Common and Comparative Incidence Indicators of Adverse Events for Well-Defined Study Pools
John R Gerlach, Dataceutics, Inc., Pottstown, PA

HA03. Survey of Population Risk Management Applications Using SAS®
Jack N Shoemaker, d-Wise, Morrisville, NC

HA04. Linking Healthcare Claims and Electronic Health Records (EHR) for Patient Management – Diabetes Case Study
*** BEST PAPER ***
Paul A. LaBrec, Treo Solutions - 3M Health Information Solutions, San Diego, CA

HA05. %ME: A SAS® Macro to Assess Measurement Equivalence for Patient-Reported Outcome Measures
Qinlei Huang, St. Jude Children’s Research Hospital, Memphis, TN

HA06. The Association of Morbid Obesity with Mortality and Coronary Revascularization among Patients with Acute Myocardial Infarction
Ashwini S Erande, MPH, University Of California Irvine, Orange, CA
Shaista Malik, MD, PhD, University Of California Irvine, Orange, CA

HA07. Using the SAS System as a bioinformatics tool: A macro that translates BLASTn results to populate a DNA sequence database table
Kevin Viel, inVentiv Health Clinical and Histonis, Incorporated, Atlanta, GA

HA09. Using SAS® to Calculate and Compare Adjusted Relative Risks, Odds Ratios, and Hazard Ratios
Besa Smith, MPH, PhD, ANALYDATA, San Diego, CA
Tyler Smith, MS, PhD, National University, School of Health and Human Services, Department of Community Health, San Diego, CA

HA10. Estimating Medication Adherence Using a Patient-Mix Adjustment Method
R. Scott Leslie, MedImpact Healthcare Systems, Inc., San Diego, CA

Industry Basics

IB01. Challenges in Processing Clinical Lab Data
*** BEST PAPER ***
Alan Meier, MedImmune, LLC, Gaithersburg, MD

IB02. TLF Validation Etiquette: What to say, When to Say, How to Say, Why to Say
Karen Walker, inVentiv Health Clinical, San Diego, CA

IB03. Common Variables in Adverse Event and Exposure analysis datasets specific for Oncology clinical trials
Haridasan Namboodiri, PRA International, Horsham, PA

IB04. Cover the Basics, Tool for structuring data checking with SAS
Ole Zester, Novo Nordisk, Denmark

IB05. Attain 100% Confidence in Your 95% Confidence Interval
Indu Nair, United BioSource Corporation, Blue Bell, PA
Binal Patel, United BioSource Corporation, Blue Bell, PA

IB06. Good versus Better SDTM – Why “Good Enough” May No Longer Be Good Enough When It Comes to SDTM
Henry Winsor, Relypsa, Inc., Redwood City, CA

IB07. From “Just Shells” to a Detailed Specification Document for Tables, Listings and Figures
Supriya Dalvi, InVentiv Health Clinical, Mumbai, India

IB09. Clinical Study Report Review: Statistician’s Approach
Amita Dalvi, inVentiv Health Clinical, Mumbai, India

IB10-SAS. Clinical Trial Data Transparency: Seeing is Believing
(No paper available)
Janet Stuelpner, SAS, Cary, NC

JMP

JP01-SAS. Risk-Based Monitoring of Clinical Trials Using JMP® Clinical
Richard C. Zink, Ph.D., JMP Life Sciences, SAS Institute, Inc., Cary, NC
Kelci J. Miclaus, Ph.D., JMP Life Sciences, SAS Institute, Inc.

Management and Support

MS01. A New Trend in the industry – Partnerships between CROs and Pharma. Do we know how to work in this new relationship?
Kevin Lee, Accenture Life Sciences, Berwyn, PA

MS02. Building Better Programming Teams with Situational Exposure Training
Elizabeth Reinbolt, MS, DataCeutics, Inc., Lincoln, NE
Steven Kirby, JD, MS, Shire, Chesterbrook, PA

MS03. Distance Management: how to lead a team of SAS users who sit half a world away
Max Cherny, GlaxoSmithKline, King of Prussia, PA

MS04. Was Dorothy Right: Is There No Place Like Home?
*** BEST PAPER ***
Kjersten Offenbecker, Theorem Clinical Research, King of Prussia, PA

MS05. How To Win Friends and Influence People – A Programmer’s Perspective in Effective Human Relationships
Priscilla Gathoni, Morristown, NJ

MS07. The Fourth Lie – False Resumes
*** BEST PAPER ***
Ernest Pineda, Gerard Group, Inc., San Bruno, CA

MS08. Demystify "Ten years of pharma programming experience required" - What hiring managers actually look for
Peng Yang, Clindata Insight Inc, Moraga, CA

MS09. Monitoring Quality, Time and Costs of Clinical Trial Programming Projects using SAS®
Jagan Mohan Achi, PPD, Austin, TX

MS10. Kaizen
Usha Kumar, inVentiv Health Clinical, Pune, Maharashtra, India

MS11. A Guide for Front-Line Managers to Retain Talented Statistical SAS Programmers
R. Mouly Satyavarapu, inVentiv Health Clinical, Ann Arbor, MI

MS12. Recruiting for Retention
Kathy Greer, DataCeutics, Inc., Pottstown, PA
John Reilly, DataCeutics, Inc., Pottstown, PA

MS13-SAS. When is Validation Valid?
(No paper available)
Janet Stuelpner, SAS, Cary, NC

Posters

PO01. A User Friendly Tool to Facilitate the Data Integration Process
Yang Wang, Seattle Genetics, Inc., Bothell, WA
Boxun Zhang, Seattle Genetics, Inc., Bothell, WA

PO02. Survival Analysis Approaches and New Developments using SAS
Jane Lu, AstraZeneca Pharmaceuticals, Wilmington, DE
David Shen, Independent Consultant

PO04. CDISC Mapping and Supplemental Qualifiers
Arun Raj Vidhyadharan, inVentiv Health, Somerset, NJ
Sunil Mohan Jairath, inVentiv Health, Somerset, NJ

PO07. SAS Can Automatically Provide GTL Templates for Graphics in Three Ways
David Shen, Li Zhang, Independent Consultant, Chesterbrook, PA
Ben Adeyi, Dapeng Zhang, Shire Pharmaceuticals, Chesterbrook, PA

PO08. Design of Experiments (DOE) Using JMP
Charles E. Shipp, Consider Consulting, Los Angeles, CA

PO09. Bad Date: How to find true love with Partial Dates!
Namrata Pokhrel, Accenture Life Sciences, Berwyn, PA

PO10. Switching from PC SAS® to SAS Enterprise Guide®
Zhengxin (Cindy) Yang, inVentiv Health Clinical, Princeton, NJ

PO11. Guidelines for Protecting Your Computer, Network and Data from Malware Threats
Ryan Paul Lafler, High School Student, Operating System and Software Enthusiast, Spring Valley, CA
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA

PO12. Process and Tools for Assessing Compliance with Standard Operating Procedures
Ginger Redner, Merck & Company, Inc., Upper Gwynedd, PA
Eunice Ndungu, Merck & Company, Inc., Upper Gwynedd, PA

PO13. Adopted Changes for SDTMIG v3.1.3 and 2013 OpenCDISC Upgrades
*** BEST PAPER ***
Yi Liu Celerion Inc., Lincoln, NE
Stephen Read Celerion Inc., Belfast, Northern Ireland, UK

PO14. Route to SDTM Implementation in In-Vitro Diagnostic Industry: Simple or Twisted
Carey Smoak, Roche Molecular Systems, Inc., Pleasanton, CA
Sofia Shamas, MaxisIT Inc., NJ
Chowdagam Chaitanya, MaxisIT Inc., NJ
Don Lim, Bluewave Consulting Inc., CA
Girish Rajeev, InVentiv Health Clinical, FL

PO15. Evaluating the benefits of JMP® for SAS programmers
Xiaopeng Li, Celerion, Lincoln, NE
Chun Feng, Celerion, Lincoln, NE
Nancy Wang, Celerion, Lincoln, NE

PO16. Automation of ADAM Dataset Creation with a Retrospective, Prospective and Pragmatic Process
Karin LaPann, MSIS, PRA International, Horsham, PA
Terek Peterson, MBA, PRA International, Horsham, PA

PO17. Healthcare Data Manipulation and Analytics Using SAS
Lumin Shen, University of Pennsylvania
Jane Lu, AstraZeneca Pharmaceuticals Inc

PO18. Compare Without PROC COMPARE
Pavan Vemuri, PPD, Morrisville, NC

PO19. An Overview of REDCap, a secure web-based application for Electronic Data Capture
Kevin Viel, inVentiv Health Clinical and Histonis, Incorporated, Atlanta, GA

PO20. A Parameterized SAS Macro to Select an Appropriate Covariance Structure in Repeated Measures Data Analysis Using PROC MIXED
Leela Aertker, Rho, Chapel Hill, NC
Paul Nguyen, Rho, Chapel Hill, NC
Charity Quick, Rho, Chapel Hill, NC

PO22. Tips for Finding Your Bugs Before QC Does
Beatriz Garcia, Inventiv Health Clinical Mexico, Mexico City, Mexico

PO24. Create Excel TFLs Using the SAS® Add-in
Jeffrey Tsao, Amgen, Thousand Oaks, CA
Tony Chang, Amgen, Thousand Oaks, CA

Statistics & Pharmacokinetics

SP01. Factor Analysis of Scale for Assessment of Negative Symptoms using SAS Software
Ben Adeyi, Shire Pharmaceuticals, Chesterbrook, PA
David Shen, Independent Consultant, Chesterbrook, PA

SP02. Handling with missing data in clinical trials for time-to-event variables
Giulia Tonini,PhD Menarini Ricerche, Florence, Italy
Simona Scartoni, Menarini Ricerche, Florence, Italy
Angela Capriati, MD, PhD, Menarini Ricerche, Florence, Italy

SP03. Defining Non-Inferiority Margins for Skin Adhesion Studies
Marina Komaroff, Noven Pharmaceuticals, New York, NY
Sailaja Bhaskar, Noven Pharmaceuticals, New York, NY

SP04. %IC_LOGISTIC: A SAS® Macro to Produce Sorted Information Criteria (AIC/BIC) List for PROC LOGISTIC for Model Selection
*** BEST PAPER ***
Qinlei Huang, St. Jude Children’s Research Hospital, Memphis, TN
Liang Zhu, St. Jude Children’s Research Hospital, Memphis, TN

SP05. A SAS® Macro to address PK timing variables issues
Timothy J Harrington, Dataceutics inc, Pottstown, PA

SP06. A Mental Health and Risk Behavior Analysis of American Youth Using PROC FACTOR and SURVEYLOGISTIC
Deanna Schreiber-Gregory, North Dakota State University

SP07. A SAS® Macro to Evaluate Balance after Propensity Score Matching
Erin Hulbert, Optum Life Sciences, Eden Prairie, MN
Lee Brekke, Optum Life Sciences, Eden Prairie, MN

SP08. Methodology for Non-Randomized Clinical Trials: Propensity Score Analysis
Dan Conroy, Ph.D., inVentiv Health, Burlington, MA

SP09. Same Data, Separate MEANS – ‘SORT’ of Magic or Logic?
Naina Pandurangi, inVentiv Health Clinical, Mumbai, India
Seeja Shetty, inVentiv Health Clinical, Mumbai, India

SP10. Our Survival Confidence Intervals are not the Same!
David Franklin, Quintiles Inc., Cambridge, MA

SP13. The path less trodden - PROC FREQ for ODDS RATIO
Manjusha Gondil, Inventiv International Pharma Services Pvt. Ltd., Pune, India
Linga Reddy Baddam, Inventiv International Pharma Services Pvt. Ltd., Pune, India

SP14-SAS. Creating and Customizing the Kaplan-Meier Survival Plot in PROC LIFETEST in the SAS/STAT® 13.1 Release
Warren F. Kuhfeld, SAS Institute Inc., Cary, NC
Ying So, SAS Institute Inc., Cary, NC

SP15-SAS. Modeling Categorical Response Data
(No paper available)
Maura Stokes, SAS Institute, Cary, NC

SP16. Automating Pharmaceutical Safety Surveillance process
Pankaj Bhardwaj, Tata Consultancy Services Ltd, New Delhi, India
Chandramouli Raghuram, Tata Consultancy Services Ltd, Edison, NJ

Techniques & Tutorials: Foundations

TT01. Modernizing Your Data Strategy: Understanding SAS® Solutions for Data Integration, Data Quality, Data Governance and Master Data Management
*** BEST PAPER ***
Gregory S. Nelson, ThotWave Technologies, Chapel Hill, NC
Lisa Dodson, SAS Institute, Cary, NC

TT02. Are You Missing Out? Working with Missing Values to Make the Most of What is not There
Arthur L. Carpenter, California Occidental Consultants, Anchorage, AK

TT04. ‘V’ for … Variable Information Functions to the Rescue
Richann Watson, Experis, Batavia, OH
Karl Miller, inVentiv Health Clinical, Lincoln, NE

TT05. Principles of Writing Readable SQL
Kenneth W. Borowiak, PPD, Morrisville, NC

TT06. Functioning at a Higher Level: Using SAS® Functions to Improve Your Code
*** BEST PAPER ***
Peter Eberhardt, Fernwood Consulting Group Inc., Toronto, ON, Canada
Lucheng Shao, Ivantis Inc., Irvine, CA

TT08. Investigating the Irregular: Using Perl Regular Expressions
Peter Eberhardt, Fernwood Consulting Group Inc., Toronto, ON, Canada

TT09. Strategies and Techniques for Debugging SAS® Program Errors and Warnings
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA

TT10. Strategies and Techniques for Getting the Most Out of Your Antivirus Software for SAS® Users
Ryan Paul Lafler, High School Student, Operating System and Software Enthusiast, Spring Valley, CA
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA

TT11. What is the Definition of Global On-Demand Reporting within the Pharmaceutical Industry?
Eric Kammer, Novartis Pharmaceuticals Corporation, East Hanover, NJ

TT12. Let the CAT Out of the Bag: String Concatenation in SAS 9
Joshua Horstman, Nested Loop Consulting, Indianapolis, IN

TT13. Internal Consistency and the Repeat-TFL Paradigm: When, Why and How to Generate Repeat Tables/Figures/Listings from Single Programs
Tracy Sherman, InVentiv Health Clinical, Cary, NC
Brian Fairfield-Carter, InVentiv Health Clinical, Cary, NC

TT14. The Three I’s of SAS® Log Messages, IMPORTANT, INTERESTING, and IRRELEVANT
William E Benjamin Jr, Owl Computer Consultancy, LLC, Phoenix, AZ

TT15. Ma, How Long Do I Cook The Turkey For?
David Franklin, TheProgrammersCabin.com, Litchfield, NH