Enhance your PharmaSUG experience by attending optional pre- and post-conference training seminars taught by seasoned experts. Half-day courses are only $125 and full-day courses are $250. You can sign up for classes when you register for the conference. Space is limited!

Be sure to review the seminar registration, attendance, and cancellation policy.

Saturday, May 7, 2016

Course Title (click for description) Instructor(s) (click for bio) Time
#1 Advanced Reporting and Analysis Techniques for the SAS® Power User: It's Not Just About the PROCs! Art Carpenter 8:00 AM - 5:00 PM
#2 Data Sharing is Data Caring – De-Identifying and Anonymizing Patient Data to Protect Patient Privacy and Honor Informed Consent Dave Handelsman 8:00 AM - 12:00 PM
#3 The SDTMIG: Beyond the Modeled Domains and Other Implementation Challenges Fred Wood
& Jerry Salyers
8:00 AM - 12:00 PM
#4 Clinical Graphs using SAS® Sanjay Matange 1:00 PM - 5:00 PM
#5 Define-XML for SAS® Programmers Lex Jansen 1:00 PM - 5:00 PM

Sunday, May 8, 2016

Course Title (click for description) Instructor(s) (click for bio) Time
#6 Cleaning, Validating, and Reshaping Your Data: Taking Advantage of SAS® Tools Art Carpenter 8:00 AM - 12:00 PM
#7 ADaM Datasets: Creation and Applications Nancy Brucken
& Mario Widel
& Paul Slagle
8:00 AM - 12:00 PM
#8 Visualization (SAS®, JMP, R, Qlik and Tableau) Greg Nelson 8:00 AM - 12:00 PM
#9 Building Dynamic Programs and Applications Using the SAS® Macro Language Art Carpenter 1:00 PM - 5:00 PM
#10 Essential SAS® Programming Techniques for Perl®, Python® and R® Users Kirk Paul Lafler 1:00 PM - 5:00 PM
#11 FDA Submission Data Requirements Dave Izard 1:00 PM - 5:00 PM

Wednesday, May 11, 2016

Course Title (click for description) Instructor(s) (click for bio) Time
#12 An In-Depth Look at PROC REPORT Jane Eslinger 1:00 PM - 5:00 PM
#13 Introduction to Enterprise Guide Ben Cochran 1:00 PM - 5:00 PM
#14 Building Clinical Trial Dashboards Using Base-SAS Software Kirk Paul Lafler
& Roger Muller
& Josh Horstman
1:00 PM - 5:00 PM

Thursday, May 12, 2016

Course Title (click for description) Instructor(s) (click for bio) Time
#15 Learning R for SAS Users Arthur Li 8:00 AM - 5:00 PM

Seminar Registration, Attendance, and Cancellation Policy

  1. You must register for the conference in order to attend a seminar.
  2. You must register for a seminar via the PharmaSUG 2016 conference registration form either by postal mail, fax, or online (preferred).
  3. You may cancel a seminar on or before April 25, 2016, and receive a full refund minus a $25 administration fee per cancelled seminar.
  4. You may add a seminar on or before April 25, 2016 for no additional fee. To sign up for an additional seminar after you have already registered for the conference, please contact the This email address is being protected from spambots. You need JavaScript enabled to view it..
  5. On or before April 25, 2016, you may swap one seminar for another; however, this is considered a change in conference registration and will incur a $25 administration fee.
  6. After April 25, 2016, you MAY NOT SWAP seminars; however, a new seminar may be added depending on space and availability.
  7. There will be NO REFUNDS after April 25, 2016. However, if you are unable to attend, the seminar material will be provided to you (either by postal mail or email) without additional charge.
  8. Should a seminar be cancelled at any time for any reason, the sole liability of PharmaSUG and the instructor is a refund of the seminar fee, and they are NOT liable for any special or consequential damages arising from the cancellation of the seminar.
  9. On-site registration will be permitted based on space and availability, and payable by major credit card (MC, VISA, Discover, AMEX). However, seminar materials may not be available on-site but will be provided later to paid attendees.
  10. You may sign up for seminars occurring at the same time, i.e., you can attend one class and ask for material for another class, bearing in mind that tuition must be paid for both seminars.

For questions about the above seminar policy and availability, please contact Matt Becker and Venky Chakravarthy, Seminar Coordinators, at This email address is being protected from spambots. You need JavaScript enabled to view it..

Course Descriptions

Advanced Reporting and Analysis Techniques for the SAS® Power User: It's Not Just About the PROCs!
Art Carpenter
Saturday, May 7, 2016, 8:00 AM - 5:00 PM

This one day course presents a series of those nuggets. It covers a broad range of SAS topics that have proven to be useful to the intermediate and advanced SAS programmer who is involved with the analysis and reporting of data. The intended audience is expected to have a firm grounding in Base SAS. For most of the covered topics, the course will introduce useful techniques and options, but will not ‘teach the procedure’. No matter how experienced we are, no matter how well we know a procedure or a technique, there is still more that we do not yet know.

The course includes options and techniques associated with:
  • New, powerful, and little used options in MEANS/SUMMARY
  • Reporting procedures including TABLULATE and REPORT
  • Understanding more about the REPORT compute block in the DATA step (functions, options, statements)
  • Working with data
  • Taking full advantage of formats
  • Interfacing with the Macro Language
  • Output Delivery System, ODS, extras
  • Operating System Interfaces and how you can take advantage of them
  • Advanced Table look-up techniques
  • Importing and exporting data
  • . . . . much, much more

Data Sharing is Data Caring – De-Identifying and Anonymizing Patient Data to Protect Patient Privacy and Honor Informed Consent
Dave Handelsman
Saturday, May 7, 2016, 8:00 AM - 12:00 PM

Clinical trial data, whether in support of clinical trial data transparency, journal publication, or planning new development and marketing strategies, requires that individual patient data be disassociated from the real-world patients that have contributed their data during the clinical trial process.  This disassociation, whether it’s referred to as de-identification or anonymization, is required to both protect patients from having their privacy compromised as their data is shared, as well as to avoid violating informed consent agreements.

As the pressure to make these valuable data assets available increases, biopharmaceutical companies are working toward the most efficient means to de-identify patient-level data while limiting the risk of patient re-identification and, at the same time, retaining the data’s utility.

During this seminar, a variety of industry-published de-identification strategies (such as those from TransCelerate and PhUSE) will be discussed, and a practical comparison of the different operational techniques for de-identifying data will be provided. As part of this seminar, several datasets will be de-identified live with help from the audience.

By the conclusion of this seminar, audience members will have a keen understanding of the challenges associated with patient-level clinical trial data de-identification, and the means to begin addressing those challenges.

The SDTMIG: Beyond the Modeled Domains and Other Implementation Challenges
Fred Wood, Jerry Salyers
Saturday, May 7, 2016, 8:00 AM - 12:00 PM

This course will cover aspects of the SDTMIG that, in our experience, frequently present the greatest challenges to sponsors. These include the use of variables in the SDTM but not in domain models, when to create custom domains, and when to use Findings About rather than a custom Findings domain. In addition, considerations around when to create Supplemental Qualifiers and how to relate them back to parent domains via the most efficient IDVAR values will be presented.

Other problematic challenges include the use of relative Timing variables as updated in SDTMIG 3.2, the submission of legacy terms in addition to CDISC Controlled Terminology, misuse of variables, not following conventions established for modeled domains when creating custom domains, and the creation of Trial Design datasets. The course will also include examples and exercises that highlight some of the newer domains and concepts in SDTMIG 3.2, as well as some planned for SDTMIG v3.3. The exercises will be used 1) to generate discussion, and 2) so that attendees can assess their overall understanding of SDTM as well as the concepts presented in the course material. The exercises will not require the use of computers or the knowledge of SAS®.

Clinical Graphs using SAS®
Sanjay Matange
Saturday, May 7, 2016, 1:00 PM - 5:00 PM

Graphs used in the Health and Life Sciences domain and Clinical Research have special requirements to display data in a clear and concise manner including raw data and derived statistics. Data needs to be displayed by treatment, visit and other classifiers along with related information such as Subjects at Risk aligned with the horizontal or vertical axis. This ½ day presentation will introduce you to the key concepts of the SGPLOT and SGPANEL procedures including the layering of plot statements to create the graph you need. We will review the process and features by creating graphs commonly used in the Pharmaceutical industry. These include Mean Change in QTc by Visit, Distribution of ASAT by Time and Treatment, Survival Plot, Forest Plots, Adverse Event Timeline, Waterfall Chart for Change in Tumor Size, Distribution of Maximum LFT Values by Treatment, Swimmer Plot, Panel of LFT Shifts by Treatment and Immunology Profile.

Audience: Graph programmers
Required: Basic SAS programming skills

Define-XML for SAS® Programmers
Lex Jansen
Saturday, May 7, 2016, 1:00 PM - 5:00 PM

Extensible Markup Language (XML) is a markup language that defines a set of rules for encoding documents in a format that is both human-readable and machine-readable. It is an open standard that was developed by the Worldwide Web Consortium (W3C) in order to provide a flexible way to create common information formats and share both the format and the data on the World Wide Web, intranets, and elsewhere. CDISC is a global, open, multidisciplinary, non-profit organization that has established standards to support the acquisition, exchange, submission and archive of clinical research data and metadata. The CDISC XML Technologies Team creates publishes several CDISC standards in an XML representation. These XML standards include the Operational Data Model (ODM) and several ODM extensions:
  • Define-XML
  • Controlled Terminology in XML (CT-XML)
  • Dataset-XML
  • Analysis Results Metadata for Define-XML 2.0.
The SAS® Clinical Standards Toolkit is the framework used by SAS® to support Health and Life Sciences industry data model standards. It is targeted at advanced SAS programmers and supports working with several XML based CDISC standards, such as ODM, Define-XML, Dataset-XML and CT-XML. This presentation will first introduce XML and will then give an overview of XML standards that are relevant to Define-XML for validation (XML Schema, Schematron) and transformation (XSL stylesheets). We will also introduce CDISC XML based standards: ODM, Define-XML and the Analysis Results Metadata extension for Define-XML 2.0. We will then give examples of the way the SAS® Clinical Standards Toolkit supports the Define-XML standard (including Analysis Results Metadata for ADaM). A goal of the seminar will be to gain a better technical understanding of CDISC based XML standards that are relevant to Define-XML and what the ways are in SAS to efficiently support those XML standards.

Intended audience: SAS programmers familiar with Base SAS and CDISC, and an interest in a technical presentation
Required: Some knowledge of XML is beneficial, but not needed

Cleaning, Validating, and Reshaping Your Data: Taking Advantage of SAS® Tools
Art Carpenter
Sunday, May 8, 2016, 8:00 AM - 12:00 PM

The procedures of SAS along with the DATA step provide the programmer and data analyst access to flexible programming power unavailable in any other programming language. Along with that power comes the complexity of multiple solutions to many common programming tasks. This class covers a number of Intermediate and Advanced SAS programming topics that offer solutions that take advantage of techniques that are not employed by a majority of SAS programmers. Based on Art’s latest book, Carpenter’s Guide to Innovative SAS® Techniques, published in the spring of 2012, this course will extend the knowledge and tool set of SAS programmers that work with data.

During this seminar we will:
  • Learn to create user defined formats and functions to clean and validate your data
  • Use multiple techniques to sparse and display sparsed data
  • Extend PROC COMPARE with the Macro Language to automate data comparisons
  • Explore alternative techniques to PROC TRANSPOSE when reshaping your data
  • Discover how to display and report on all levels of classification variables, even when they are not in the data
  • Learn several ways to form discrete buckets for continuous data
Intended Audience Level: Intermediate and Advanced
Delivery Method: Seminar style
Class Material: Copy of the PPT slides

ADaM Datasets: Creation and Applications
Nancy Brucken, Mario Widel, Paul Slagle
Sunday, May 8, 2016, 8:00 AM - 12:00 PM

This half-day course shows you how to develop your CDISC ADaM datasets to meet your specific statistical analysis needs, such as t-tests, proportions, time to events, occurrence data (adverse events, concomitant medications) and ANOVA. Students will learn specifics of the published ADaM dataset structures and how to apply them to their own clinical study data. Additionally, we will examine situations that don’t fit the published structures, like multivariate analyses, and describe options for handling them.

Visualization (SAS®, JMP, R, Qlik and Tableau)
Greg Nelson
Sunday, May 8, 2016, 8:00 AM - 12:00 PM

Data means little without our ability to visually convey it. Whether building a business case to open a new clinic, presenting research findings, estimating patient volumes, displaying incidence rates or comparing the relative effectiveness of a therapy, we are crafting a story that is defined by the graphics that we use to tell it.

Great visualizations start with how people learn and think. This influences the techniques we use for communication and the role that visualization plays in storytelling. Using examples from across health and life sciences, students will learn how to critically think about visualizations and learn how to become more discerning in your review of graphical displays of data.

Through a series of case studies, students will also get an opportunity to practice the design of data displays through small group projects designed to exercise skills in critical thinking. Here we will review common techniques for creating graphics in statistical packages such as SAS, JMP, R, Qlik and Tableau. Users do not have to have expertise in the software packages, but code samples will be used so that students can gain an appreciation of what it takes to create them.

By the end of the course, students should have a strong understanding of data storytelling and how techniques across a number of software packages can support that process. Each student will have access to the gallery of graphic examples complete with code for the languages in which they were developed as well as access to continuing education resources for ongoing learning and application of your newly formed skills.

Suitable for all experience levels, the goal of this workshop is to share techniques and best practices that can be used to design, create and evaluate data visualizations.

Building Dynamic Programs and Applications Using the SAS® Macro Language
Art Carpenter
Sunday, May 8, 2016, 1:00 PM - 5:00 PM

This seminar shows you how to take advantage of SAS Macro Language capabilities that enable you to write dynamic programs and applications. By mastering the concepts and techniques presented in this class your programs will become free of hard-coded data dependencies, thus eliminating the need to re-write the code every time a data set name, variable name, or other data attribute, changes. Let “them” change the project's specifications as often as “they” want - your code is ready!

The dynamic programming techniques that you will learn about during this seminar:
  • Are flexible and are easily adaptable to changing data structures, data table names, and variable (field) attributes
  • Reduce maintenance requirements by removing data dependencies from within the programs
  • Provide significant resource savings during program/application development cycles
  • Gives the end-user extensive control over program execution by using tables such as SAS data dictionaries, SAS data sets, and Excel tables
  • Reduce program validation efforts by providing reusable and generalized code that can be applied to many different applications
  • Establish controlled data environments, thus insuring data integrity throughout your organization
This course makes extensive use of example macros that have been gathered from real world applications, and it concentrates on the techniques necessary to make effective use of these tools.

Essential SAS® Programming Techniques for Perl®, Python® and R® Users
Kirk Paul Lafler
Sunday, May 8, 2016, 1:00 PM - 5:00 PM

In an age where many software languages and products have come and gone, one language, SAS® software, has become a mainstay for users over its 4-plus decade history. Within small, medium and large organizations around the globe, SAS software offers users a powerhouse of features and capabilities. With a very supportive user population, SAS software is used by millions of users in more than 75,000 business, government and university customer sites in 139 countries. SAS Institute predicts the future for users to be very bright for programmers, data analysts, analytic specialists and statisticians in 2016 and beyond; with demand projections expected to climb to even higher levels. Still, three powerful “open” source software languages have come of age; Perl, Python and R, and are currently being taught to the current and next generation of young professionals on many of our University campuses. This course demonstrates the power of the SAS software emphasizing essential SAS programming techniques including reading external data; reading Excel spreadsheet data; subsetting data; implementing logic conditions with IF-THEN/ELSE; working with missing values; working with dates; sorting data; by-group processing; appending (concatenating) data; transposing data; match-merging two datasets; producing detail output; producing summary output; producing frequency output; producing statistical output; producing HTML output; producing PDF output; and producing graphical output.

Intended Audience: All SAS users
Prerequisites: No Base-SAS programming experience necessary
Delivery Method: Instructor-led training with code examples
Course Material: Course Notes are provided

FDA Submission Data Requirements
Dave Izard
Sunday, May 8, 2016, 1:00 PM - 5:00 PM

SAS® statistical and programming professionals work tirelessly contributing to CRF & clinical database design, protocol & SAP development, analysis dataset design & implementation and the generation of tables, figures and listings in support of clinical trials. If the compound under study successfully navigates clinical and regulatory hurdles, most of these items will make their way into a regulatory submission to the FDA. The FDA has now issued final versions of two guidance documents, a companion technical specifications document and the continued support for a data standards catalog. These documents have moved the needle with respect to Sponsor and CRO organization obligations in terms of how they plan and execute studies as well as prepare clinical assets for inclusion in a regulatory submission. This highly interactive seminar will review each asset, its role in the submission and the impact that these final guidance documents have on how the asset is handled as it weaves its way through the drug development lifecycle on its way to the FDA. A portion of the seminar will be dedicated to a discussion of “hot off the press” topics, including a review of FDA behavior since these documents have been finalized including Sponsor feedback during the review period.

Audience Level: Beginner to Intermediate – individuals who are new to the Pharmaceutical industry would benefit greatly for the opportunity to put their hard work creating analysis datasets and TLFs into the context of a regulatory submission. Conversely, experienced professionals who have created submission assets in the past who are looking for a refresher on recent changes to FDA requirements, CDISC standards and the future outlook on submission data requirements for other global regulatory bodies would also enjoy this seminar.

An In-Depth Look at PROC REPORT
Jane Eslinger
Wednesday, May 11, 2016, 1:00 PM - 5:00 PM

This seminar session will explore one of the most powerful reporting procedures in SAS: PROC REPORT. It will focus on the procedure’s most used capabilities: header creation, border control, calculating percentages, and creating multiple summary rows. In addition, the session will go over the differences between PROC REPORT and PROC TABULATE and when you might want to use one over the other.

Introduction to Enterprise Guide
Ben Cochran
Wednesday, May 11, 2016, 1:00 PM - 5:00 PM

This course introduces the student to Enterprise Guide, a product with is a point and click interface to the power and functionality of the SAS system. Enterprise Guide gives the student query tools to access the needed data, analyze the data, and then gerate all kinds of reports and graphs from the data...all in a very easy to use interface. This product is a great introduction to the SAS system...and a whole lot more.

Building Clinical Trial Dashboards Using Base-SAS Software
Kirk Paul Lafler, Roger Muller, Josh Horstman
Wednesday, May 11, 2016, 1:00 PM - 5:00 PM

The concept of dashboards, which serve to display the current status of “point-in-time” metrics and key performance indicators, is often associated with business intelligence. However, such tools can have enormous utility within the clinical trial arena as well. Effectively designed dashboards extract real-time data from multiple sources for the purpose of highlighting important information, numbers, tables, statistics, metrics, performance scorecards and other essential content on a single screen. Applications include monitoring the ongoing conduct of a trial and managing the process of creating and validating statistical outputs for large and complex clinical reporting efforts.

This seminar explores best practice programming techniques in the design of highly interactive, filterable, and drill-down dashboards using Base-SAS® software. Attendees learn how to create effective dashboards with a purpose not in weeks or months, but in hours, using Base-SAS® programming techniques including DATA step, PROC FORMAT, PROC PRINT, PROC MEANS, PROC SQL, Enterprise Guide, ODS, ODS Statistical Graphics, PROC SGRENDER, PROC SGPLOT, PROC SGPANEL, PROC TEMPLATE, PROC DOCUMENT, HTML and JavaScript.

Intended Audience: All SAS users
Prerequisites: Minimum 1-year Base-SAS programming experience
Delivery Method: Instructor-led training with code examples
Course Material: Course Notes are provided

Learning R for SAS Users
Arthur Li
Thursday, May 12, 2016, 8:00 AM - 5:00 PM

If you are a SAS programmer, have you ever thought of using an alternative language to validate your results that are generated from SAS? R will be the perfect choice for you because R is not only an open-source software but almost all the tools that you use in SAS to manage your data can also be found in R in similar methods.

The focus of this seminar will be on managing and manipulating data by using R software. The topics include arithmetical expressions of R objects, control structures, data input and output, subsetting objects, data manipulations and aggregation, and writing user-defined functions.

Although this is a lecture-based seminar, I would recommend that you bring your own laptop to the lecture and have R installed on your laptop (www.r-project.org) if you’ve never used R before. We can run some examples together during the break time.

Instructor Biographies

Nancy Brucken

Nancy Brucken has been an ADaM team member since 2011. She was a member of the ADaM General Occurrences sub-team, and currently co-leads the ADaM Questionnaires, Ratings and Scales sub-team, and participates on both the ADaMIG v1.2 sub-team and the Rheumatoid Arthritis Therapeutic Area team. She is a graduate of Marietta College and the University of Michigan, and a devout Ohio State Buckeyes fan.

Art Carpenter

Art Carpenter’s publications list includes five books, and numerous papers and posters presented at SUGI, SAS Global Forum, and other user group conferences. Art has been using SAS® since 1977 and has served in various leadership positions in local, regional, national, and international user groups. He is a SAS Certified Advanced Programmer and through California Occidental Consultants he teaches SAS courses and provides contract SAS programming support nationwide.

Ben Cochran

After more than 11 years with SAS Institute in the Professional Services division (as an instructor) and Marketing Departments (as Marketing Manager for the SAS/EIS product), Ben Cochran left to start his own consulting and SAS Training business in the fall of 1996 - The Bedford Group, Inc. As an affiliate member of SAS Institute's Alliance Partner Program, Ben has been involved in many consulting projects for over 18 years and has been teaching SAS courses since 1985. For the last few years, Ben has been chosen to be one of about a dozen 'Loyalty Partners' by SAS Institute. Ben has authored and presented dozens of papers at SUGI/SAS Global Forum conferences and regional user groups on a variety of topics since 1988.

Jane Eslinger

Jane Eslinger is a Senior Technical Support Analyst at SAS Headquarters in Cary, North Carolina. In the five years that Jane has been at SAS, she has achieved certifications as an Advanced Programmer for SAS 9 and as an Advanced Visual Business Analyst. She presented a paper on compute blocks in PROC Report at the 2015 SAS Global Forum and has presented at numerous conferences and users’ groups. In her day-to-day work, Jane enjoys supporting SAS customers using ODS and Base SAS procedures, with an emphasis on PROC REPORT. Prior to arriving at SAS, Jane served as a statistician and statistical programmer in the social science and clinical research fields. She earned her Bachelor of Science in Statistics from NC State University.

Dave Handelsman

Dave Handelsman is a healthcare and life sciences expert with more than 25 years of industry, software and management experience.   As the Senior Director of Strategy and Product Development at d-Wise, Dave is responsible for sustaining d-Wise’s growth and evolution, while further establishing d-Wise as the go-to technology and consulting organization for healthcare and life sciences businesses. Prior to joining d-Wise in February 2014, Dave held leadership roles at SAS, ClinTrials Research and PRA. He is currently the post-Chair of the CDISC Advisory Council.

Josh Horstman

Josh Horstman is an independent statistical programmer with 18 years experience using SAS in the pharmaceutical industry. He has experience working for GlaxoSmithKline, Eli Lilly and Company, inVentiv Health, and others. Josh has presented numerous papers at PharmaSUG, SAS Global Forum, and other SAS User Group meetings. He holds a bachelor's degree in mathematics and computer science, and a master's degree in statistics from Colorado State University.

Dave Izard

Dave Izard frequently finds himself at the intersection of clinical data standards, regulatory expectations and sponsor organization needs and desires. A pharmaceutical professional since 1997, he current serves as the Clinical Data Consulting Lead for Accenture’s Accelerated Research & Development Shared Services after leading Octagon Research Solutions / Accenture’s SDTM practice for 6 years. Prior to joining Octagon / Accenture he served in a variety of Clinical Programming leadership roles at both GSK and Shire. He has served as a paper author & presenter, seminar instructor and section chair at industry conferences including the Pharmaceutical SAS Users Group (PharmaSUG), the Society of Clinical Data Management (SCDM) and various local and regional SAS meeting. His current PhUSE efforts include supporting the development of the Study Data Standardization Plan and Legacy Data Conversion Plan & Report templates as well as the revised Site Selection / OSI BIMO guidance. He holds Bachelors and Masters of Science Degrees in Computer Science from Bucknell and West Chester University respectively.

Lex Jansen

Lex Jansen is a Principal Software Developer at SAS Institute, Health and Life sciences R&D. In this role he develops software that supports data standards in the pharmaceutical industry. He is one of the developers working on the SAS Clinical Standards Toolkit. Prior to working at SAS he was a Senior Consultant, Clinical Data Strategies at Octagon Research Solutions, Inc. In this position Lex worked on client consulting projects dealing with the assessment, design and/or implementation of CDISC standards. Previous to his employment with Octagon, he held various positions in the 16 years that he worked at the pharmaceutical company Organon. Lex holds a MSc in Mathematics from the Eindhoven University of Technology in the Netherlands. Since 2008 Lex has been a member of the CDISC XML Technologies Team, where he has been active in the development of various CDISC standards: Define-XML 2.0, Dataset-XML and the Analysis Results Metadata extension for Define-XML 2.0. Lex owns the website (www.lexjansen.com) which is well-known in the SAS community and contains almost 28,000 links to papers that were presented at major SAS User Group conferences.

Kirk Paul Lafler

Kirk Paul Lafler has been programming in SAS since 1979 and is consultant and founder of Software Intelligence Corporation. He is a SAS Certified Professional, application developer, data scientist, sasCommunity emeritus advisory board member, mentor, and provider of IT consulting services and training to SAS users around the world. As the author of six books including Google Search Complete! (Odyssey Press. 2014) and PROC SQL: Beyond the Basics Using SAS, Second Edition (SAS Institute. 2013); he has written more than five hundred papers and articles; been an Invited speaker at five hundred-plus SAS International, regional, special-interest, local, and in-house user group conferences/meetings; and is the recipient of 23 “Best” contributed paper, hands-on workshop (HOW), and poster awards.

Arthur Li

Arthur holds an M.S. in Biostatistics from the University of Southern California. Currently, he is a Biostatistician at the City of Hope National Medical Center. In addition, Arthur developed and taught an introductory SAS course at U.S.C. for the past seven years, as well teaching the Clinical Biostatistics Course at U.C.S.D. extension. As well as teaching and working on cancer-related research, Arthur has written a book titled “Handbook of SAS® DATA Step Programming.”

Sanjay Matange

Sanjay Matange is R & D Director in the Data Visualization Division at SAS, responsible for the development and support of ODS Graphics. This includes the Graph Template Language (GTL), Statistical Graphics (SG) procedures, ODS Graphics Designer and other related graphics applications. Sanjay has been with SAS for over 20 years, co-author of two patents, author of three SAS Press books and author of Graphically Speaking, a blog on data visualization.

Roger Muller

Roger D. Muller, Ph.D. has been as SAS user for over 40 years, primarily in the life sciences, business marketing, and educational areas. His current interests are in creative display of textual and graphical information using a wide variety of SAS products.

Greg Nelson

Greg is the founder and CEO of ThotWave Technologies, a niche consultancy specializing in healthcare analytics. With certifications in Healthcare IT, Project Management, Six Sigma and Balanced Scorecard, Greg is also a prolific writer and has presented over 200 professional and academic papers in the United States and Europe. Before starting ThotWave, he worked for i3/Ingenix, the Gallup Organization and a boutique research firm in Palo Alto, California.

Jerry Salyers

After a career in Data Management at Procter and Gamble Pharmaceuticals, Jerry joined Fred Wood’s Data Standards Consulting group within Accenture Life Sciences providing internal consulting services while also working one-on-one directly with clients in review of legacy-data mapping to SDTM-based datasets.. He also creates and delivers training classes on both CDASH and the SDTM to internal functions, and custom training to external clients. Jerry is also a certified CDISC instructor for both CDASH and SDTM.

Paul Slagle

Paul is Director of Data Standards for InVentiv Health Clinical and leads a team of SDTM and ADaM consultants and programmers. Paul is active in CDISC and is currently participating in the ADaM team the oncology sub team. He is also working on the CFAST team providing ADaM guidance to the Breast Cancer therapeutic area guide. Paul has been active in the using of CDISC since 2004 implementing SDTM followed by ADaM standards in clinical trials. He is SAS programmer with over 30 years’ experience.

Mario Widel

Mario is a Research Scientist at Eli Lilly and Company. He has been involved in CDISC related activities since 2007. In his current role Mario oversees and participates in the metadata definition for SDTM and ADaM datasets, the design, creation and validation of TFL’s. He is a regular presenter at conferences like JSM, PharmaSUG, SAS Global Forum, PhUSE and CDISC. Mario is an authorized CDISC instructor.

Fred Wood

Fred leads the Data Standards Consulting Group for Accenture Accelerated R&D Services. He is one of the principal contributors to the SDTM. Fred is a founding member of the CDISC SDS, SEND, and Devices Teams, and has led or co-led these for many years; he currently serves on the Leadership Teams of all three. Fred is a member of the CDISC Standards Review Council, and has been on many other CDISC teams since 1999.