Enhance your PharmaSUG experience by attending optional pre- and post-conference training seminars taught by seasoned experts. Half-day courses are only $200 with a conference registration, or $400 without a conference registration, while full-day courses are $400 with a conference registration, or $600 without. Space is limited!

Register here if you are signing up for a seminar only. If you are also planning to attend the conference, please register for both the conference and seminars on the Conference Registration page.

Sunday, May 19, 2024

Course Title (click for description) Instructor(s) (click for bio) Time
#1 End-to-End Electronic Submission Components for Regulatory Submission of Clinical Study Data Prafulla Girase
& Nate Freimark
8:00 AM - 5:00 PM
#1-1 Understanding and Creating Define-XML 2.1 using SAS® openCST Lex Jansen 8:00 AM - 12:00 PM
#1-2 Introduction to the Production of Tables, Listings, and Figures (TLFs) Using Python, R, and SAS® Kirk Lafler 8:00 AM - 12:00 PM
#2-2 Code Crunchers: Mastering Statistics for Programmers with Precision and Power Jim Box 8:00 AM - 12:00 PM
#2-1 Navigating LLM / ChatGPT Revolution - From Its Potential to Practical Application Kevin Lee 1:00 PM - 5:00 PM
#1-3 CDISC ARS Standards Training - Streamlining Analysis Results Reporting Bhavin Busa
& Bess LeRoy
1:00 PM - 5:00 PM
#2-3 Advanced ADaM Topics: Avoiding ADaM Pitfalls Sandra Minjoe
& Mario Widel
1:00 PM - 5:00 PM

Wednesday, May 22, 2024

Course Title (click for description) Instructor(s) (click for bio) Time
#3-1 Share Your Code with SAS Packages – Tutorial from 0 to Hero Bartosz Jablonski 1:00 PM - 5:00 PM
#3-2 Hands-On Functions: How to Build Your Own User-Defined FCMP Functions and Macro Functions Troy Martin Hughes 1:00 PM - 5:00 PM
#3-3 Mastering Statistical Hypothesis Testing Using R with Comparisons to SAS Ryan Lafler
& Daniela Nuñez
1:00 PM - 5:00 PM
#3-4 SDTM – A Deeper Dive Into the Basics and Beyond Soumya Rajesh
& Kristin Kelly
1:00 PM - 5:00 PM




Course Descriptions

End-to-End Electronic Submission Components for Regulatory Submission of Clinical Study Data
Prafulla Girase, Nate Freimark
Sunday, May 19, 2024, 8:00 AM - 5:00 PM


A regulatory submission of clinical study data also needs to be accompanied by various other electronic submission (eSUB) components such as Define-XML, annotated CRF, study data reviewer’s guide, analysis data reviewer’s guide etc. This seminar will take a deep dive into each of these components. It will educate attendees about various requirements, best practices, consistency checks etc. It will also go over key considerations related to preparation of a whole eSUB package for a submission such as folder structure considerations, PDF validation practices, final package checklist, regulatory hand-off etc.

Prerequisite: Very basic knowledge of eSUB components.
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Understanding and Creating Define-XML 2.1 using SAS® openCST
Lex Jansen
Sunday, May 19, 2024, 8:00 AM - 12:00 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 Data Exchange Standards Team 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)
  • Analysis Results Metadata for Define-XML 2.x.
The Open SAS® Clinical Standards Toolkit is an open-source framework 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.x. We will then give examples of the way the Open-source release of 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.
Note: This is not an official CDISC training seminar.
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Introduction to the Production of Tables, Listings, and Figures (TLFs) Using Python, R, and SAS®
Kirk Lafler
Sunday, May 19, 2024, 8:00 AM - 12:00 PM


The streamlined production of Tables, Listings, and Figures (TLFs) in a clinical study represents essential elements of a Statistical Analysis Plan (SAP) by providing answers to regulatory questions along with the necessary support documentation for the clinical data contained in them. Tables are derived from source data and often involve the manipulation of data, listings represent the various reports that are generated in file formats like Rich Text Format (RTF), and figures representing graphical output that provides visual clarity and understanding of the data. This course provides attendees with an introduction to the production of TLFs using Python, R, and SAS® software.

Seminar Topics
  • Introduction to Tables, Listings, and Figures (TLFs) in Clinical Studies.
  • Terms, Abbreviations, Acronyms, and Definitions.
  • Statistical Analysis Plan (SAP) Defined.
  • Highlight a SAP for Clinical Studies.
  • Review ICH E3 and Clinical Study Report (CSR) Template.
  • Explore an Example Clinical Study Report (CSR).
  • Explore the Types of Data: Nominal, Ordinal, Interval, and Ratio.
  • A High-level Introduction to Python, R, and SAS software.
  • Process of Data Preparation: Data Cleaning, Data Manipulation, Data Transformation, TLF Planning.
  • Example Tables, Listings, and Figures (TLFs).
  • Process of Producing Tables, Listings, and Figures (TLFs).
  • Packages used to produce TLFs in Python: Rich Text Format (RTF) Output - Pandas, numpy, scikit, matplotlib.
  • Packages used to produce TLFs in R: Rich Text Format (RTF) Output - Tidyverse (Data Manipulation), atable, r2rtf (Reporting in RTF Format).
  • Procedures used to produce TLFs with SAS software: Categorical Data: PROCs – FREQ, SGPLOT, LOGISTIC, GENMOD, GLIMMIX; Continuous Data: PROCs – MEANS, UNIVARIATE, TTEST, NPAR1WAY, GLM, REG, MIXED, NLIN, NLMIXED; Graphing Data: PROCs – UNIVARIATE (Histograms, QQPlots), Statistical Graphics (SG) SGPLOT (Histograms, BoxPlots, BarCharts, ScatterPlots, RegressionPlots, ScatterPlot Matrix), Graph Template Language (GTL); Rich Text Format (RTF) Output: PROCs – SORT, FORMAT, SQL, TRANSPOSE, REPORT, TABULATE, Output Delivery System (ODS); Process of using ODS DOCUMENT in the Creation of TLFs.
  • TLF Validation Activities.
Intended Audience: Programmers, Statistical Programmers, Clinical Scientists, Statisticians, Data Managers, and Others desiring to learn how to produce Tables, Listings, and Figures (TLFs) using Python, R, and SAS Software.

Prerequisites: Basic understanding of Statistics, but no previous Python, R, and SAS experience required
Delivery Method: Instructor-led tutorial with code examples
Seminar Material: e-Course Notes (PDF Format) and code are provided to Attendees.
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Code Crunchers: Mastering Statistics for Programmers with Precision and Power
Jim Box
Sunday, May 19, 2024, 8:00 AM - 12:00 PM


Ever wonder about the statistics behind some of the Tables you program at work? Want to know what p-values really mean? Need to learn about how probability works? Join this class for an introduction to probability and statistics used in clinical research. This is a concepts class, so we won’t go too heavy on the equations, but at the end you’ll understand hypothesis testing and what statistical significance really means.
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Navigating LLM / ChatGPT Revolution - From Its Potential to Practical Application
Kevin Lee
Sunday, May 19, 2024, 1:00 PM - 5:00 PM


ChatGPT is at the forefront of the next revolution, and in this seminar, we're about to embark on a journey that will demystify this remarkable technology. Imagine a virtual assistant that can comprehend and generate human-like text from Clinical Trial Data, a tool that can answer questions about specific patients, write SAS/R/Python codes, assist in content creation such as tables/listing/graphs, and even unleash its creativity in the realm of art. To truly harness its potential, you need to understand how to use ChatGPT in the art of prompt engineering, application development using ChatGPT API in Python/SAS and fine-tuning ChatGPT with your own data. In the seminar, we will embark on an exploration of ChatGPT that will equip you with the knowledge and skills to leverage its capabilities effectively while ensuring ethical and responsible use.

The seminar will cover various aspects of Large Language Models (LLM), with a focus on ChatGPT. It will begin with an introduction to LLM. The seminar then delves into ChatGPT, explaining its purpose, development history, and potential impact on organizations and individuals. The seminar will explore ChatGPT applications, including website prompts, API integration, Python coding and fine-tuning, and presents use cases ranging from simple inquiries, SAS coding, SAS migration to R/Python, to art generation. There's an emphasis on how to effectively use ChatGPT through prompt engineering techniques. Concerns regarding ChatGPT, such as data privacy, bias, and ethical considerations, will be addressed. Finally, the seminar touches on enterprise-level ChatGPT implementation, discussing risk mitigation and regulatory compliance.

After attending the seminar, you will emerge with a comprehensive understanding of the LLM and ChatGPT phenomenon, including its architecture, practical use cases, prompt engineering, and API applications using Python/SAS. You will learn practical skills to effectively utilize ChatGPT in various domains, from effective prompts, content development, coding, art generation and more. Furthermore, you will gain insights into the ethical considerations surrounding LLM and ChatGPT, encompassing data privacy, bias, and regulatory compliance. You will also be equipped with knowledge about enterprise-level ChatGPT implementation and risk mitigation strategies. Ultimately, this seminar will empower you to leverage ChatGPT's transformative potential while adhering to ethical and responsible ChatGPT practices in the Biometrics Department.
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CDISC ARS Standards Training - Streamlining Analysis Results Reporting
Bhavin Busa, Bess LeRoy
Sunday, May 19, 2024, 1:00 PM - 5:00 PM


CDISC Analysis Results Standard (ARS) is set to be a foundational standard and is scheduled to be released in Q1 2024. Join us for an in-depth seminar on the ARS logical model, an initiative to streamline analysis results, covering Tables, Figures, and Listings (TFL). Learn about the background and development of this logical model, geared towards enhancing automation, reproducibility, reusability, and traceability. This is your chance to be industry-ready. Discover insights into the current challenges analysts face in their workflows and our vision for the future state. We'll introduce machine-readable analysis results metadata and structured analysis results data (ARD) representation, aiming to automate statistical outputs. Through practical examples, we'll guide you through the model's elements, demonstrating its potential to elevate traceability, reproducibility, and overall quality in clinical trial analysis and reporting. Reference the CDISC ARS model, project files, utilities, and docs on GitHub at: https://github.com/cdisc-org/analysis-results-standard.

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Advanced ADaM Topics: Avoiding ADaM Pitfalls
Sandra Minjoe, Mario Widel
Sunday, May 19, 2024, 1:00 PM - 5:00 PM


The seminar instructors have been working in the industry, volunteering on the CDISC ADaM team, and giving ADaM training for many years. This seminar pulls together common issues that they have seen and recommends ways to avoid them. Content will cover issues related to the ADaM classes of ADSL, BDS, OCCDS, and ADAM OTHER, including:
  • When to use ADPL in addition to ADSL, vs. ADSL by itself
  • When to use/not use DTYPE
  • What content to put in PARAM vs. PARQUAL
  • When to use BASETYPE and what can be used instead of BASETYPE
  • How to incorporate FDA’s FMQs
  • When to use class ADAM OTHER
Hands-on exercises will be included. Please bring a computer with Excel to get the most out of this seminar.
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Share Your Code with SAS Packages – Tutorial from 0 to Hero
Bartosz Jablonski
Wednesday, May 22, 2024, 1:00 PM - 5:00 PM


When working with SAS code, especially when it becomes more and more complex, there is a point in time when a developer decides to break it into small pieces. The developer creates separate files for macros, formats/informats, and for functions or data too. Eventually the code is ready and tested and sooner or later you will want to share code with another SAS programmer. Maybe a friend has written a bunch of cool macros that will help you get your work done faster. Or maybe you have written a pack of functions that would be useful to your friend. There is a chance you have developed a program using local PC SAS, and you want to deploy it to a server, perhaps with a different OS. If your code is complex (with dependencies such as multiple macros, formats, datasets, etc.), it can be difficult to share. Often when you try to share code, the receiver will quickly encounter an error because of a missing helper macro, missing format, or whatever… Small challenge, isn’t it?

How nice it would be to have it all (i.e. the code and its structure) wrapped up in a single file – a SAS package – which could be copied and deployed, independent from OS, with a one-liner like: %loadPackage(MyPackage).

In the seminar an idea of how to create such a SAS package in a fast and convenient way, using the SAS Packages Framework, will be shared. We will discuss:
  1. concept of a package,
  2. the framework
  3. overview of the process, and
  4. how to build a package.
The intended audience for the presentation is intermediate or advanced SAS developers (i.e. with good knowledge of Base SAS and practice in macro programming) who want to learn how to share their code with others. All materials are publicly available at seminar's GitHub: https://github.com/yabwon/HoW-SASPackages.
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Hands-On Functions: How to Build Your Own User-Defined FCMP Functions and Macro Functions
Troy Martin Hughes
Wednesday, May 22, 2024, 1:00 PM - 5:00 PM


Attend and receive a FREE copy of the author’s 550-page book, SAS® Data-Driven Development: From Abstract Design to Dynamic Functionality, Second Edition, released in 2022! Students will receive the physical book at the training!

“User-defined” functions are those functions that are created by SAS users, as contrasted with “built-in” functions that are part of out-of-the-box Base SAS functionality. SAS provides two methods to build user-defined functions, including the SAS macro language and the SAS Function Compiler (aka PROC FCMP). This introductory course demonstrates how to build user-defined functions (and subroutines)—including both macro functions and FCMP functions. No prior experience with the SAS macro language or PROC FCMP syntax is required. User-defined functions improve software reusability—that is, the ability of code modules to be reused in future software projects, and to be reused by multiple SAS users within a team or organization. Reusability enables a function to be developed once but used repeatedly, which reduces the workload of the SAS users who are writing programs, by enabling us to rely on previously built (and fully tested) code modules. Thus, user-defined functions facilitate more flexible and configurable software, as well as a more productive, efficient SAS team.

This HANDS-ON workshop enables students to run all programs in real-time using SAS Display Manager, SAS Enterprise Guide, or SAS OnDemand for Academics. FCMP function topics comprise approximately 2/3 of the course, and include:
  • Gentle introduction to PROC FCMP syntax and the construction of user-defined functions and subroutines (with the FUNCTION and SUBROUTINE statements, respectively)
  • Use of OUTARGS option to modify multiple arguments (within the calling program)
  • Passing character and/or numeric data types to functions
  • Passing arrays to functions, and utilizing arrays within functions
  • Declaring, initializing, and referencing hash objects within functions
  • Calling functions and subroutines from the DATA step, and from %SYSFUNC and %SYSCALL
  • Calling functions from PROC FORMAT
Macro function topics comprise approximately 1/3 of the course, and include:
  • Gentle introduction to the SAS macro language, including differentiation between SAS macros and SAS macro functions
  • Differentiation between positional and keyword parameters
  • Defining optional parameters and default parameter values
  • Passing macro lists and two-dimensional data structures to functions
  • Use of the PARMBUFF option in the %MACRO statement to facilitate multi-element arguments
  • Macro function argument validation, exception handling, and use of global macro variables as return values / return codes
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Mastering Statistical Hypothesis Testing Using R with Comparisons to SAS
Ryan Lafler, Daniela Nuñez
Wednesday, May 22, 2024, 1:00 PM - 5:00 PM


This half-day course is open to all aspiring and experienced data scientists, statisticians, bioinformatics scientists, and clinical programmers interested in understanding, designing, and developing parametric and non-parametric statistical hypothesis tests for clinical experiments. This course leverages the R and SAS programming languages to conduct statistical hypothesis testing using real-world examples geared towards the pharmaceutical industry, clinical trials, and the biological and life sciences. Attendees are given a rigorous introduction to frequentist hypothesis testing including discussions about parametric statistical distributions, significance levels, error rates, effect sizes, statistical power, standard errors, confidence intervals, and p-values. Attendees also learn about strategies for successful experimental design, controlling for confounding and lurking covariates, handling missing values, and assessing causation against correlation.

Several parametric hypothesis tests including t-tests, Chi-Squared tests, One-Way ANOVA (Analysis of Variance), Factorial ANOVA, and One-Way MANOVA (Multivariate Analysis of Variance) are covered in R with comparisons to SAS, including a thorough discussion of each test’s assumptions, use-cases, output, and limitations. Frequently used non-parametric equivalents including the Mann-Whitney U test, the Wilcoxon Signed-Rank test, and the Kruskal-Wallis test are similarly investigated and developed in R.

By enrolling in this course, each attendee receives the documented R and SAS code files, their personal copy of the PDF version of the slides, and the confidence to successfully perform statistical hypothesis testing in their organization.
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SDTM – A Deeper Dive into the Basics and Beyond
Soumya Rajesh, Kristin Kelly
Wednesday, May 22, 2024, 1:00 PM - 5:00 PM


While SDTM & the SDTMIG have been around for a while, we often need to refresh our memories about the nuances and nitty gritty details surrounding this fundamental standard. This interactive seminar is tailored to cover not only some of the basics of SDTM, but also those topics that, in our experience, pose as challenges to sponsors and programming teams. These include:
  • "Why SDTM": the background and purpose of SDTM
  • "How to do SDTM": high-level concepts about SDTM IG/Model, CT etc.
  • "Ideas" - deeper dive into examples (assumptions, things from knowledge base, etc)
  • New domains and variables introduced in the SDTMIG v3.4, and how to include some of these in the current (3.3) version per FDA request,
  • How to handle visit occurrences in SV
  • Collected versus derived Exposure data, keeping null permissable variables, etc.
The seminar will also include examples and exercises that highlight some of the topics listed above, that could be used to generate discussion, and get an assessment the overall understanding of SDTM by the attendees.

The audience level that this seminar is targeted for is beginner to intermediate - individuals who are new to the pharmaceutical industry: life science / data management professionals/ programmers / statisticians, etc. This would also help experienced SDTM programmers who have created submission datasets in the past who are looking for a refresher on recent changes to the standards.
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Instructor Biographies

Jim Box

Jim has been a data scientist at SAS for the last 10 years, supporting the Life Sciences industry. Prior to that he spent 20 years as a statistician in CROs and has been using SAS software since version 6.08.


Bhavin Busa

Bhavin Busa is the Principal & Co-founder of Clymb Clinical. He is recognized as a thought leader in the areas of data standards, programming, and regulatory submission. He holds a position on the PHUSE Working Group Leadership Committee and serves on the CDISC Open-Source Alliance (COSA) Board. Additionally, Bhavin serves as a CDISC ARS Product Owner/Co-lead and is slated to be the Chair of upcoming PHUSE US Connect 2024.


Nate Freimark

Nate Freimark is Vice President - Clinical Programming and Data Standards at The Griesser Group. Nate is a former CDISC ADaM team lead, one of the ADaM trainers and a member of multiple ADaM and SDTM subteams. Nate is also a member of several PhUSE teams and the ADaM lead for many Therapeutic Area User Guides (TAUGs) and the Tobacco Implementation Guide (TIG) . He has been a member of the ADaM team since 2005, a member of the ADaM Leadership Team since its creation, and has been “doing CDISC” since 2004. Nate has been involved in ADaM Education since its inception from the development of the training material to giving public, private, and FDA ADaM training courses. Nate is also a lead programmer who has worked on numerous projects involving the creation of SDTM and ADaM datasets (and associated defines) as well as the tables, listings, and graphs created based upon them dating back to 2004. He works closely with other project team members within The Griesser Group and outside of The Griesser Group to produce a quality product on time. He has extensive experience with a broad range of therapeutic areas including anti-infective, oncology, and pain management studies. Nate has also been a liaison between integrating companies trying to figure out how best to move forward in a unified CDISC compliant environment.


Prafulla Girase

Prafulla Girase possesses over 22 years of diverse experience in the fields of Statistical Programming, Clinical Data Standards, Statistical Submissions Management. He has served as a lead or co-lead for electronic submissions (eSUB) in numerous NDA/BLA clinical data packages, contributing to the approval of therapies currently available in the market. Prafulla's expertise extends to participating in meetings with regulatory agencies such as the FDA and PMDA, where he has engaged in discussions about data standards and even attended face-to-face data format consultation sessions with PMDA. Recently, Prafulla has become a member of EMA’s industry-focused group for the raw data pilot program. In his present role as a Sr. Director at Alexion AstraZeneca Rare Disease, he assumes responsibility for overseeing Data Standards, Systems, and Early Phase Statistical Programming.


Troy Martin Hughes

Troy Martin Hughes has been a SAS practitioner for more than 20 years, has managed SAS projects in support of federal, state, and local government initiatives, and is a SAS Certified Advanced Programmer, SAS Certified Base Programmer, SAS Certified Clinical Trials Programmer, and SAS Professional V8. He has given more than 100 presentations, trainings, and hands-on workshops at SAS conferences, including at SAS Global Forum, SAS Analytics Experience, WUSS, SCSUG, SESUG, MWSUG, PharmaSUG, BASAS, and BASUG. He has authored three groundbreaking books that model software design and development best practices:
  • PROC FCMP User-Defined Functions: An Introduction to the SAS® Function Compiler (2023)
  • SAS® Data-Driven Development: From Abstract Design to Dynamic Functionality, Second Edition (2022)
  • SAS® Data Analytic Development: Dimensions of Software Quality (2016)
Troy has an MBA in information systems management as well as other credentials, including: PMP, PMI-RMP, PMI-PBA, PMI-ACP, SSCP, CISSP, CSSLP, Network+, Security+, CySA+, CASP+, Cloud+, CISA, CGEIT, CISM, CRISC, ITIL Foundation, CSM, CSD, A-CSD, CSPO, CSP, CSP-SM, CSP-PO, and SAFe Government Practitioner (SGF). He is a US Navy veteran with two tours of duty in Afghanistan.


Bartosz Jablonski

Bartosz Jablonski, PhD - but everyone calls him Bart. A mathematician working and playing with data, an open-minded analyst and science enthusiast. Consultant, seasoned SAS professional (since 2009), and SAS teacher. He gained experience in various domains including: higher education, telecommunication, clinical trials, and banking. Mostly by resolving various analytical and programming tasks using (among others) advanced SAS techniques mixed with domain knowledge or statistical methods. Since 2015 he has led SAS Programming courses at the Faculty of Mathematics and Information Science (Warsaw University of Technology). Author and speaker on various local and international SAS-related conferences. Author, designer, and developer of the SAS Packages Framework. The framework which allows to create SAS Packages - practical, organised, devops oriented, and "easy to work with" code sharing medium for SAS. See: https://github.com/yabwon/SAS_PACKAGES. He's not afraid to admit to be a SAS geek... an active member of Polish SAS Users Group (PolSUG) also "third and a half dan" in www.sasensei.com. To turn on his internal problem solver mode just say: "you probably can't do something like this in SAS..."


Lex Jansen

Lex Jansen is an independent consultant, currently working as Senior Director, Data Science Development at CDISC. Before, Lex was a Principal Solution Consultant at SAS Institute, Health and Life sciences. In this role, he helped customers implement SAS software for clinical research, such as SAS Life Science Analytics Framework (LSAF). Prior to this role he was one of the developers of the SAS Clinical Standards Toolkit. Lex was also one of the Java developers of the SAS Life Science Analytics Framework. 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. Before 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 an active member of the CDISC Data Exchange Standards Team, where he has been active in the development of various CDISC standards: ODM 2.0, Define-XML 2.0/2.1, 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 more than 37,000 links to papers that were presented at major SAS User Group conferences.


Kristin Kelly

Kristin Kelly is a Senior Principal CDISC Consultant at Pinnacle 21. Kristin has more than 15 years of experience working in the pharmaceutical industry primarily focused on clinical data standards. Kristin is involved with the CDISC SDS team as the former Team Lead, various sub-teams within SDS, the SEND Core Team as well as several Phuse Working Groups. She is an authorized CDISC instructor for SDTM. Kristin has also contributed to several FDA projects for both clinical and nonclinical. She is a regular presenter at conferences including the CDISC Interchange, PharmaSUG and PhUSE.


Kirk Lafler

Kirk Paul Lafler is an educator, developer, programmer, consultant, and data analyst; currently working as a lecturer and adjunct professor at San Diego State University and the University of California San Diego Extension; and teaching SAS, SQL, Python, Excel, and cloud-based technology courses to users around the world. Kirk has decades of programming experience and specializes in SAS software, SQL, RDBMS technologies (Oracle, SQL-Server, Teradata, DB2), Python, and other languages and productivity tools. Kirk is the author of the popular PROC SQL: Beyond the Basics Using SAS, Third Edition (SAS Press. 2019) and is actively involved with SAS, SQL, Python, R, ML, and cloud-computing user groups, conferences, and blogs as an Invited speaker, educator, keynote, and leader; and is the recipient of 28 “Best” contributed paper, hands-on workshop (HOW), and poster awards.


Ryan Lafler

Ryan Lafler is the Founder, C.E.O., Chief Data Scientist, and Lead Consultant at Premier Analytics Consulting, LLC, a consulting and contracting business that specializes in providing Big Data Science products and services for our clients. Ryan also serves as an Adjunct Professor at San Diego State University for the Master of Science Big Data Analytics (BDA) Program and the Department of Mathematics and Statistics. He received his Master of Science in Big Data Analytics from San Diego State University after defending and publishing his thesis and graduated with Honors in May 2023. He received his Bachelor of Science in Statistics with a Minor in Quantitative Economics from San Diego State University and graduated Magna cum Laude, with Great Distinction in Statistics. Ryan’s specialties include programming in Python, R, SAS, JavaScript, and SQL for data science, machine learning engineering, deep learning integration, statistical analysis, spatiotemporal analysis, data visualization, interactive dashboard development, and database structuring purposes.


Kevin Lee

Kevin Lee is a passionate Data Scientist and esteemed Machine Learning Leader, boasting two decades of experience in cutting-edge Machine Learning and Data Sciences Services and products within the pharmaceutical industry. His enduring enthusiasm for leadership and innovative technologies has helped him to drive continuous innovation in the Biometric department. Recently, Kevin has found renewed excitement in the immense potential of ChatGPT, particularly in its applications within the pharmaceutical industry. He is eager to contribute his wealth of knowledge and expertise in AI, LLM, and ChatGPT to the dynamic realm of the Biometric Department by pushing the boundaries of technological advancement. As a lifelong learner, Kevin takes pleasure in sharing his extensive knowledge, having delivered over 100 papers. Beyond corporate boundaries, he extends his expertise by imparting insights into Machine Learning, Python programming, data standards, and oncology, both in academic and corporate settings.


Bess LeRoy

Bess LeRoy is the Head of Standards Innovation at CDISC. Bess has been a CDISC team member since 2011. She has over 20 years of experience working in public health research and has held positions at the Framingham Heart Study, the Rotterdam Study, the Arizona Cancer Center, and the Critical Path Institute. Bess has a BS from the University of Michigan, an MPH from Boston University School of Public Health, and is a doctoral candidate at Johns Hopkins Bloomberg School of Public Health.


Sandra Minjoe

Sandra Minjoe started programming in the pharma/biotech industry in 1993 and is currently a Senior Principal Clinical Data Standards Consultant at ICON PLC. She has more than 20 years of experience on the CDISC ADaM team, is a former CDISC ADaM Team Lead, has been part of the ADaM team since 2001, proposed structures that became ADSL and OCCDS, and continues to work on ADaM sub-teams. In addition to her CDISC involvement, Sandra is an emeritus PharmaSUG Executive Committee member.


Daniela Nuñez

Daniela Nuñez is a statistical programmer at Emanate Biostats, Inc., a Carlsbad-based CRO that provides high quality, CDISC-compliant statistical analysis outputs for clinical trials. With extensive programming experience in SAS, R, SQL, and Python, Daniela’s technical expertise allows her to develop innovative solutions to managing clinical data. Well-versed in applications of statistics, analytics, and machine learning, she enjoys building and refining machine learning models to draw the most optimal insight from big data. Aside from working with clinical data, her skill set also includes creating large language models (LLMs), and she continues to take a special interest in natural language processing (NLP), deep learning, and all other applications of artificial intelligence. She graduated with a Bachelor of Science in Statistics from San Diego State University in May 2023.


Soumya Rajesh

Soumya Rajesh is a Sr. Standards Engineer – Global Data Standards at IQVIA, with over 18 years of experience in the CRO Industry, in the areas of SDTM Standards, Programming and Regulatory Operations, in various Therapeutic Areas and study phases. Previous publications and presentations at PhUSE, PharmaSUG & CDISC Interchanges cover topics such as: Sound SDTM & ADaM, Clinical Classifications, Disposition Events, SDTM IG vs. Model, and ISS & ISE Dataset Preparation, and the award-winning paper at PharmaSUG 2019 on Findings About. Soumya is also a CDISC authorized trainer of SDTM & CDASH, a Lead for the CDISC SDS LT, Co-Lead of the SDS NSV sub-team, member of CDASH NSV Registry sub-team, past member of PHUSE Working Groups and PharmaSUG Conference Committee.


Mario Widel

Mario Widel has been involved in CDISC related activities since 2007. In his current role, Mario focuses on ADaM planning, development and documentation for regulatory submission. He is an authorized CDISC instructor and has presented at numerous conferences including PharmaSUG, JSM, SAS Global Forum and PhUSE.