Author: John Brega, PharmaStat, LLC, Newark, CA
Date: Tuesday, June 10th, 2014
Presented at: Bay Area CDISC Implementation Network

We frequently give this presentation to new clients, to let them know what to expect when planning a submission. Topics of this conversation include:


  • Strategy and planning
  • Specifying project deliverables
  • Production and QC of analysis datasets and TFLs
  • Evaluation of project deliverables
  • Assembling and auditing the data submission
  • Fielding FDA requests
  • 120 Day Safety Update
  • Preparing for the Advisory Committee meeting

Author: John Brega, PharmaStat, LLC, Newark, CA
Date: Wednesday, July 24th, 2013
Presented at: Bay Area CDISC Implementation Network

This presentation de-mystifies the Define.xml 2.0 documentation standard by:

  1. Introducing the new features in Define.xml 2.0 with examples of familiar problems they solve
  2. Comparing display-formatted documentation from 2.0 with1.0 for a variety of use cases
  3. Pointing out challenges in collecting metadata content for the new features
  4. Discussing methods for managing user-editable content

Author: Linda Collins
Date: Tuesday, September 25th, 2012
Presented at: PhUSE Single Day Event, San Diego

The ODS Statistical Graphics package contains a powerful set of graphical elements. One especially useful feature of this package is the way that these elements can be combined.  With small changes in syntax, one can present several different kinds of information on a single graph, or use a layout as a prototype for a set of related graphs. This presentation will show some examples of techniques for combining various types of graphs – line graphs, series, bar charts or sets of text entries – into a coordinated presentation.


Author: Elizabeth Li, Carl Chesbrough, PharmaStat, LLC, Newark, CA
Date: Sunday, June 10th, 2012
Presented at: PharmaSUG 2012

It is becoming more common for regulatory submissions to include define.xml – the data definition documents for Study Data Tabulations Model (SDTM) data, Analysis Data Model (ADaM) data, and even legacy data.  Although define.xml documents can help regulatory reviewers to navigate submission datasets, documents and variable derivations, they usually do not print out properly on paper.  One solution is to generate a define.pdf document with the same content as the define.xml.  The portable document format (PDF) file includes bookmarks and hyperlinks to facilitate online review, and it can also be printed out for hardcopy review.  Providing define.pdf documents can help sponsors remove obstacles to the review of their regulatory submissions.

This paper presents tips for using SAS® Version 9.3 Output Delivery System (ODS) rich text format (RTF) to generate an RTF file, and then use Acrobat’s PDF Maker to convert it to a define.pdf document.  It discusses reasons for the use of ODS RTF instead of ODS PDF.  It demonstrates how to create a user-defined style using SAS® PROC TEMPLATE.  It shows how to use RTF code to set up bookmarks and hyperlinks to internal as well as external locations.  It provides examples of using other RTF code to improve formatting of the RTF document.  The features of bookmarks, hyperlinks, headings, and other formatting details are important to an online review of any document.


Author: Micaela Salgado-Gomez, PharmaStat, LLC, Newark, CA
Date: Thursday, November 3rd, 2011
Presented at: San Diego CDISC User Network Meeting, San Diego November 2011

This presentation discusses the Common Data Standards Issues Document issued by CDER which describes reviewer’s experience with submitted SDTM data , recommendations for standard data preparation, and the impact of the recommendation on SDTM and ADaM preparation.


Author: Elizabeth Li, Linda Collins, PharmaStat, LLC, Newark, CA
Date: Friday, June 10th, 2011
Presented at: PharmaSUG 2011

In the CDISC era, biotechnology and pharmaceutical companies are paying increasing attention to how analysis dataset specifications are documented and accuracy of datasets that are generated.  It has always been a desirable practice to record the details about analysis datasets, including the structure of the dataset, the source of data variables, the logic of derivations, and methods of special data handling.  For FDA submissions that include analysis data model (ADaM) datasets, the analysis data specifications must be included in submission documentation.  The use of independent programming is increasingly a gold standard validation method.  In this paper, we describe techniques for leveraging analysis data specifications to automate processes in producing analysis datasets, quality control of the data by independent programming validation, and generating Data Definitions (define.xml) content.  The result of this process is increased confidence in the quality of the data and the reliability of the documentation.


Author: Linda Collins, Lisa Brooks, Michael Rea, Alan Hopkins
Date: Friday, June 10th, 2005
Presented at: Proceedings of the Western Users of SAS Software Conference

There’s an intrinsic tension between setting up an elegant, modular programming system and writing simple, easy-tounderstand programs. Macro libraries have enormous value as a production tool; they allow common applications to be written, validated, and reused easily. However, they often contain a great deal of obscure code designed to produce ‘pretty’ results. For some audiences – such as a statistician or regulatory reviewer who wants to verify that the desired procedures were coded correctly – a simple, straightforward program is preferable. The ideal program for this audience contains only the procedures necessary to produce statistical results (see CDISC Analysis Data Model Version 2.0).

In this paper, we present a technique for satisfying both needs. The framework is an application macro library that runs common SAS® statistical procedures and produces a finished report. A program run generates both a publication-quality statistical table and a simple program containing only the data pre-processing and statistical procedures. The generated code is executable as a portable, stand-alone program, which does not require access to the original macro library. The simplified code can be used for debugging, to verify correct use of the macro library, and as a record of the steps and procedures used to program the table.


Author: Alan Hopkins and Linda Collins
Date: Wednesday, May 4th, 2005
Presented at: PharmaSUG 2005

We present a general table model for display of statistical results from a typical clinical trial and describe an application to generate table descriptions in XML. This XML file is then used as input to a SAS code generating application which creates a SAS driver program built with validated macros. The table descriptions and associated software may be saved as standards for future studies. Using an XML-structured approach to defining tables and validated software for producing the tables will result in much quicker validation and higher quality of statistical tables produced for clinical study reports.