In order to shorten the time for regulatory review of a new drug application (NDA) or biologic license application(BLA), more and more biotech and pharmaceutical companies prepare their Bioresearch Monitoring (BIMO) program packages as part of their initial submissions. In this paper, we walk the reader through a process of producing BIMO information, particularly the subject-level data line listings by clinical site (by-site listings) and the summary-level clinical site (CLINSITE) dataset. This paper concludes with methods of preparing electronic Common Technical Document (eCTD) documentation, such as data definition (define.xml) and reviewer’s guide, to support the CLINSITE dataset. In addition, we discuss challenges as we share our experience in planning, producing, and quality control (QC) for a successful BIMO package.

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.

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.

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.