PharmaSUG Single Day Event
CDISC Tools and Optimization
SAS Institute Headquarters, Cary, NC - Bldg. C (Map)
September 29, 2014, 8:00am - 5:00pm
The Single Day Event in Cary was a huge success! Thanks to everyone who presented and participated. Don't forget that all paid registrants will receive a $75 discount for our annual conference in Orlando next May!
|Title (click for abstract)||Presenter(s) (click for bio)||Presentation|
|What's New with CDISC? / Q & A||Wayne Kubick, CDISC||PPT(5.9MB)|
|Leverage the CDISC Data Model to Streamline Analytical Workflows||Kelci Miclaus, SAS Institute||PPTX(2.3MB)|
|Building (and Rebuilding) the CDISC Toolbox||Jeff Abolafia, Rho|
& Frank DiIorio, CodeCrafters
|XML in a SAS and Pharma World||Mike Molter, D-Wise||PPTX(1.3MB)|
|Dataset XML - A New CDISC Standard||Lex Jansen, SAS Institute||PDF(3.1MB)|
|How a Large CRO has Implemented and Benefitted from CDISC Standards||Amy Caison,
& Jhelum Naik, PPD
Download the schedule as a PDF (114K).
Presentation AbstractsWhat's new with CDISC?
Wayne Kubick, CDISC
Review of current major programs and activities. Question and answer session relevant to CDISC Standards and Plans.
Leverage the CDISC Data Model to Streamline Analytical Workflows
Kelci Miclaus, SAS Institute
CDISC standards are increasingly being adopted worldwide by CRO, pharmaceutical and regulatory agencies alike. Of course, this can be met with resistance when companies have systems already fine-tuned to their own standard; what is needed are tools that showcase the clear advantage to leveraging data standards. We will present how JMP Clinical Software from SAS uses extensive SAS programming and JMP analytic visualizations to provide analytical tools that will drastically increase efficiency to help optimize the clinical data review. The solution is fully built on the SDTM and/or ADaM data model to perform clinical safety analysis, study snapshot comparison, data and fraud detection, even Risk-Based Monitoring using the study database. Integrations with Clinical Data Integration (CDI) and SAS Drug Development (SDD) as well as a new architecture that tracks all CDISC variable requirements and usage in the SAS programs provided by the system will be highlighted.
Building (and Rebuilding) the CDISC Toolbox
Jeff Abolafia, Rho
Frank DiIorio, CodeCrafters
In recent years, CDISC data models have become either the de facto standard for FDA submissions. This has coincided with increasing recognition by pharma and CROs that these standards provide opportunities for improving project workflow and quality. Publishing a standard is one thing; organizational commitment to developing tools to utilize the standard is quite another. Rho, Inc. has been developing such tools for over a decade. This presentation provides an overview of our CDISC tool box, emphasizing how the tools have changed over time. We demonstrate the importance to tool developers of regarding “CDISC Standards” as living documents rather than static entities. Attendees will gain an appreciation of the  metadata and tools needed to effectively use the standards as well as  understanding some of the decision-making needed as standards are introduced and updated.
XML in a SAS and Pharma World
Mike Molter, D-Wise
The introduction of standards to the clinical data life cycle has brought about significant changes to the job of a SAS programmer. Traditionally, SAS programmers who built data sets and statistical output for regulatory submission purposes had little need for technical knowledge beyond SAS programming and maybe some Microsoft or Adobe basics. In today’s world, collected data can be made available in an XML format produced by EDC systems (i.e. ODM.xml). Submissions are expected to be accompanied by metadata expressed through an XML extension of ODM (i.e. Define.xml). There’s even talk of replacing the traditional version 5 transport files with another XML extension of ODM (i.e. SDS-XML) for submission of domain data. The increased use of XML for transferring data and metadata has its advantages, but also imposes new requirements of a programmer’s skill set. This paper serves as an introduction to some of these new skills. In it we’ll discuss general XML basics and examine how they are applied in our industry today. We’ll also look at tools that allow us to move data from a SAS data set to an XML format and vice versa. This paper is for industry SAS programmers at an intermediate level or above.
Dataset XML - A New CDISC Standard
Lex Jansen, SAS Institute
Dataset-XML is a new CDISC standard that is used to provide study data sets in an XML format. The purpose of Dataset-XML is to support the interchange of tabular clinical research data using CDISC ODM-based XML technologies. This presentation will introduce the standard and present SAS based tools to transform between SAS data sets and Dataset-XML documents. Also, a short update is presented on the ongoing FDA Dataset-XML pilot.
How a Large CRO has Implemented and Benefitted from CDISC Standards
Amy Caison, PPD
Jhelum Naik, PPD
Data standards facilitate efficiency and enhanced quality by structuring how studies are designed, as well as how data are collected, transformed, and analyzed. The pharmaceutical and biotech industry must navigate a landscape of strict regulations and ever-changing standards and, as knowledge workers in this industry, we must conform to these standards to ultimately satisfy the demands of our stakeholders, be they regulatory agencies and/or sponsors. Though not a part of national regulatory agencies, the standards developed by the Clinical Data Interchange Standards Consortium (CDISC) are recognized by the FDA and other regulatory bodies as the preferred standard. With full implementation of the Prescription Drug User Fee Act (PDUFA V) anticipated within the next few years, the FDA will have statutory authority to reject submissions that do not conform to these standards. As successful businesses, we must leverage these standards to our advantage, utilizing them to enable greater efficiencies and improving our financial performance. To achieve these goals, we must identify, adapt to, and implement applicable standards, effectively train our staff and provide them with quality tools to efficiently implement these standards, and maintain the currency of our application of standards, while harnessing our technical expertise to achieve superior quality results. This paper explores how a large CRO has responded to the permeation of CDISC standards in the industry, what benefits can be realized from the application of these standards to clinical trial work and the challenges which inevitably arise with the implementation of these standards. We will discuss how the implementation of standards has resulted in the opportunity to develop standard tools to facilitate routine tasks, as well as the significant training and governance tasks that results from managing the application of standards across sponsors and projects. Though challenging at times, significant benefits are possible including substantial process and operational efficiencies, improved quality, and smoother communication among stakeholders once everyone is fluent with the standards. Nonetheless, the multitude of overlapping standards (e.g., core CDISC standards, sponsor-specific interpretations of CDISC standards, internal CRO standards, CDISC therapeutic area standards, etc.) makes standards management and implementation challenging. In addition, the increasing complexity of the standards has necessitated a rethinking of traditional work processes and roles within traditional biostatistics and programming clinical trial work. Ultimately, any organization working in the clinical trial industry must find their own path through the continually evolving standards landscape given their unique history and circumstance. However, we argue that rather than treating the implementation of CDISC standards as a compulsory requirement, the greatest benefit is realized by leveraging CDISC standards to work for the benefit of both the CRO and its sponsors. This paper addresses how a large CRO has engaged in such a way with the standards and the benefits which have been realized as a result.
Presenter BiographiesJeff Abolafia
Jeff Abolafia is currently Chief Strategist of Data Standards at Rho. Previously Jeff was a member of the faculty in the Department of Biostatistics at the University of North Carolina. Jeff has been involved with public health research and data standards for over twenty five years and is a frequent contributor and presenter at PharmaSUG, PhUSE, SAS Global Forum, and CDISC conferences. Jeff co-founded the RTP CDISC User's Group and is a member of the CDISC ADaM and ADaM Metadata teams. His areas of interest include data standards, submissions, statistical computing, and bioinformatics.
Amy L. Caison
Amy L. Caison, Ed.D. is a programming team leader in PPD’s Wilmington office and has over 6 year of experience as lead programmer/lead quality validator on clinical trials in oncology, psoriasis, diabetes mellitus, epilepsy, and irritable bowel syndrome. Dr. Caison received her Doctor of Education in Higher Education Administration from North Carolina State University in 2002 and has more than 7 years of experience in clinical trials and over 17 years of SAS programming experience, with particular focus in SDTM and data standards.
A SAS programmer since 1975, Frank DiIorio is president of Codecrafters, Inc. and the author of "SAS Applications Programming: A Gentle Introduction" and "Quick Start to Data Analysis with SAS". A frequent presenter a local and regional SAS User Groups, he is past president of the Southeast SAS Users Group and co-chaired its 1994 and 1996 conferences. He is also active in several local SAS user groups and was a co-founder of the Research Triangle CDISC Users Group.
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. Currently he is one of the developers working on the SAS Clinical Standards Toolkit. Since 2008 Lex has been an active member of the CDISC XML Technologies Team and was one of the developers of the Define-XML 2.0 specification. He was also involved in developing the Dataset-XML 1.0.0 specification.
Wayne R. Kubick
Wayne R. Kubick is Chief Technology Officer for CDISC, building upon previous stints as a two-term board member, Technical Director, team leader and general commentator at large. In addition to his work with CDISC, he has spent the past two decades in a variety of technology-focused roles in clinical research and development spanning from BBN Software Products, to CIO of Parexel International, followed by a 12 year ride as a senior executive at Lincoln Technologies, which became part of Phase Forward, which became part of Oracle Health Sciences. Mr. Kubick holds a B.A. from the University of Illinois and an M.B.A. from Boston University.
Kelci Miclaus is Research and Development Manager for the JMP Life Sciences Division at SAS Institute and develops statistical features for JMP Genomics and JMP Clinical software. She joined SAS in 2006 and holds a PhD in Statistics from North Carolina State University. Her research and development areas include genetic association and relatedness, mixed models, pattern discovery, clinical trials safety analysis and CDISC data standards.
Mike Molter is a Life Sciences Consultant with d-Wise Technologies in Raleigh, North Carolina. Mike began working with SAS software in 1999 in the healthcare industry before moving to statistical programming in clinical trials in 2003. In his current role, Mike helps clients develop and implement technical and process solutions around clinical data standards such as CDISC SDTM and ADaM, using a variety of SAS tools. Mike volunteers with CDISC’s XML Technologies team as well as the Data Optimization FDA/PhUSE working groups. He has presented at various local, regional, and national SAS and CDISC user group conferences. Personal interests include reading, triathlon, and the Detroit Tigers.
Jhelum Naik, M.S. is a senior programmer analyst in PPD’s Wilmington office and has over 6 years of experience as a programming lead on clinical trials in various therapeutic areas. Ms. Naik has received her M.S. in Computational Biology from the New Jersey Institute of Technology, Newark, NJ and has 7 years of experience in clinical trials and 10 years of SAS programming experience, with particular focus in CDISC SDTM.