Nov 17, 2017 Meeting

Phil Hall, Edward Lifesciences

SDTMs in Medical Devices – A First Attempt

Abstract:

While clinical trial data of pharmaceutical and medical devices have a lot in common, the differences can be difficult to deal with in SDTMs.

This presentation acknowledges the similarities, highlights the differences and serves as a case-study of how the Transcatheter Heart Valve (THV) Statistical Programming group of Edwards Lifesciences has decided to map their raw data into Study Data Tabulation Model (SDTM) domains. This is not intended to be the definitive guide of how to map medical device trial data to SDTM standards but to serve as the opening statement of a conversation.

About the speaker:

Phil Hall is a Distinguished Statistical Programmer at Edwards Lifesciences, a global leader in patient-focused medical innovations for structural heart disease, as well as critical care and surgical monitoring, head-quartered in Irvine, California.

He has a Bachelor’s Degree in Applied Statistics and a Master’s Degree in Biometry, both from the University of Reading, UK. Before joining Edwards in 2010, Phil had spent his career working in Europe and the US at pharmaceutical companies and CROs as a statistician and statistical programmer.

Carey Smoak, DataCeutics

A Critique of Implementing the Submission Data Tabulation Model (SDTM) for Drugs and Medical Devices

Abstract:

Most SAS programmers in Pharma / Biotech are familiar with the SDTM model. But there are areas of SDTM that are not being fully utilized. These areas include Therapeutic Area User Guides (TAUGs), Associated Persons Implementation Guide (SDTMIG-AP) and SDTM for Medical Devices (SDMTIG-MD).

This presentation will explain the benefit of fully implementing all of the SDTM standards for Drugs and Medical Devices.

About the speaker:

Carey has been using SAS for 35 years. He is the co-founder and co-leader of the CDISC Medical Device team. He currently works for DataCeutics as a Senior Consultant. He is a frequent speaker at conferences and has more than 40 publications to his credit.

Helen Shi, Santen Inc.

Which Paint Brush Shall I Choose?

Abstract:

As programming professionals, we probably all heard of the design principle of KISS. Yet, few of us can articulate what it stands for.

I will mainly talk about the visualization needs involving multiple functions including medical affairs, pharmacovigilance, regulatory, publishing, data management and clinical operations during clinical trial. By breaking down their needs by analysis level, timeliness and display format, we will map SAS and other software tools according to these needs from our setting and how as programmers we can manage the painter box for these requests.

About the speaker:

Helen Shi has been in clinical data programming for 5 years at Santen Inc. Being a Subject Matter Expert for SAS Life Science Analysis Framework and visualization, Helen is passionate about supporting good decision making along pipeline and moving innovations from bench to market in various countries.

Helen has also got the Stanford Advanced Project Management certificate in 2015. She serves on the board of a youth entrepreneurship organization. She enjoys playing the violin and board games in her pastime.

Yi-ting Lin, Gilead Sciences

Practical tips when using ODS and SG procedures to generate clinical trial graphs

Abstract:

Graphic reporting is important for clinical trial not only graphs are part of CSR TFLs but also in exploratory analysis toward publication or research purpose. SAS ODS and SG (Statistical Graphics) procedures are developed to easily facilitate the needs for different types of graphs.

But several hours can be spent to find the solution for some fundamental graph area issues such as modifying the size or location of graph area vs plot area, or where to turn off/on graph border or plot border. Since there are so many details about SAS graph programming, it is good to know some practical tips that can save your day when using ODS and SG procedures for clinical trial graphs.

About the speaker:

Yi-ting Lin has been working in biotech/pharmaceutical industry for over 13 years as a statistical analyst and statistical programmer. She is with Gilead Science for 6 years and currently works as a Sr. Manager of Statistical Programming in Liver Disease Therapeutic Area. She supported multiple HCV NDA for FDA submission and now leads a team to support multiple liver fibrosis projects.