TITLEPRESENTER ABSTRACT SECTION
Compartment Models in PROC NLMIXEDFang Chen, Director of Advanced Statistical Methods at SAS. Raghavendra Kurada, Senior Research Statistician Developer at SAS. PK models are nonlinear models that are widely used in the biopharmaceutical industry to predict pharmacokinetic changes in a body system. In SAS/STAT® 14.3, the NLMIXED procedure provides enhanced PK modeling capability through the new CMPTMODEL statement, which enables you to fit a large class of PK models, including one-, two-, and three-compartment models for intravascular (bolus and infusion) and extravascular (oral) types of drug administration. This talk introduces the CMPTMODEL statement, provides examples, and discusses prediction, visualization, and data input. Statistics & Pharmacokinetics
The diagnosis and handling of Missing data in clinical trialsYing Yao, statistical programmer from BIIn this paper, we would like to display the pattern of missing data that frequently happen in clinical trials and clarify the reasons why they happen, and discuss several ways of prevention for the missing data cases. Then we will review the theory of missing data and methodology regarding how to identify and then how to handle the missing data with examples in SAS. In the last section, we will go through the technics and the pre-requisites for applying and modeling to make sure the methods are used properly.Statistics & Pharmacokinetics
ADaM Structures for Integration: A PreviewWayne Zhong, member of the ADaM Integration, ADaM compliance sub-teams.The existing ADaM classes (ADSL, BDS, and OCCDS) already support some simple cases of integration analysis. However, there has been a need for an integration standard that supports the more complex cases. To address this need, the ADaM Integration sub-team is developing the upcoming ADaM Integration standards document. This paper introduces the new IADSL, IBDS, and IOCCDS classes found in this document. This paper also discusses the analysis needs that necessitated the creation of the new classes, and provides examples in the form of usage scenarios, data, and metadata. Data Standards/CDISC and Regulatory Submission
Advanced Figures using SAS Graph Template Language (GTL) Wei (Tony) Zhang, Asso. Dir. Programming Lead in PfizerThis paper demonstrates how SAS Graph Template Language can be effectively and easily used to create plots like swimmer plot, waterfall plot, spider plot, forest plots, survival plot, and other graphs using Graph Template Language and the ODS Graphics procedure; new functions in SAS 9.4 GTL; ODS template modification, and other tips to use in GTL for complex figures.Data Visualization and Graphics
Create the TA,TE models that conform to SDTM criteria by the web platformJianfeng YeThis paper proposes a new solution which define the rules in the network platform, which will easily build a standardized data model through the browser. This method not only facilitates the trial designer to better understand the study design, but also enhances the quality of data delivery to some extent.Application Development & Technical Techniques
Data De-identification Automation in SASHuan Lu, Statistical Programmer at Sanofi Aventis.Data in clinical trials submitted to Food and Drug Administration (FDA), European Medicines Agency (EMA) or national competent authorities of EU Member States shall be shared in order to fulfill the commitment by considering how de-identification and anonymization techniques can be applied to individual patient data (IPD). Given appropriate de-identification specification and plan, automation in data de-identification process becomes very much needed, DEID as data de-identification automation SAS macro package was created under such a background, which would be an ideal tool to de-identify data automatically.Application Development & Technical Techniques