SafetyGraphics R Library – An Open-Source and Clinical Workflow for Assessing Hepatoxicity in Clinical Trials

Tables, figures and listings are an inefficient way to understand data relative to interactive data visual tools with automated analyses. The DIA-ASA Biopharm Safety Evaluation Working Group is developing a series of novel interactive safety graphic tools to enhance the ability to identify and evaluate safety signals. Each will be made available as an open-source, non-proprietary application. The first tool to be released is designed to explore cases of potential drug-induced hepatotoxicity based on the eDISH plot developed by FDA. In this talk I will describe the workflow typically used to assess hepatoxicity and how this tool facilitates the workflow. Building upon the existing static eDISH plot, the tool allows the user to dynamically adjust laboratory thresholds, modify the time dimension for the occurrence of peak ALT/AST and bilirubin values, account for the extent of alkaline phosphatase elevation, with filters for treatment, gender, race and age. Cases that appear in the potential Hy’s Law, Temple’s corollary and hyperbilirubinemia quadrants can be individually explored in further detail. The tool is accompanied by a proposed workflow to guide the analytical steps supported by references to the medical literature. This will allow scientists to more easily identify safety signals and perform exploratory analyses.

About the speaker
Zachary Skrivanek

Dr. Skrivanek graduated with a Ph.D. in biostatistics from Ohio State University and a B.S. in Industrial and Labor Relations from Cornell University. Dr. Skrivanek’s research interests started in genetic linkage analysis. He has published several papers and presented at Joint Statistical Meetings in this area. He developed a software package, Sequential Imputation for Multi Point Linkage Estimation (SIMPLE), to implement the methods that he developed. He joined Eli Lilly in 2002 where he contributed to the development of Endocrine drugs and related biomarkers in early clinical phase drug development. He later transitioned to a product team in late phase clinical development as the lead statistician and developed a novel Bayesian adaptive, seamless phase 2/3 study which selected the doses algorithmically for the entire Phase 3 program for the compound while the study was ongoing and double-blinded. Dr. Skrivanek heavily leveraged Visual Analytics in his compound work and is currently leading an effort to make Visual Analytics an integral part of drug development at Eli Lilly.

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