PSI Webinar(s): Causal inference in Clinical Trials
Over the course of two sessions, a panel of 8 esteemed speakers will give an introduction to the topic, followed by a presentation of case studies & interactive panel discussion.
Date: Tuesday 14th March 2023
Time: 14:00-14:45 GMT | 15:00-15:45 CET
Speaker: Els Pattyn (Sanofi)
Who is this event intended for? Any statisticians working in the Pharmaceutical industry.
What is the benefit of attending? Attendees will have the opportunity to see an example of JMP development for regulatory compliant calculation of immunogenicity cut-point.
Registration for this webinar is free to both Members of PSI and Non-Members.
Please click here to register.
"Immunogenicity represents a significant hurdle for the development of all biotherapeutics and biosimilars as it can affect both efficacy and safety of the treatment. Over the last decade industry and regulators succeeded in standardizing a tiered screening/confirmatory/titer testing approach for anti-drug antibodies (ADAs). Unlike assays to determine the concentration of biopharmaceuticals, ADA assays are semi-quantitative in nature, and therefore requiring error prone and complex statistical approaches for positivity cut-points at each tier of the testing paradigm.
To get around these hurdles, a solution has been created within Sanofi by the development of a fully-automated and validated script using the JMP statistical software. This script follows a pre-determined decision tree based on the latest recommendations from industry guidance, white papers and scientific best-practice. It is designed for both binding and neutralizing antibody methods used to support non-clinical and clinical studies in regulated environments (GLP/GcLP). The user-friendly interface allows application by any bioanalytical scientist without requiring deep statistical knowledge.
The script allows end-users to easily select the appropriate decision trees applicable for the specific needs of a given type of assay or study. The application accepts Excel files to upload assay response data and then makes outcome-dependent decisions based on best-practices for the chosen method and context. For example, the script will select the most appropriate normalization/transformation, apply adapted effects included in the mixed-effects model based on the study-design, optionally calculate analyst-specific cut-points in case of significant analyst-specific differences and adapt down-stream analysis in cases where no second-tier confirmatory data is available.
The validated version of this purpose-built statistical tool, named ImmunoStat Simple, allows immunogenicity cut-points to be calculated quickly and efficiently in a standardized way across multiple sites in a global organization, and the automated reporting is suitable for regulatory submissions. The successful implementation of this automated JMP script demonstrates how digital tools and automation can improve the efficiency and capabilities of modern bioanalytical laboratories."
Els Pattyn is educated as a bio-engineer. After obtaining her PhD, she additional worked 8 years as a post-doctoral researcher at the University of Ghent in the immunology research, whereafter she took the role of scientist NANOBODY® characterization at Ablynx. After obtaining a master in statistical data analysis, she switched to Ablynx’ statistics team. By the acquisition of Ablynx by Sanofi in 2018, Els joined Sanofi’s Non Clinical Efficacy and Safety Statistics team, where she provides statistical support for mainly projects in immunology research, with focus on dose response modelling, design of experiments and immunogenicity assessment.