PSI ToxSIG Webinar: Beyond the looking glass - Interpreting animal welfare & behaviour by monitoring & assessing mice activity data
Analysing continuously collected locomotive activity data to interpret mice welfare and behaviour.
Several quantitative methodologies have been proposed to support decision-making in drug development. In particular, MultiCriteria Decision Analysis (MCDA) is a useful tool to assess the benefit-risk balance of medicines according to the performances of the treatments on several criteria, accounting for the preferences of the decision-makers regarding the relative importance of these criteria. The EMA Benefit-Risk Methodology Project suggested that it is one of the most comprehensive among the quantitative methodologies they considered, and it is also recommended by several highly profiled expert groups. While MCDA requires the exact elicitation of the weights of the criteria according to the preferences of the decision-makers, extended versions of MCDA have been proposed, such as Stochastic Multicriteria Acceptability Analysis (SMAA) and Dirichlet SMAA, where the weights are considered as random variables to account for some uncertainty in the weight assignment.
This webinar proposes a very concrete illustration of MCDA and of the extended models SMAA and Dirichlet SMAA using case-studies. We will present how to derive a benefit-risk utility score for each treatment, how to compare several treatments, how to present the results and how to conduct sensitivity analyses. The differences between the models will be highlighted, and some R code will be presented and shared after the presentation.
Gaelle Saint-Hilary works in statistics for the pharmaceutical industry since 2006. She is currently completing a PhD on “Quantitative Decision-Making in Drug Development”, sponsored by Servier, at the Polytechnic University of Turin (Italy). Before that, she worked as biostatistician in the industry, first at Servier for 5 years and then at Novartis Oncology for 4 years. She was responsible for the clinical development and the licensing of medicinal products in neuropsychiatry and leukemia, and her main scientific interests were benefit-risk assessment, network meta-analyses, multiple test procedures, simulation models of time-to-event data and survival analysis in presence of intercurrent events. The development and the promotion of quantitative methods for drug benefit-risk assessments is one of the major topics she considers during her PhD, with the final goal of enhancing decision-making throughout the drug life-cycle.
Graduated in 2011, Stéphanie Cadour works as a biostatistician at Servier (France) since then. She was initially responsible for the statistical aspects of phase II and III clinical studies conducted in the therapeutic areas of neuropsychiatry and diabetes. She is now working on early phase studies in the field of oncology. In parallel of these activities, Stephanie developed skills on meta-analyses as well as on quantitative approaches for benefit-risk assessment on which she has been working on since 2011.