Date: Tuesday 4th June 2024
Time: 15:00-16:00 BST | 16:00-17:00 CEST
Location: Online via Zoom
Speaker: Lea Vaas
Who is this event intended for? Statisticians and other scientists working in in-vivo studies within Pharmaceutical Industry
What is the benefit of attending? Learning about Virtual Control Groups in animal studies and its application in toxicity Studies.
This event is free to attend for both Members of PSI and Non-Members. To register your place, please click here.
Lea Vaas will present how replacement of concurrent control animals by Virtual Control Groups (VCGs) in systemic toxicity studies may help in contributing to the 3R's principle of animal experimentation: Reduce, Refine, Replace. This will be followed by Q&A.
|
Speaker |
Biography |
Abstract |
|
|
L. Vaas studied Plant biotechnology and got roped into statistics and data-analysis during her M.Sc. on multiple comparisons in augmented experimental designs. Finishing a PhD as co-developer of an R-package for analysis of high-dimensional longitudinal data set the course for pursuing a career in the field of statistics. After different Postdoc experiences in academic research institutions such as Helmholtz and Fraunhofer, L. Vaas joined Bayer in 2017 in the group of Research and Pre-Clinical Statistics. |
In systemic toxicity studies replacement of concurrent control animals by so-called Virtual Control Groups (VCGs) may reduce the use of animals thus contributing to the 3R's principle of animal experimentation: Reduce, Refine, Replace. Although VCGs are an established concept in clinical trials, the idea of replacing living beings with virtual data from historical data sets has so far not been introduced into the design of regulatory animal studies1. However, major steps facilitating review of methodology for derivation of ViCoGs from historical control data and performance testing in statistical analysis, are the collection, curation and sharing of suitable sets of historical control data from preclinical toxicity studies. This talk will summarize accomplished and ongoing efforts for cross-industry provision of data resources, standardization and curation activities and line out both general ideas and specific methodology for derivation of ViCoGs. A discussion of advantages and pitfalls along this journey will include real-world examples, case studies2 and potential solutions. Further, ideas for transferring these insights into regulations and guidelines, especially possibilities for reaching out for regulatory advice to gain acceptance of this concept as early as possible1 will be discussed. [1] Steger-Hartmann, T., Kreuchwig, A., Vaas, L., Wichard, J., Bringezu, F., Amberg, A., Muster, W., Pognan, F. and Barber, C. (2020) Introducing the concept of virtual control groups into preclinical toxicology testing, ALTEX - Alternatives to animal experimentation, 37(3), pp. 343–349. doi: 10.14573/altex.2001311. [2] Gurjanov, A., Steger-Hartmann, T., Kreuchwig, A., and Vaas, L.A.I.(2023) Hurdles and Signposts on the Road to Virtual Control Groups -A Case study illustrating the Influence of Anesthesia Protocols on Electrolyte Levels in Rats, Front. Pharmacol. Sec. Predictive Toxicology 2023 Vol 14. doi: 10.3389/fphar.2023.1142534 |
