Karolina Kopanska
Postdoctoral Researcher, Center for Alternatives to Animal Testing (CAAT) John Hopkins University
Dr. Karolina Kopańska is a computational toxicologist specializing in chemical and pharmaceutical safety assessment, predictive modelling, and the advancement of non-animal approaches in regulatory science. She completed her PhD in Computational Toxicology at Universitat Pompeu Fabra, where her research focused on developing methods for uncertainty analysis and probabilistic reasoning within modern toxicological testing frameworks.
Currently a postdoctoral researcher at the Johns Hopkins Bloomberg School of Public Health, Center for Alternatives to Animal Testing (CAAT), and a member of its non-profit spin-off, CAATevents. Actively involved in several international research collaborations and public-private partnerships, and serves on advisory boards of toxicology-focused initiatives.
Seminars
- Overview of VICT3R and Virtual Control Groups (VCGs): rationale in the context of current global regulatory changes, and how using statistical methods and AI on historical control data can reduce animal use by up to 25%, supporting ethical innovation in toxicology
- Qualification strategy to demonstrate scientific validity, robustness, and reproducibility of studies including VCGs – examples from reanalysed legacy studies and ongoing prospective studies with industry partners and CROs
- Regulatory engagement and leveraging global partnerships to translate VCG qualification results into scientific opinions and internationally harmonised guidance documents – overview of our interactions with EMA, FDA, and OECD, and the role of the Scientific and Regulatory Advisory Board
- How pharma teams are collaborating within IQ MPS Affiliate to progress simple and complex in vitro NAM platforms toward regulatory acceptance
- Review insights from recent FDA publication on submitted NAM case examples and reviewer feedback – what works and what can be improved (need for well-articulated context-of-use)
- Discuss the value of a strong regulatory strategy: Suggestions for the qualification of alternative approaches leveraging toxicology data, statistical modelling, and AI – based on VICT3R experience
- Gain practical guidance for integrating in vitro and in silico NAMs into toxicology packages without over-claiming translatability
- What industry needs from consortia, regulators, and data-sharing frameworks to accelerate adoption of novel platforms covering diverse mechanisms of injury
