PSI Pre-Clinical SIG Webinar: Adjusting Experimental & Statistical Approaches throughout Preclinical development pathways
Date: Tuesday 24th October 2023
Time: 14:00-15:00 BST | 15:00-16:00 CEST
Speaker: PD Dr. Ulf Tölch (Berlin Institute of Health)
Who is this event intended for? Statisticians in Pharmaceutical Industry.
What is the benefit of attending? Learning how to enhance efficient evidence generation of preclinical experiments.
Registration for this webinar is free to both Members of PSI and Non-Members.
Please click here to register.
PD Dr. Tölch will present a framework to foster efficient evidence generation in preclinical experiments and will illustrate the proposed approach using examples from various projects. This will be followed by Q&A.
The ultimate goal of preclinical research is to identify interventions that can be tested in clinical settings. Whereas safety and toxicity testing are highly regulated, efficacy testing is often variable consisting of several iterative experimental steps. Consequently, experimental design and statistical testing have to be adopted to the goals of each experiment. Additional factors like available resources, already collected evidence, and maturity of the project need to be considered as well. The ultimate goal is to efficiently identify effective interventions. Here, I present a framework to systematically adjust validity and reliability in preclinical experiments to foster efficient evidence generation. To illustrate this approach, I will present examples from our consultation project within the Berlin Institute of Health and on the national level for multicenter preclinical studies.
PD Dr. Ulf Tölch
Ulf Tölch obtained his PhD in biology at LMU Munich. His research includes cognitive neuroscience, quantitative methods and statistical modelling of decision making. He currently serves as a research group leader at BIH QUEST Center for Responsible Research at Charité Universitätsmedizin. His research team explores robust methodological approaches in preclinical settings to inform and improve research decisions.