Statistical Planning of Translational Research

• Applicants: Professor Dr. Tim Friede; Professor Dr. Frank Konietschke
• Subject Area: Epidemiology and Medical Biometry/Statistics
• Term: since 2021
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 455924146

In the first funding period of the project we developed efficient new statistical methods for the planning and analysis of preclinical studies, particularly suited for small sample sizes. The current project aims to further develop these methods and extend them into the clinical domain to bridge the gap between preclinical and clinical research. In the second phase of our project, we will focus on developing and applying Bayesian models for integrating preclinical data into clinical trials, group sequential methods, and techniques for sample size recalculation. Additionally, we will work on specific statistical approximations for small sample sizes and develop user-friendly software solutions to facilitate the practical implementation of these methods. A central aspect of our project is considering ethical issues in translational research. Particularly in preclinical research, it is crucial to design statistical planning and analysis as accurately as possible to avoid unnecessary animal testing and maximize the reproducibility of results. Our new statistical methods contribute to minimizing the number of animals required while enhancing the reliability of the studies. This supports scientific integrity and upholds ethical responsibility in biomedical research. Through these approaches, we aim to significantly improve the efficiency and robustness of translational research in both preclinical and clinical phases, thereby contributing to the optimization of medical research and the development of new therapies.

• DFG Programme: Research Grants