Teaching

Classroom teaching

ICPE pre-conference course on transparency and reproducibility across the RWE lifecycle, (Berlin, Germany)

Transparency and reproducibility are major prerequisites for conducting meaningful real-world evidence (RWE) studies that are fit for decision-making. With HARPER and RECORD-PE, many advances have been made in the documentation and reporting of study protocols, study parameters, and results, but the principles for computational reproducibility of study results, version control and sharing of analytic code in RWE are not yet as established as in other quantitative disciplines like computational biology and health informatics, where there are potentially fewer barriers.

For more information and resources, see: https://janickweberpals.github.io/icpe-git-2024/

ICPE pre-conference course on missing data (Copenhagen, Denmark)

Landscape Analysis on Techniques to Deal with Missing Data in Longitudinal Healthcare Databases
Session: Advanced Pharmacoepidemiology Methods: Mitigating Missing Data Concerns with External or Internal Subset Validation Populations, August 2022

This course introduced participants to advanced methods available to mitigate concerns around missing data in Real World Evidence studies. These include the identification and incorporation of data from external validation groups, the use of subset internal calibration groups, and the use of multiple imputation methods when data are believed to be missing at random. Real-world examples will be used across the lecture sessions to illustrate and connect different concepts.

Introduction to Pharmacoepidemiology (Heidelberg, Germany)

Introduction to Pharnacoepidemiology, Epidemiology Module, Medical Biometry/Biostatistics MSc course Institute for Medical Biometry and Informatics (IMBI), Medical Faculty of Heidelberg, Rupert Carola University Heidelberg (Germany), 6-hr one day session, 2 yr cycle, 2019-2021

Between 2019 and 2021, I had the opportunity to teach the following lecture every other year at the Medical Faculty of Heidelberg, Rupert Carola University Heidelberg (Germany).

Teaching philosophy

I had my first academic teaching and mentoring experiences as a senior graduate student in the third year of my PhD. Since I was heavily involved in cancer prognostic studies, I instructed new research scholars and graduate students with the fundamentals of cancer epidemiology. Already at that point I figured out three teaching and mentoring principles that I always like to pass on to mentees and students.

Hands-on

I would describe myself as an autodidact as I have always enjoyed to figure out things on my own and apply them hands-on. Admittedly, an autodidact learning rate can be significantly slower than more systematic learning approaches as hierarchical principles may not be pre-structured. Nevertheless, it taught me that concepts can be learned more deeply and sustainably by discovering them handson. For example, I regularly give introductory lectures in Pharmacoepidemiology 101 for master’s students in medical biometry/biostatistics who are strongly trained in the analysis of randomized trials but were mostly not aware of biases inherited in non-randomized data. The way I approached the abstract world of biases in pharmacoepidemiology was to present studies in which one of the biases led to a wrong conclusion of the study. Instead of pre-instructing them on these biases, they had to figure out potential problems there may have been with the study design or analysis in a team-based way. It was thrilling to see how much both the students and I learned from each other and how quickly they adopted and applied the learned concepts in a following exercise lecture. This is why I think a hands-on approach leads to a more sustainable learning success.

Passion

When instructing and supervising students, one of my major aims is to create passion for the subject of matter. When interviewing candidates for new positions, one thing that I always ask is which topic they would like to do research on if they had a choice. I made the experience that not many applicants have an answer to that, who otherwise demonstrated an excellent skillset for the positions they applied for. I see it as my mission to guide students and lead them to their field of interest that they feel most passionate for. This creates a situation where students are most excited and productive about their work and research. It also helps them to set a basis for their future professional life. For example, when I discuss with graduate students about their next strategical step in their projects, instead of providing them my opinion, I first ask them to tell me what they think would be the best next step. This provides them the neccessary maturity and responsibility to confidently conduct their own research and establish their profiles in the scientific world.

Curiosity

Finally, I always encourage students to be curious and try to expand their knowledge and understanding beyond their own scientific branch. It is critical to advocate from early on that science is international and interdisciplinary. Particularly in the field of health sciences, the joint work of many professions is necessary to make a difference for the patient. The pharmaceutical profession comes in many nuances from being a hospital pharmacist who sees patients and consults physicians to the pharmacist in basic research who analyzes genomic data to develop new and innovative drugs. Especially for undergraduate students it is very important to make them aware of the possibilities there are. I realized this on my own as I would not have discovered the field of pharmacoepidemiology without being curious and expanding my horizon. This also why I chose to do a postdoctoral fellowship in a data scientific environment mainly working with computer scientists and bioinformaticians on machine learning problems. I have often realized that we speak two different languages for the exact same thing and that it is possible to learn a lot from each other. Another aspect of being curious is the critical appraisal of findings that one may take for granted. I started my PhD asking the question if β-blockers may be used as chemopreventive drug leading to a better prognosis for cancer patients. By systematically summarizing and meta-analyzing pertinent studies, it turned out that a common methodological pitfall in the design of epidemiological studies (immortal time bias) was the major driver among those studies to arrive at this conclusion. This is a striking example for my motivation to teach and instruct students to always make informed decisions based on the best current evidence.