Pioneering Computational Culture Within Pharmacy Schools by Empowering Students With Data Science and Bioinformatics Skills

Abstract

As advancements in digital health lead to the generation of increasingly diverse and voluminous pharmaceutical data, it is increasingly critical that we teach trainee pharmaceutical scientists how to leverage this data to lead future innovations in health care and pharmaceutical research. To address this need, the University of Southern California Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences is incorporating data science and bioinformatics into the graduate and undergraduate curricula through introductory courses tailored for students without prior programming experience. These courses feature a teaching framework designed to make the fundamentals of data science and bioinformatics accessible to pharmacy students through step-by-step, Jupyter-based coding assignments with examples relevant to the pharmaceutical sciences. The framework supports Doctor of Pharmacy students by focusing on the practical applications of data science in clinical settings, while for Doctor of Philosophy and Master's students students, the emphasis is on research methodologies and advanced data analysis techniques. Here, we outline the design of this framework, highlighting the strategies we developed and the opportunities it provides to cultivate a computational culture within our institution and beyond.