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

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 healthcare and pharmaceutical research. To address...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:American journal of pharmaceutical education 2024-12, p.101341
Hauptverfasser: Ronkowski, Cynthia, Deshpande, Dhrithi, Sharma, Nitesh, Vahed, Mohammad, Patel, Yesha M, Gukasyan, Hovhannes J., Wu, Maryann, Peng, Kerui, Church, Terry David, Kim, Rory E., Mirzaian, Edith, Padula, William Vincent, Tomaszewski, Daniel, Ng, Tien M.H., Wong-Beringer, Annie, Zaro, Jennica, Qato, Dima M, Davies, Daryl L, Papadopoulos, Vassilios, Mangul, Serghei
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung: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 healthcare and pharmaceutical research. To address this need, the University of Southern California Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences (USC Mann) 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 PharmD students by focusing on the practical applications of data science in clinical settings, while for PhD and MS 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.
ISSN:0002-9459
1553-6467
1553-6467
DOI:10.1016/j.ajpe.2024.101341