Cynthia Ronkowski, Dhrithi Deshpande, Nitesh Sharma, Mohammad Vahed, Yesha M Patel, Hovhannes J Gukasyan, Maryann Wu, Kerui Peng, Terry David Church, Rory E Kim, Edith Mirzaian, William Vincent Padula, Daniel Tomaszewski, Tien M H Ng, Annie Wong-Beringer, Jennica Zaro, Dima M Qato, Daryl L Davies, Vassilios Papadopoulos, Serghei Mangul
{"title":"Pioneering Computational Culture Within Pharmacy Schools by Empowering Students With Data Science and Bioinformatics Skills.","authors":"Cynthia Ronkowski, Dhrithi Deshpande, Nitesh Sharma, Mohammad Vahed, Yesha M Patel, Hovhannes J Gukasyan, Maryann Wu, Kerui Peng, Terry David Church, Rory E Kim, Edith Mirzaian, William Vincent Padula, Daniel Tomaszewski, Tien M H Ng, Annie Wong-Beringer, Jennica Zaro, Dima M Qato, Daryl L Davies, Vassilios Papadopoulos, Serghei Mangul","doi":"10.1016/j.ajpe.2024.101341","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":55530,"journal":{"name":"American Journal of Pharmaceutical Education","volume":" ","pages":"101341"},"PeriodicalIF":3.8000,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"American Journal of Pharmaceutical Education","FirstCategoryId":"95","ListUrlMain":"https://doi.org/10.1016/j.ajpe.2024.101341","RegionNum":4,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"EDUCATION, SCIENTIFIC DISCIPLINES","Score":null,"Total":0}
引用次数: 0
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 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.
期刊介绍:
The Journal accepts unsolicited manuscripts that have not been published and are not under consideration for publication elsewhere. The Journal only considers material related to pharmaceutical education for publication. Authors must prepare manuscripts to conform to the Journal style (Author Instructions). All manuscripts are subject to peer review and approval by the editor prior to acceptance for publication. Reviewers are assigned by the editor with the advice of the editorial board as needed. Manuscripts are submitted and processed online (Submit a Manuscript) using Editorial Manager, an online manuscript tracking system that facilitates communication between the editorial office, editor, associate editors, reviewers, and authors.
After a manuscript is accepted, it is scheduled for publication in an upcoming issue of the Journal. All manuscripts are formatted and copyedited, and returned to the author for review and approval of the changes. Approximately 2 weeks prior to publication, the author receives an electronic proof of the article for final review and approval. Authors are not assessed page charges for publication.