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Using PharmaPy with Jupyter Notebook to teach digital design in pharmaceutical manufacturing.
Laky, Daniel J; Casas-Orozco, Daniel; Abdi, Mesfin; Feng, Xin; Wood, Erin; Reklaitis, Gintaras V; Nagy, Zoltan K.
Afiliación
  • Laky DJ; Davidson School of Chemical Engineering, Purdue University, West Lafayette, Indiana, USA.
  • Casas-Orozco D; Department of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA.
  • Abdi M; Davidson School of Chemical Engineering, Purdue University, West Lafayette, Indiana, USA.
  • Feng X; Office of Pharmaceutical Quality, Center for Drug Evaluation and Research, Food & Drug Administration, Silver Spring, Maryland, USA.
  • Wood E; Office of Pharmaceutical Quality, Center for Drug Evaluation and Research, Food & Drug Administration, Silver Spring, Maryland, USA.
  • Reklaitis GV; Office of Pharmaceutical Quality, Center for Drug Evaluation and Research, Food & Drug Administration, Silver Spring, Maryland, USA.
  • Nagy ZK; Davidson School of Chemical Engineering, Purdue University, West Lafayette, Indiana, USA.
Comput Appl Eng Educ ; 31(6): 1662-1677, 2023 Nov.
Article en En | MEDLINE | ID: mdl-38314247
ABSTRACT
The use of digital tools in pharmaceutical manufacturing has gained traction over the past two decades. Whether supporting regulatory filings or attempting to modernize manufacturing processes to adopt new and quickly evolving Industry 4.0 standards, engineers entering the workforce must exhibit proficiency in modeling, simulation, optimization, data processing, and other digital analysis techniques. In this work, a course that addresses digital tools in pharmaceutical manufacturing for chemical engineers was adjusted to utilize a new tool, PharmaPy, instead of traditional chemical engineering simulation tools. Jupyter Notebook was utilized as an instructional and interactive environment to teach students to use PharmaPy, a new, open-source pharmaceutical manufacturing process simulator. Students were then surveyed to see if PharmaPy was able to meet the learning objectives of the course. During the semester, PharmaPy's model library was used to simulate both individual unit operations as well as multiunit pharmaceutical processes. Through the initial survey results, students indicated that (i) through Jupyter Notebook, learning Python and PharmaPy was approachable from varied coding experience backgrounds and (ii) PharmaPy strengthened their understanding of pharmaceutical manufacturing through active pharmaceutical ingredient process design and development.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Comput Appl Eng Educ Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Comput Appl Eng Educ Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos