Plant, A.
(2022),
Implementing Systems Thinking and Data Science in the Training of the Regenerative Medicine Workforce, npj Regenerative Medicine, [online], https://doi.org/10.1038/s41536-022-00271-2, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=935272
(Accessed April 28, 2024)
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Implementing Systems Thinking and Data Science in the Training of the Regenerative Medicine Workforce
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Abstract
Regenerative Medicine and Advanced Therapies (RMAT) are complex products and often include "living" cellular materials. Every patient—and for some applications, every product—is unique, and product manufacturing entails lengthy, complicated processes. Intricate relationships exist between the patient's disease state, the donor starting material, the manufacturing process, supply chain logistics, and the clinical response. Each clinical application provides a unique context with distinct requirements for the therapy. RMAT products are stimulating a paradigm shift in biopharma manufacturing by requiring an understanding of interrelated systems at multiple scales—from molecular and cellular processes to optimization of the manufacturing process, supply chain logistics, and patient queuing. The next generation workforce must be prepared with modern data tools and methodologies along with a systems-thinking mindset.Citation
npj Regenerative Medicine
Pub Type
Journals
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Keywords
regenerative medicine, workforce, computational, interdisciplinary
Citation
Created July 27, 2022, Updated December 12, 2023