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Smart Vaccine Manufacturing Using Novel Biotechnology Platforms: A Study During COVID-19
Journal of Computing and Information Science in Engineering ; 22(4):10, 2022.
Article in English | Web of Science | ID: covidwho-1927633
ABSTRACT
Healthcare experts have come to a consensus that effective and safe vaccines are necessary to control the rapid spread of the ongoing COVID-19 pandemic across the globe. Since the traditional vaccine development and manufacturing approaches were unable to meet the rapidly growing COVID-19 vaccine demand, biopharmaceutical firms had to devise novel and smart techniques to boost the development, production, and distribution of COVID-19 vaccines in a large scale with lightning speed. This triggered their transition to smart vaccine manufacturing approaches using novel viral vector and nucleic acid biotechnology platforms. This paper tries to explore this rationality of the biopharmaceutical industry by comparing the traditional and the novel biotechnology platform-based vaccine manufacturing techniques and reviewing the COVID-19 vaccine manufacturing scenarios. To highlight the "smart" characteristics of the novel platform-based COVID-19 vaccine products and to make an effective comparison with the traditional products, a well-established product classification framework is used as a reference. Finally, the study concludes by presenting the future possibility of incorporating smart manufacturing paradigms with the novel platform-based manufacturing process. It is hoped that this study would serve as an asset for the biopharmaceutical firms to appropriately streamline their strategies, resources, and goals to meet the global vaccine requirements.
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Full text: Available Collection: Databases of international organizations Database: Web of Science Topics: Vaccines Language: English Journal: Journal of Computing and Information Science in Engineering Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Web of Science Topics: Vaccines Language: English Journal: Journal of Computing and Information Science in Engineering Year: 2022 Document Type: Article