Abstract
This research study paper aims to provide a clear understanding of how data science and advanced analytics are being presented and studied within the academic research world and with a practical application in the commercial pharmaceutical context. This study also had key objectives to proceed with the identification of interconnection and dependencies and understand any research gaps of how both concepts are being also integrated into the commercial pharmaceutical operations like sales and marketing.
The study consisted of a hybrid approach for a deep theoretical and practical understanding of a systematic quantitative literature review of research articles and publications presented in different platforms like PubMed, Elsevier, iMedPub, Sage Journals, and Google Scholar as well as a focus group study with a group of 25 pharmaceutical professionals. The findings present in this research paper indicate an increase in new data science and advanced analytics models, techniques, and systems applying new analytical and data management techniques to large quantities of data and new decision process problems.
This study is a contribution to the discovery and understanding of how different applications of data science and advanced analytics in the pharmaceutical space are being managed, underpinning theories and key factors employed to study the past, current, and future of data science and advanced analytics adoption, utilization, and success.
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Pesqueira, A. (2022). Data Science and Advanced Analytics in Commercial Pharmaceutical Functions: Opportunities, Applications, and Challenges. In: Guarda, T., Anwar, S., Leon, M., Mota Pinto, F.J. (eds) Information and Knowledge in Internet of Things. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-75123-4_1
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