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António Miguel Pesqueira, Sousa, M., Pere Mercadé Melé, Rocha, Álvaro, Miguel Sousa & Lopes da Costa, R. (2021). Data Science Projects in Pharmaceutical Industry. Journal of Information Science and Engineering. 37 (5), 1135-1152

A. M. Pesqueira et al.,  "Data Science Projects in Pharmaceutical Industry", in Journal of Information Science and Engineering, vol. 37, no. 5, pp. 1135-1152, 2021

@article{pesqueira2021_1732396356156,
	author = "António Miguel Pesqueira and Sousa, M. and Pere Mercadé Melé and Rocha, Álvaro and Miguel Sousa and Lopes da Costa, R.",
	title = "Data Science Projects in Pharmaceutical Industry",
	journal = "Journal of Information Science and Engineering",
	year = "2021",
	volume = "37",
	number = "5",
	doi = "10.6688/JISE.202109_37(5).0010",
	pages = "1135-1152"
}

TY  - JOUR
TI  - Data Science Projects in Pharmaceutical Industry
T2  - Journal of Information Science and Engineering
VL  - 37
IS  - 5
AU  - António Miguel Pesqueira
AU  - Sousa, M.
AU  - Pere Mercadé Melé
AU  - Rocha, Álvaro
AU  - Miguel Sousa
AU  - Lopes da Costa, R.
PY  - 2021
SP  - 1135-1152
SN  - 1016-2364
DO  - 10.6688/JISE.202109_37(5).0010
AB  - The purpose of this paper is to discuss the relevance of data science in Medical Affairs
(MA) functions in the pharmaceutical industry, where data is becoming more important
for the execution of activities and strategic planning in the health industry. This study analyses pharmaceutical companies who have a data science strategy and the variables that can
influence the definition of a data science strategy in pharma companies in opposite to other
pharmaceutical companies without a data science strategy. The current paper is empirical
and the research approach consists of verifying the characteristics and differences between
those two types of pharmaceutical companies. A questionnaire specifically for this research was developed and applied to a sample of 280 pharma companies. The development
and analysis of the questionnaire was based on a Systematic Literature Review of studies
published up to (and including) 2017 through a database search and backward and forward
snowballing. In total, we evaluated 2247 papers, of which 11 included specific data science
methodologies criteria used in medical affairs departments. It was also made a quantitative
analysis based on data from a questionnaire applied to a Pharma organization. The findings
indicate that there is good evidence in the empirical relation between Data Science and the
strategies of the organization. 
ER  -