JISE


  [ 1 ] [ 2 ] [ 3 ] [ 4 ] [ 5 ] [ 6 ] [ 7 ] [ 8 ] [ 9 ] [ 10 ] [ 11 ] [ 12 ] [ 13 ] [ 14 ] [ 15 ] [ 16 ]


Journal of Information Science and Engineering, Vol. 37 No. 5, pp. 1135-1152


Data Science Projects in Pharmaceutical Industry


ANTÓNIO MIGUEL PESQUEIRA1, MARIA JOSÉ SOUSA2, PERE MERCADÉ MELÉ3,
ÁLVARO ROCHA4, MIGUEL SOUSA5 AND RENATO LOPES DA COSTA6
1Bavarian Nordic A/S
6301 Zug, Switzerland
E-mail: antonio.pesqueira@live.com

2,6ISCTE, Instituto Universitário de Lisboa
Lisboa, 1649-026 Portugal
E-mail: maria.jose.sousa@iscte-iul.pt; renatojlc@gmail.com

3Department of Statistics and Econometrics
University of Málaga, Spain
E-mail: pmercade@uma.es

4Department of Information Systems and Technologies
University of Coimbra
Coimbra, 3004-531 Portugal
E-mail: amrrocha@gmail.com

5Department of Information Systems and Technologies
University of Essex
Colchester CO4 3SQ, UK
E-mail: miguel.ac.sousa@gmail.com


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.


Keywords: data science, pharmaceutical, medical affairs, literature review, projects

  Retrieve PDF document (JISE_202105_10.pdf)