From Inception to ConcePTION: Genesis of a Network to Support Better Monitoring and Communication of Medication Safety During Pregnancy and Breastfeeding

Publication authors: Thurin, N. H. Pajouheshnia, R. Roberto, G. Dodd, C. Hyeraci, G. Bartolini, C. Paoletti, O. Nordeng, H. Wallach-Kildemoes, H. Ehrenstein, V. Dudukina, E. MacDonald, T. De Paoli, G. Loane, M. Damase-Michel, C. Beau, A. B. Droz-Perroteau, C. Lassalle, R. Bergman, J. Swart, K. Schink, T. Cavero-Carbonell, C. Barrachina-Bonet, L. Gomez-Lumbreras, A. Giner-Soriano, M. Aragon, M. Neville, A. J. Puccini, A. Pierini, A. Ientile, V. Trifiro, G. Rissmann, A. Leinonen, M. K. Martikainen, V. Jordan, S. Thayer, D. Scanlon, I. Georgiou, M. E. Cunnington, M. Swertz, M. Sturkenboom, M. Gini, R.

In 2019, the Innovative Medicines Initiative (IMI) funded the ConcePTION project-Building an ecosystem for better monitoring and communicating safety of medicines use in pregnancy and breastfeeding: validated and regulatory endorsed workflows for fast, optimised evidence generation-with the vision that there is a societal obligation to rapidly reduce uncertainty about the safety of medication use in pregnancy and breastfeeding. The present paper introduces the set of concepts used to describe the European data sources involved in the ConcePTION project and illustrates the ConcePTION Common Data Model (CDM), which serves as the keystone of the federated ConcePTION network. Based on data availability and content analysis of 21 European data sources, the ConcePTION CDM has been structured with six tables designed to capture data from routine healthcare, three tables for data from public health surveillance activities, three curated tables for derived data on population (e.g., observation time and mother-child linkage), plus four metadata tables. By its first anniversary, the ConcePTION CDM has enabled 13 data sources to run common scripts to contribute to major European projects, demonstrating its capacity to facilitate effective and transparent deployment of distributed analytics, and its potential to address questions about utilization, effectiveness, and safety of medicines in special populations, including during pregnancy and breastfeeding, and, more broadly, in the general population.

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