Scientific competency questions as the basis for semantically enriched open pharmacological space development

Author(s)
Kamal Azzaoui, Edgar Jacoby, Stefan Senger, Emiliano Cuadrado Rodríguez, Mabel Loza, Barbara Zdrazil, Marta Pinto, Antony J Williams, Victor de la Torre, Jordi Mestres, Manuel Pastor, Olivier Taboureau, Matthias Rarey, Christine Chichester, Steve Pettifer, Niklas Blomberg, Lee Harland, Bryn Williams-Jones, Gerhard F Ecker
Abstract

Molecular information systems play an important part in modern data-driven drug discovery. They do not only support decision making but also enable new discoveries via association and inference. In this review, we outline the scientific requirements identified by the Innovative Medicines Initiative (IMI) Open PHACTS consortium for the design of an open pharmacological space (OPS) information system. The focus of this work is the integration of compound-target-pathway-disease/phenotype data for public and industrial drug discovery research. Typical scientific competency questions provided by the consortium members will be analyzed based on the underlying data concepts and associations needed to answer the questions. Publicly available data sources used to target these questions as well as the need for and potential of semantic web-based technology will be presented.

Organisation(s)
External organisation(s)
Novartis Pharma AG, Janssen, GlaxoSmithKline, Universidade de Santiago de Compostela (USC), Royal Society of Chemistry, Centro Nacional de Investigaciones oncologicas (CNIO), Technical University of Denmark (DTU), Universität Hamburg, Swiss Institute of Bioinformatics, University of Manchester, AstraZeneca, Connected Discovery Ltd, University Pompeu Fabra
Journal
Drug Discovery Today
Volume
18
Pages
843-52
No. of pages
10
ISSN
1359-6446
DOI
https://doi.org/10.1016/j.drudis.2013.05.008
Publication date
09-2013
Peer reviewed
Yes
Austrian Fields of Science 2012
301208 Pharmaceutical technology
Portal url
https://ucrisportal.univie.ac.at/en/publications/366d7c64-0d84-4928-8106-74c9b098a04c