Objective
Recent pharmacovigilance (PV) issues have led to questions regarding the ability of the current PV system to meet the global needs. Controversies around the assessment of spontaneous reports and conflicting results from pharmacoepidemiology studies may lead to delay in, or inappropriate, regulatory decisions. The PROTECT consortium, consisting of 20 core partners lead by the European Medicines Agency (EMEA), will
develop and test methods of proactive monitoring of drug safety and benefit risk (B/R) assessment utilising a large range of EU data sources and expertise. in partnership with EFP1A companies, PROTECT will develop essential parameters, methodologies and algorithms to enable data mining, signal detection and evaluation in various types of
data-sets including spontaneous reporting, registries and electronic health care databases (EHR). impact analysis
methods will be used to enhance signal prioritisation.
PROTECT will develop means of combining results from clinical trials, spontaneous reporting and observational data, strengthening continuous B/R monitoring in the post-authorisation phase. Bayesian modelling, multi-criteria decision analysis and other analytical methods will be compared. Methods for graphical expression of B/R will be
tested with different stakeholders.
Collection of data directly from patients is underutilized and may be essential when knowledge of total drug consumption or potential confounders is needed or conventional PV is disrupted. PROTECT will trial direct patient data collection in natural language using web-based, telephone and text messaging systems. As well as testing
transferability of the data into a common language, PROTECT will explore linkage to data from EHR and electronic registries.
Fields of science
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- medical and health sciencesbasic medicinepharmacology and pharmacydrug safety
- medical and health scienceshealth scienceshealth care serviceseHealth
- natural sciencescomputer and information sciencesdatabases
- natural sciencescomputer and information sciencesdata sciencedata mining
- engineering and technologyenvironmental engineeringenergy and fuelsrenewable energysolar energyphotovoltaic
Call for proposal
IMI-JU-01-2008
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Coordinator
1083 HS Amsterdam
Netherlands
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Participants (34)
2300 Copenhagen S
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WC1A 1DG LONDON
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SE1 7QY London
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1162 St. Prex
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80539 MUNCHEN
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28022 Madrid
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08035 Barcelona
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28004 Madrid
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75654 Paris
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75015 Paris
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20156 Milano
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9712CP Groningen
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3584 CS Utrecht
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S-75140 Uppsala
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LS2 7UE Leeds
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SW7 2AZ LONDON
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NE1 7RU Newcastle Upon Tyne
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94250 GENTILLY
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CT13 9NJ Sandwich
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4070 Basel
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4056 Basel
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1831 Diegem
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1411 DD Naarden
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64293 Darmstadt
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13353 Berlin
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151 85 Sodertaelje
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2500 Valby
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2880 Bagsvaerd
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61-701 Poznan
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WC2B 4AE London
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8000 Aarhus C
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RG21 4FA Basingstoke
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58455 Witten
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9713 GZ Groningen
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