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EU-ADR

financed

Exploring and understanding adverse drug reactions by integrative mining of clin...

Exploring and understanding adverse drug reactions by integrative mining of clinical records and biomedical knowledge Serious adverse effects resulting from the treatment with thalidomide prompted modern drug legislation more than 40 years ago. Post-marketing spontaneous reporting systems for suspected adverse drug reactions (ADRs) have been a co... see more

31/01/2012

ERASMUS MC

6M€

Project Budget: 6M€

Project leader

ERASMUS UNIVERSITAIR MEDISCH CENTRUM ROTTERDA... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

PARTICIPATION DEPralty Sin fecha límite de participación.

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Financing granted El organismo FP7 notifico la concesión del proyecto The day 2012-01-31 We do not have the information of the call

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14 Participantes

ERASMUS MC

0.00€ | Leader

THE UNIVERSITY OF NOTTINGHAM

N.D. | participant

Fundació Institut Hospital d...

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Project leader

ERASMUS UNIVERSITAIR MEDISCH CENTRUM ROTTERDA... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Project Budget 6M€

participation deadline Sin fecha límite de participación.

Project description Serious adverse effects resulting from the treatment with thalidomide prompted modern drug legislation more than 40 years ago. Post-marketing spontaneous reporting systems for suspected adverse drug reactions (ADRs) have been a cornerstone to detect safety signals in pharmacovigilance. It has become evident that adverse effects of drugs may be detected too late, when millions of persons have already been exposed.In this project, an alternative approach for the detection of ADR signals will be developed. Rather than relying on the physician's capability and willingness to recognize and report suspected ADRs, the system will systematically calculate the occurrence of disease (potentially ADRs) during specific drug use based on data available in electronic patient records. In this project, electronic health records (EHRs) of over 30 million patients from several European countries will be available. In an environment where rapid signal detection is feasible, rapid signal assessment is equally important. To rapidly assess signals, a number of resources will be used to substantiate the signals: causal reasoning based on information in the EHRs, semantic mining of the biomedical literature, and computational analysis of biological and chemical information (drugs, targets, anti-targets, SNPs, pathways, etc.).The overall objective of this project is the design, development and validation of a computerized system that exploits data from electronic healthcare records and biomedical databases for the early detection of adverse drug reactions. The EU-ADR system will generate signals using data and text mining, epidemiological and other computational techniques, and subsequently substantiate these signals in the light of current knowledge of biological mechanisms and in silico prediction capabilities. The system should be able to detect signals better and faster than spontaneous reporting systems and should allow for identification of subpopulations at higher risk for ADRs.

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