Objective
When a new medicine reaches the market, it is accompanied by an extensive data package that provides information about the safety and efficacy of the medicine in a clinical trial setting. However, assessing the expected future value of the medicines when used in “real world” clinical practice requires additional information next to traditional (pre-authorisation) clinical trials. Regulatory, HTA agencies and other healthcare decision makers have to make decisions on authorisation and access under conditions of uncertainty. Currently, data packages which aim to minimise uncertainty on safety and efficacy may leave significant uncertainty in assessments of real world effectiveness of new medicines. This results in further research commitments required post-authorisation (PASS, PAES, Reimbursement with Evidence Generation), and wide variability in access to medicines between countries.
The subsequent uncertainty relating to the reimbursement, and thus market implementation of new medication once approved by regulatory authorities, is negatively affecting the value of the drug development pipeline. The costly clinical developments to get to market approval, no longer seem to be a guarantee for market entry. This new risk presents a serious additional hurdle for drug developers that already face pipeline attrition. It also affects the speed and level of patient access, and therefore the extent to which patients and society might benefit from new medicines.
In recent years there has been considerable attention paid to the post-authorisation evaluation of treatments in real world clinical practice: study design and analytical methodology for assessing relative effectiveness; and use of registries and electronic healthcare data. It may be possible to improve the value of information available at initial market authorisation by incorporating these techniques into pre-authorisation drug development. HTA bodies, regulators, will become able to make better-informed decisions, and developers of new medicines will be able to direct development efforts to areas where value is most likely to be delivered to patients and health care systems, improving the efficiency of the whole medicine development chain.
However, the adoption of real world / relative effectiveness objectives in a pre-authorisation development strategy has many operational, methodological, regulatory, and ethical issues and Pharmaceutical R&D organisations need more certainty as to: the impact of development choices on the regulatory review process; the value of different programmes to HTA bodies and other decision makers; the best balance of pre-launch and post-launch effectiveness research and the coordination of various post-authorisation commitments. There is little guidance on how to incorporate alternative study designs into a development programme to optimally meet the needs of all stakeholders over time.
The GetReal consortium aims to improve the efficiency of the medicine development process by better incorporating real-life clinical data into drug development and to enrich decision-making by regulatory authorities and HTA bodies through:
• Bringing together regulators, HTA bodies, companies, patients and other societal stakeholders
• Assessing existing processes, methodologies, and key research issues
• Proposing innovative (and more pragmatic) trial designs and assessing the value of information
• Proposing and testing innovative analytical and predictive modelling approaches
• Assessing operational, ethical, regulatory issues and proposing and testing solutions;
• Creating new decision making frameworks, and building open tools to allow for the evaluation of development programmes and use in the assessment of the value of new medicines;
• Sharing and discussing deliverables with, among others, Pharmaceutical companies, regulatory authorities, HTA / reimbursement agencies, clinicians and patient organizations;
• Developing trai
Fields of science (EuroSciVoc)
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 discovery
- medical and health sciencesbasic medicinepharmacology and pharmacypharmaceutical drugs
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Call for proposal
IMI-JU-07-2012
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Coordinator
WC1A 1DG LONDON
United Kingdom
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Participants (29)
3584 CX Utrecht
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1112 ZA DIEMEN
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LE1 7RH Leicester
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3012 Bern
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1200 Bruxelles / Brussel
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75015 Paris
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93218 Saint Denis La Plaine Cedex
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1083 HS Amsterdam
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Participation ended
SE1 7QY London
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Participation ended
WC1E 7HT London
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45110 Ioannina
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M1 4BT Manchester
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9713 GZ Groningen
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94250 GENTILLY
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RG21 4FA Basingstoke
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08889 Whitehouse Station Nj
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55218 Ingelheim
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2340 Beerse
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1831 Diegem
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10154 New York
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13353 Berlin
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151 85 Sodertaelje
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2880 Bagsvaerd
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4070 Basel
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4056 Basel
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64293 DARMSTADT
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WC2B 4AE London
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M13 9PL Manchester
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N1 6AH LONDON
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