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IMI is a large public private partnership which has committed Euro 5 Billion from the European Commission, the European Pharmaceutical sector and other partners, to enable and accelerate bringing medical innovation to patients. IMI is now 10 years old and already has changed the ecosystem and way of working in developing innovative medicines across the public/private divide. Big data represents a significant piece of this investment and projects in this area are attempting to provide solutions to major challenges including: 1. Data integration from many sources across many jurisdictions and institutions and which need to be validated with regard to their quality and robustness 2. Data interfaces, for example, between research and clinical data and how to overcome the challenges around data protection and access 3. Data standards and who establishes these and how they are deployed 4. How do we scale and sustain some of the successful pilots to ensure the value of the investment? 5. How do we take advantage of the digital revolution to enable more relevant and accurate data capture in the real world? Much has been done already through IMI projects and beyond and now we need to consolidate through intelligent implementation across the European landscape. With a mixture of generic and disease specific investments, and although many challenges remain, significant progress has been made and examples of success will be described.
This article was published in the following journal.
Name: Studies in health technology and informatics
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Health-related data created, recorded, or gathered by patients, family members, or caregivers, to help address a health concern. Distinct from data generated in clinical settings and through encounters with providers.
The science concerned with the benefit and risk of drugs used in populations and the analysis of the outcomes of drug therapies. Pharmacoepidemiologic data come from both clinical trials and epidemiological studies with emphasis on methods for the detection and evaluation of drug-related adverse effects, assessment of risk vs benefit ratios in drug therapy, patterns of drug utilization, the cost-effectiveness of specific drugs, methodology of postmarketing surveillance, and the relation between pharmacoepidemiology and the formulation and interpretation of regulatory guidelines. (Pharmacoepidemiol Drug Saf 1992;1(1); J Pharmacoepidemiol 1990;1(1))
Information application based on a variety of coding methods to minimize the amount of data to be stored, retrieved, or transmitted. Data compression can be applied to various forms of data, such as images and signals. It is used to reduce costs and increase efficiency in the maintenance of large volumes of data.
Various units or machines that operate in combination or in conjunction with a computer but are not physically part of it. Peripheral devices typically display computer data, store data from the computer and return the data to the computer on demand, prepare data for human use, or acquire data from a source and convert it to a form usable by a computer. (Computer Dictionary, 4th ed.)
The science and art of collecting, summarizing, and analyzing data that are subject to random variation. The term is also applied to the data themselves and to the summarization of the data.
Mergers & Acquisitions
Commercial and market reports on mergers and acquisitions in the biotechnology, pharmaceutical, medical device and life-science industries. Mergers and acquisitions (abbreviated M&A;) is an aspect of corporate strategy, corporate finance and manageme...
A generic drug (generic drugs, short: generics) is a drug defined as "a drug product that is comparable to brand/reference listed drug product in dosage form, strength, route of administration, quality and performance characteristics, and intended u...