SAVANA SIGNED
Massive reutilization of Electronic Health Records (EHRs) through AI to enhance clinical research and precision medicine
Total Cost €
0EC-Contrib. €
0Partnership
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0SAVANA project word cloud
Explore the words cloud of the SAVANA project. It provides you a very rough idea of what is the project "SAVANA" about.
Project "SAVANA" data sheet
The following table provides information about the project.
| Coordinator |
MEDSAVANA SL
Organization address contact info |
| Coordinator Country | Spain [ES] |
| Project website | https://savanamed.com |
| Total cost | 1˙803˙600 € |
| EC max contribution | 1˙262˙520 € (70%) |
| Programme |
1. H2020-EU.3. (PRIORITY 'Societal challenges) 2. H2020-EU.2.3. (INDUSTRIAL LEADERSHIP - Innovation In SMEs) 3. H2020-EU.2.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies) |
| Code Call | H2020-SMEInst-2018-2020-2 |
| Funding Scheme | SME-2 |
| Starting year | 2018 |
| Duration (year-month-day) | from 2018-11-01 to 2020-04-30 |
Partnership
Take a look of project's partnership.
| # | ||||
|---|---|---|---|---|
| 1 | MEDSAVANA SL | ES (MADRID) | coordinator | 1˙262˙520.00 |
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Project objective
In the last twenty years, the average return on R&D expenditure in the pharma industry has dropped from almost 18% to 3.7%. Moreover, annual funding for biomedical research has more than doubled while new drugs approvals have declined by one third. There is a wide consensus that the main cause of this problem is the exhaustion of a model intended to develop ‘broad indications’ and the need for a new ‘precision medicine’ model. We simply do not know enough about the underlying disease mechanisms involved, and more research is required to develop better disease classifications, which will enable a more targeted development approach for drugs and therapies.
Electronic Health Records (EHRs) has been used for more than ten years in most developed countries, and they gather now exhaustive clinical information of millions of patients. Leveraging EHRs could accelerate clinical research, and improve healthcare quality.
However, in order to uncover unknown disease models from EHRs, precision medicine requires massive research studies on thousands of patients (often in several countries). Currently there is no tool capable of: 1) automating the extraction of data from EHRs, and also, solving the privacy concerns raised by EHRs.
SAVANA RESEARCH uses Natural Language Processing to extract data from massive amounts of EHRs’ clinical narratives. It has the following advantages intended to make a leap in clinical research efficiency: 1) It uses only de-identified clinical records and ensures state of the art technologies to protect data privacy; 2) It is capable of decoding ten times more EHRs in half of the time; 3) It is capable of identifying 100 times more variables from EHRs; 4) And it costs 40% less. The application of NLP to healthcare is a fast-growing market that is expected to reach 2.65 billion by 2021, by growing at a CAGR of 20.8%. SAVANA RESEARCH’s target markets are primary Europe and North America, which together comprises 75% of all clinical trials worldwide.
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