Breakthrough gene expression search engine for cost reduction and significantly increased use of open data in drug discovery.

Project Information

XPRESSO

Grant agreement ID: 673405

DOI

10.3030/673405

Project closed

EC signature date 27 April 2015

Start date 1 May 2015

End date 31 October 2015

Funded under

• INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT)

Total cost

€ 71 429,00

EU contribution

€ 50 000,00

Coordinated by

MEDICAL TECHNOLOGY GROUP OU
Estonia

Periodic Reporting for period 1 - XPRESSO (Breakthrough gene expression search engine for cost reduction and significantly increased use of open data in drug discovery.)

Reporting period: 2015-05-01 to 2015-10-31

Summary of the context and overall objectives of the project

During the Phase 1 innovation project we assessed the commercial potential of an advanced gene expression search engine. We can see that the service can bring about a shift in information retrieval in life sciences through pre-analyzed public data. We conducted a survey among potential users and received valuable feedback about the type of solution that they would want to use.

From the feedback we understood that among the users there was a need for an easy to use tool that could encompass large amounts of good quality data. In addition the usability of such a tool plays an important part in usage adoption.

In addition we attended several meetings with people form the biomedical industry and learned that the ability to normalize heterogeneous data and make it available for analysis is an important aspect when dealing with -omics data. As such we analyzed publicly available datasets and determined the ones, which could add value for the potential users of the solution.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

* End user survey to learn about feedback to the proposed search engine.
* Produced feasibility analysis and business plan.
* Met with biomedical industry players and learned about the importance of including various data sources to benefit the biomedical research community.
* Received coaching from an industry expert and set out a plan for tailoring the solution for potential institutional customers (i.e. research labs, pharmaceutical and biotech companies).

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

During the course of the project we verified that our proposed solution has impact because it allows scientists and researchers to interpret previous experiment results, which paves way for new discoveries. Users appreciate the value in finding experiments that affect the expression of the gene they are researching. This has positive impacts on increasing the likelihood of success in research experiments and as such has a positive impact on the medical research community.

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