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About liver disease


Since early 2000, GENFIT has been convinced of the importance of bioinformatics in the R&D process.

We rely on both external solutions and those developed by our teams, thus enabling us to benefit from customized solutions particularly in biostatistics.

These platforms stimulate scientific reflection and contribute to decision-making. The NASH database is one of our finest examples.

In a field where technology is evolving at an increasing pace and where huge volumes of complex data accumulate, our competitive instinct drives us to continually update our bioinformatics approaches.

Thus, we work on the development, installation and evolution of informatics systems that enable our scientists to benefit from an environment adapted to the optimal use of their knowledge and skills.

We also implement different approaches in biostatistics/data-mining in order to extract the essential information from our databanks and optimize its interpretation.

Our bioinformatics contribution to the discovery of novel biomarkers

Our predictive and diagnostic biomarker programs benefit from this skill and experience.
Our bioinformaticians accompany our research teams from study design up to biostatistical analyses enabling data exploration, “signature” identification, functional analyses, or patient stratification.

Various types of data are analyzed, from transcriptomics (RNA, miRNA) through proteomics, up to clinical data.
The major challenge is to combine all these data-sets in order to identify a biomarker for the detection of a pathological state, to follow the development of a disease, or its regression in response to treatment.

Promoting collaborative data analysis

Our expertise in the development of informatics systems has led us to put data access at the heart of our strategy.

We therefore set up and evolve customized platforms to accompany our scientists’ decision-making for each of our programs (for example the NASH databank).

Each of these platforms promotes the collection of different types of data (samples, experiments, etc.).
They enable the data to be provided to our scientists in different forms (analytical reports, graphs, data extracts, etc.), thus facilitating data access and analysis.

Our scientific teams therefore benefit from a tools that enable them to access the latest available data, thus representing a considerable advantage to our R&D process.

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