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Translational disease-driven approach

Our major emphasis is to stay as close to a full picture of human disease as possible. We believe that defining key pathological elements of disease in patient populations has better predictive value with respect to final therapeutic outcomes in the clinic. The strength of our approach is to gather a team of scientific and clinical experts in a particular disease prior to defining a new research program.

Early in a new drug discovery program evaluation process, we collaborate with renowned key clinical opinion leaders to have the latest and the most complete clinical picture of the specific diseased population. Our aim is to be able to validate a minimal set of specifications that an innovative drug candidate must fulfill to bring benefits for the treatment of the disease.

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We have thus developed multiple platforms to address the important domain of translational medicine, employing a range of in vivo, in vitro and in silico tools enabling the pharmacological activity of compounds to be assessed, but also to translate pre-clinical data into human-specific information.
We test our lead candidates in a set of diverse and complementary preclinical assays and models, including human primary cells from disease affected patients that mimic as closely as reasonably possible the different components of the human disease.

This approach is never dissociated from our efforts in biomarker discovery and validation. Easy access to pertinent human and animal samples enables Genfit to develop novel biomarkers that are injected into our drug development programs to better assess pharmacological responses in animal models and better predict beneficial effects in humans.

We also believe that highly selective target driven approaches are not the most reliable way to find innovative and efficacious treatments to bring to the market. Therefore, we prefer to prioritize our lead candidates according to their proof of effective therapeutic action as judged from a number of complementary and disease-relevant physiological outcomes. Thus, compound selection, which is based on phenotypic assays that reproduce important, disease-related mechanisms, is at the very core of decision making in some of our drug discovery programs.