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Exsymol joins forces with ExAdEx-Innov to explore new perspectives in adipose tissue research 

Exsymol, a company specializing in the design and production of active ingredients for the cosmetics and nutrition sectors, announces an unprecedented collaboration with ExAdEx-Innov, a French biotech startup spun out of the University of Nice, focusing on research applied to human adipose tissue. 

For Exsymol, the objective of this strategic collaboration is clear: to take advantage of the latest technologies by collaborating with startups at the cutting edge of innovation to maximize the value of its active ingredients, and thus reinforce their commitment to delivering top-quality products to their customers. 

ExAdEx-Innov draws on more than three decades of experience in human adipose tissue research to offer innovative tools for the cosmetics, nutraceutical and biomedical industries. ExAdEx technology exploits the intrinsic capacity of adipose stem cells to proliferate in response to stimuli, and uses the tissue matrix of native tissue as a bioactive support for their proliferation. These models ex vivo have unique characteristics, including long-term viability, a complete extracellular matrix structure, lipid droplet size comparable to that of endogenous tissue, and much more.

ExAdEx technology offers a unique opportunity for innovation in adipose tissue research and product development. Working in partnership with Exsymol opens up new perspectives in the beauty industry. 

Exsymol recognizes the innovative opportunities offered by the patented technology developed by ExAdEx-Innov, which enables the generation of research models. ex vivo of human adipose tissue. These unique models are clinically relevant and integrate the complex 3D biology of native adipose tissue.

This collaboration marks a significant step forward in the repositioning and development of cosmetic active ingredients, using human adipose tissue models. ex vivo reliable quality, very close to the fabric in vivoto evaluate new claims and generate relevant data.

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