Exosome News: Elevai Labs Scores Grant to Better Characterize Stem Cell-derived Exosomes

Elevai Labs is partnering with Dr. Stanislav Sokolenko’s Lab at Dalhousie University in Nova Scotia, Canada to better characterize Elevai 's stem cell-derived exosomes thanks to a non-repayable grant from the Mitacs Accelerate Grants Program (“Mitacs”).

Mitacs is an organization that funds projects intended to grow research and development initiatives between industry and institutions.

About the project: ELV3000

ELV3000 is a two-year research collaboration between Dr. Sokolenko’s Lab and ELEVAI LABS. The primary aim of this research project is to establish novel techniques for characterizing the bioactive ’payload’ of Elevai Labs’ exosomes and provide Elevai with a greater understanding of how specific exosome contents may be attributable to positive skincare outcomes.

The secondary goal of the project is to further optimize the Elevai Exosome production process which may improve product efficacy through the ability to exert greater control over exosome payloads. The resulting process improvements are expected to result in new and improved products designed to markedly improve the appearance of the skin, scalp, and hair.

We are excited to be working with Dr. Sokolenko to further understand the protein dynamics of our stem cell exosomes,” says  Elevai Founder, Jordan R. Plews, Ph.D, in a news release., “This partnership will continue to accelerate and expand  Elevai’s innovation capabilities, and with the help of our other research partners, enable Elevai to continue to rapidly improve proprietary manufacturing processes and innovative products to better serve the medical aesthetics community and beyond.” 

 “My team and I are very excited to work with Elevai ,” adds Dr. Sokolenko. “Exosome production is a rapidly growing field and developing robust characterization strategies will be essential moving forward. My lab has first-hand experience in the development and characterization of new analytical methods/software that we are eager to apply as part of ELV3000. The underlying challenge in this type of work always remains the same: to separate signal from noise and generate conclusions that are both biologically and statistically sound.”