I-Corps: A skin phenotype analysis technology using mass spectrometry (MS)-based molecular omics analysis with artificial intelligence (AI)

Award ID: 2114784

The broader impacts/commercial potential of this I-Corps project will provide scientifically-founded insights to empower consumers and professionals to make informed decisions regarding the skincare products they use and guide clients on proper use. Consumers lack an understanding of their skin properties and needs, as well as knowledge around the biochemical basis for the use of a particular product or ingredient. As a result, they spend money and time trying new products and seek professional assistance in managing their skin. This project has the potential to bring robust scientific information to the skincare industry, a sector that is largely unregulated, which may result in an increase of consumer confidence in the beneficial use of their skincare products. Both direct-to-consumer and professional markets can be transformed by this technology, owing to its ability to enable commercial opportunities that will increase the overall health and wellness of individuals through self-testing. This self-testing will drive skincare product manufacturers to formulate high-quality products with ingredient transparency (including product analysis and ingredient quality control) and will create competition in the home testing market. This I-Corps project focuses on a skin phenotype assessment technology to empower consumers to make informed choices about skincare products. Specifically, mass spectrometry (MS)-based molecular omics analysis and artificial intelligence (AI) are used to determine ideal facial skincare products and/or ingredients for an individual's unique skin. The state-of-the-art MS analysis illuminates the composition of skin cells at the molecular level (e.g., amino acids, ceramides). The molecular composition can be used to characterize skin health (e.g., structure, function, environmental exposures, and hydration). The product-skin fit AI matches the needs of the individual's skin to existing products based on the biological functions of active and common ingredients in skincare products. Through prior work in animal models, 5,240 skin analytes were detected and > 50 different lipid and metabolite classes identified. These molecularly-diverse metabolites and lipids highlight the depth of biological information contained in skin cells. Taken together, the skin phenotype technology will allow for the use of scientifically proven data to address the challenges in the skincare industry (i.e. subpar skin results, discarded products, loss of valuable time, and wasted money for consumers) and allow individuals to achieve their skincare needs. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Program Director: Ruth Shuman