Recently, according to media reports, Ruoyuchen has reached a strategic partnership with AI-based raw materials company MetaNovas Biotech. The two parties will collaborate in areas such as technical services, formulation development, and raw material supply, jointly exploring new avenues for the development of industries such as nutritional health and personal care. It is reported that they also plan to co-develop exclusive raw materials in the future.
MetaNovas was founded in early 2021 in Silicon Valley, USA, and Shanghai, China. The company specializes in designing peptide molecules by integrating AI with biological knowledge graphs, providing product solutions for brands in the nutritional health and personal care industries.
Recently, MetaNovas Biotech completed its Series A financing round, co-led by GL Ventures and Baoding Ventures, with participation from Ruoyuchen as a listed company investor. Moomin Capital acted as the sole financial advisor for this round. The funds raised will primarily be used for product pipeline experiments, new raw material filings, and expanding international customer bases.
Currently, MetaNovas has established a full-chain AI technology platform encompassing raw material formulation, biological mechanisms, molecular design, and product development. It provides innovative raw material development and product solutions for several leading domestic and international consumer goods and cosmetics companies. Leveraging its Silicon Valley origins and interdisciplinary innovation, MetaNovas has entered into deep strategic partnerships with many top multinational corporations (MNCs) and high-potential international brands in its international expansion efforts.
MetaNovas’ co-founder and CEO, Wang Meijie, stated, “For major international personal care companies, developing a new material usually takes over a decade and involves significant experimental investment, making it highly challenging. Using AI, this process can be significantly accelerated.” The company’s self-developed AI platform features a systematic knowledge graph that fully supports raw material formulation analysis, biological mechanism exploration, core target prediction, and the generation of innovative content (AIGC). This enables precise molecular design, identifying new functional peptides and optimizing existing molecules, effectively shortening the development cycle.
