The partnership, unveiled alongside details of Enveda's innovative Foundation Model dubbed PRISM, marks a significant stride forward in the realm of natural product drug discovery. At the heart of this collaboration lies Enveda's PRISM (Pretrained Representations Informed by Spectral Masking), a computational marvel poised to redefine the interpretation of mass spectrometry data. Mass spectrometry stands as a cornerstone in the detection of minute molecules within nature's tapestry. By leveraging over a billion unlabeled mass spectra, PRISM has effectively mastered the intricate syntax and semantics of this data type, enabling it to decipher the chemical language of life itself.

Powered by Microsoft Azure, PRISM transcends conventional boundaries, opening avenues for unprecedented predictions in drug discovery. Through the alchemy of AI, it translates mass spectra into tangible representations of chemical structures or properties, offering a pivotal tool in Enveda's quest to source novel medicines from the natural world.

“Given their leadership in advancing and implementing AI across industries, we are thrilled to collaborate with Microsoft,” says Viswa Colluru, Ph.D., CEO and Founder of Enveda. “We believe this relationship and our new foundation model will further accelerate our ability to find powerful new medicines from natural sources.”

“Large foundation models trained on massive sets of raw data are the basis for modern AI applications. By training PRISM on the largest collection of mass spectra ever assembled, we've created a tool that can help us interpret the language of chemistry and to translate it into new, impactful medicines,” says David Healey, Ph.D., Vice President of Data Science at Enveda.

“The intersection of AI, science, and drug discovery presents a frontier of possibilities,” said Christopher Young, EVP of Business Development, Strategy and Ventures at Microsoft. “By combining Microsoft Azure infrastructure with Enveda's data, expertise, and vision, an entirely new realm of chemistry can be explored to identify new medicines.”

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