Elucidata, a biotechnology molecular data company, has announced a $16 million Series A funding round. The round was led by Eight Roads Ventures, an international investment firm, with participation from F-Prime Capital, IvyCap Ventures, and Hyperplane Venture Capital.
According to a statement from the company, the funds raised will be used to speed up the global expansion of operations, with a focus in particular on increasing product capabilities in the areas of translational drug research and related markets.
“Elucidata’s technology platform aims to democratize access to curated biomedical data at scale, allowing biopharmaceutical companies to accelerate the discovery and development of novel therapies. We are honored to collaborate with Abhishek, Swetabh, and the team on their vision to accelerate data-centric drug discovery and development.” Ashish Venkataramani, Partner, Eight Roads Ventures.
Polly creates value for its customers by cleaning and linking data at scale
Polly, the company’s data-centric Machine Learning Operations (ML-Ops) platform, is now used for research and development. Firm R&D teams can use this platform to access high-quality, human-curated biomolecular data that can be accessed and analyzed using a graphical user interface (GUI) or automated software.
Polly, which several industry-leading life sciences companies have used, has processed over 2.5 million biomolecular datasets. Polly is used to accelerating drug development by leading pharmaceutical corporations such as Genentech, Pfizer, and Janssen, as well as universities and nonprofits such as Stanford and the Bill & Melinda Gates Foundation.
“Organisations often underestimate the importance of data quality, and as a result, many AI/ML initiatives are compromised. We’re on a mission to derisk such initiatives in life sciences R&D by empowering them with high-quality biomedical data at every stage of the R&D process,” said Dr. Abhishek Jha, CEO, and Co-Founder, Elucidata.
Elucidata predicts that life sciences enterprises will use AI’s advantages in the coming period. This would require a total rethinking of the existing “model-centric” AI narrative, driven mainly by internet businesses but does not apply to specialized industries like life sciences research and development.