Ganymede Bio, the cloud infrastructure provider purpose-built for the life sciences and manufacturing industries, has announced a $12.75 million series A funding round, led by Caffeinated Capital.
This follows a $2.9 million seed round completed earlier this year, bringing the total to more than $15.6 million. Founded in 2022, Ganymede Bio has exceeded $1 million in revenue commitments, with clients ranging from early-stage biotechs to large, established biopharmaceutical companies.
“Scientific software, especially for biotechs, is 10 to 20 years behind other industries,” said Nathan Clark, co-founder of Ganymede Bio.
“We have built a platform that allows rapid coding integrations between instruments and apps like LIMS or MES, generates a singular data lake in a harmonized format, and fits modularly into any client tech stack—integrating natively with existing clouds in AWS or GCP or Azure. This makes data and operations visible to management and analysis-ready for machine learning or digital twins.”
Ganymede Bio’s data platform is powered by its Lab-as-Code core technology. It enables scientists and bioinformaticians to write their own real-time integrations and scientific analysis in a low-code cloud IDE by directly connecting to any lab instrument or scientific software, quickly bringing entire labs and manufacturing sites onto the cloud. Ganymede Bio also offers end-to-end enterprise services and builds custom integrations for clients.
“Ganymede’s speed and flexibility in integrating instruments through Lab-as-Code has been incredibly powerful for us,” said Angelo Stracquatanio, CEO and founder of Apprentice, one of Ganymede Bio’s earliest partners.
“We’re proud to be partnering across biopharma manufacturing and R&D to get therapeutics to patients faster than ever.”
Wasting less time
“We like to say we give superpowers to scientists so they can waste less time on moving data around and instead spend more time on analyzing data and deriving novel insights,” said Alan Chramiec, founding scientist of Ganymede Bio.
“The scientific process at its core involves piecing together data from multiple instruments and sources, and we finally give scientists the tool to centralize all their data and automate these efforts. We’re making the lab of the future attainable today.”