Through real-time metabolite monitoring, Bitome’s technology is expected to support accelerated product development timelines across Ginkgo’s portfolio of cell programs
Ginkgo Bioworks , the leading horizontal platform for cell programming, announced that it has acquired certain assets from Bitome, a company pioneering real-time metabolite monitoring for faster biological product development. Bitome has developed technology leveraging machine learning to provide continuous monitoring of cell culture media, illuminating the performance of cells in real-time and enabling faster rates of bioprocess optimization.
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In the design-build-test-learn process that is central to synthetic biology, testing the performance of cells is an expensive and time-consuming bottleneck. Bitome’s continuous metabolite monitoring technology can help address this bottleneck, providing essential data on cell performance and potentially accelerating the path to production-ready organisms. Real-time data on the metabolic state of the cells in a bioreactor helps scientists better anticipate which cell lines and process conditions to select for further optimization, which in turn can reduce the number and duration of bioreactor runs that are necessary for a given project.
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“Ginkgo is constantly looking for opportunities to strengthen its cell engineering platform, and a central component of cell engineering is testing and optimizing strains at scale,” said Barry Canton, co-founder and Chief Technology Officer at Ginkgo Bioworks. “Having evaluated Bitome’s technology over the past few years, we believe their technology will allow us to accelerate the design and optimization of strains across a range of customers and industries.”
“Bitome was founded to unleash faster biotech innovation, and one of the core obstacles this industry faces is incomplete strain performance data,” said Herbert Ryan, co-founder and CEO at Bitome. “Our team is thrilled to be joining the Ginkgo platform where we can deploy our technology much more broadly to create the next generation of synthetic biology.”
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