The practical impact of automatically tracking the diverse procedural and contextual variables affecting biological experiments can be far-reaching. Currently, the majority of research results cannot be replicated, wasting vast amounts of funding and considerable human effort. Moreover, the difficulty of reproducing biological protocols, a necessity in biological research -- and the lack of seamless interfaces for the multitude of devices and data sources around the lab -- severely limits the broader accessibility and proliferation of biological research methods and results. This I-Corps team is developing a platform (BioBright) to facilitate reproducibility in biological experimentation, by implementing networked hardware and software that automatically compares what should have happened in an experiment with what actually happened.

BioBright is creating an "ecosystem" of software and hardware technologies which enable networked biology. With a platform approach, the goal is to create a line of products that tie into the ecosystem. To date, the team has a patented "context-aware" pipette. One of the initial modes of commercialization includes licensing of this technology to leading pipette and fluid handling manufacturers. Through continued use of the Business Model Canvas (BMC) framework, the team expects to uncover commercial applications for the proposed technology beyond biology and scientific research. The team's preliminary market research and customer interviews suggest that the first customers may include commercial research organizations (CRO), laboratory equipment manufacturers and expand into other markets such as plant biology, in-vitro-fertilization, food production/commercial baking, and other applications where high precision, reproducibility, and exacting quality control are critical.

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Massachusetts Institute of Technology
United States
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