TetraScience, Inc.

Despite the myriad number of scientific advances that have occurred in the past decade alone, many laboratory processes, particularly as they apply to data collection and sharing, remain outdated to the point of archaic, often stifling collaboration and potentially delaying scientific advances. Researchers spend an inordinate amount of time observing experiments in person, taking measurements on their instruments before copying the information by hand into lab notebooks and entering it into spreadsheets and electronic notebooks to share with other scientists. Compounding the tedium and potential for human error is the fact that access to data is hindered by a lack of uniformity among a wide range of manufacturers and instruments using disparate languages, formats and systems. Spin Wang recognized these laboratory pain points while working as a researcher at the MIT Department of Electrical Engineering and Computer Science.

His collaborators at the time, former Harvard post-docs and now TetraScience co-founders Alok Tayi (CEO) and Salvatore Savo (COO), were experiencing the same frustrations. If you ask Spin for his definition of innovation, he’ll tell you it’s not about creating something new for the sake of it. Rather, for Spin Wang and his TetraScience colleagues, innovation means identifying a particular industry need and solving that problem. It sounds simple, but it forms the basis for the TetraScience vision and their success: “My co-founders and I recognized a need for research modernization, did the necessary market research and set about applying current technologies—Internet-of-Things, cloud computing, containerization, virtualization—into building this data integration platform to improve the lives of scientists.”

On average it takes more than a decade and costs over $2B to develop and gain market approval for new drugs. Wang and TetraScience are looking to make a major dent in those numbers.

The TetraScience data integration platform features three main components. The first aspect is what they refer to as a TetraScience Link, or the modules and integrations to which researchers connect their equipment, which in turn connects to the cloud. “We’re providing a single repository for your data—not the raw data or a screenshot of your instrument—actual clean, well structured, searchable data and metadata,” says Spin. The second component is a pipeline that facilitates data transfer from one system to another. Spin touches on the fact that such a transfer requires the researcher to facilitate the data flow and most likely perform some type of customized logic. “Our data pipeline allows researchers to orchestrate a sequence of steps and logic to perform data integration in a flexible and configurable way.” Finally, Spin Wang and TetraScience are revolutionizing the field with data integration that is instrument and manufacturer agnostic: “There are a tremendous number of vendors in this ecosystem,” says Spin. These vendors use a variety of interfaces, formats, and even philosophies that inform their software and hardware design. TetraScience data integration gets everyone on the same page, so to speak, allowing any software to communicate with any system in a consistent and vendor agnostic manner.

In addition to their recent induction into MIT’s STEX25 accelerator, TetraScience are recipients of the prestigious Digital Science Catalyst Grant Program Award, former participants in the much-lauded Y Combinator accelerator (2015) as well as counting Founder Collective, Dorm Room Fund, First Round and Floodgate as investors. They’re already partnered with industry leaders in the pharmaceutical and biotechnology fields as well as counting several of the most well-respected research and academic institutions and scientific instrument manufacturers as clients. Spin points out that while their current focus is on enterprise pharmaceutical industry and growth stage biotechnology companies, the ideal partner has less to do with size or scale than mindset: “The 21st century is about data, regardless of industry,” says Spin. “However, life science industries are facing data challenges sooner than many others, simply based on the amount of data being generated.” He continues, “Our ideal clients care about data quality, data hygiene, compliance and traceability. They want to focus on visualization and analytics.” The TetraScience team know first-hand the frustrations of wasted time and inaccessibility of important data. They’re eliminating these headaches and are intent on working with organizations looking for flexible, scalable solutions to their problems and inefficiencies.