Home PublicationsData Innovators 5 Q’s for Yvonne Linney, Chief Executive Officer of Transcriptic

5 Q’s for Yvonne Linney, Chief Executive Officer of Transcriptic

by Joshua New
by
Yvonne Linney

The Center for Data Innovation spoke with Yvonne Linney, chief executive officer of Transcriptic, a company based in Menlo Park, California that automates lab work. Linney discussed how Transcriptic uses the Internet of Things and automation to accelerate biological research, as well as how the use of robotics can make research data more reliable.

This interview has been lightly edited.

Joshua New: Transcriptic has been described as a “robotics cloud laboratory.” What exactly does that mean?

Yvonne Linney: Transcriptic has developed the world’s first robotic cloud laboratory system, which enables life science researchers to use laboratory automation, together with the Internet of Things and cloud technologies, to increase the efficiency, reliability and reproducibility of their research, accelerating time to discovery. Transcriptic uses this system, called the Transcriptic Common Lab Environment (TCLE), in its own robotic cloud lab to provide outsourced bioassay services for pharma and biotech companies. These are accessible through a simple web interface, allowing biologists to design and run their science and generate data from virtually anywhere in the world. Transcriptic also works with partners to integrate TCLE into their own labs, to receive these same benefits.

New: What fields of biology stand to benefit the most from this approach?

Linney: All fields of biology benefit. To date, Transcriptic has focused on building their cloud lab around bioassays, enabling scientists to run routine protein and nucleic acid quantitation assays on demand. However, from an architectural standpoint, TCLE can be implemented across a broader laboratory environment, from drug discovery to industrial biology. For example, Ginkgo Bioworks, a synthetic biology company that engineers organisms across a wide range of markets, is implementing TCLE in their foundries. Another Transcriptic customer wanted to explore a new therapeutic area but didn’t have the resources to commit their usual team size. They leveraged Transcriptic’s robotic cloud lab to run the underlying testing. As a result, the client was able to accomplish the same level of output as a team ten times the size.

New: Surely there is huge variety of lab work relied on in biology. Does Transcriptic only focus on a couple of the most common kinds? Or can the lab be customized to perform a wider variety of analysis?

Linney: Transcriptic has initially focused on building a remote access automated discovery biology platform to provide outsourced bioassay services. However, the overall TCLE infrastructure can be customized and applied to any laboratory. It provides improved reproducibility, remote access and monitoring, plus the ability to easily share protocols and data seamlessly.

New: How reliable is the data generated by Transcriptic’s robotic laboratory compared to human-run labs?

Linney: The combination of laboratory automation, on-line scripted protocols, and the Internet of Things greatly improves data reliability and reproducibility, which is critical in research. Our users regularly state the consistency of their data generation to be the biggest benefit in using Transcriptic and allowing them to dramatically increase their productivity. For example, between 2011 and 2014 several studies estimated that the reproducibility rate in pre-clinical research was less than 50 percent, which translates to over $28 billion per year spent on work that is irreproducible.

New: How does the cost of your services compare to the cost of standard human-run labs?

Linney: The overall costs of utilizing the Transcriptic robotic cloud lab are significantly less. Researchers can do more experiments with the same people resources. There are no additional capital expenditures to add equipment to their labs. And ultimately the improvement in reproducibility significantly reduces wasted dollars spent on repeating experiments and greatly accelerates the time-to-result. Our customers have reported up to ten-fold improvements in productivity.

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