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Summary:

A life-sciences-as-a-service startup called Transcriptic has opened its APIs to the general public, allowing researchers around the world offload tedious lab work to robots so researchers can spend more of their time analyzing the results.

robottranscriptic
photo: Transcriptic

A Menlo Park, California, startup called Transcriptic opened a unique service to the world’s genetic researchers on Tuesday. Using a set of APIs, researchers can now command Transcriptic’s purpose-built robots to process, analyze, and store their genetic or biological samples, and receive results in days.

The high concept idea, says Founder and CEO Max Hodak, is cloud computing for life sciences — only with “robotic work cells” instead of  servers on the other end. “We see the lab in terms of the devices that make it up,” he said, meaning stuff like incubators, freezers, liquid handlers and robotic arms to replace human arms.

And although Transcriptic’s technology is complex, the process for getting work done is actually pretty simple. Researchers write code to tell the robots exactly what to do with the samples (right now, the company focuses on molecular cloning, genotyping, bacteria-growing and bio-banking), and then they send their samples to the Transcriptic lab. Alternatively, Transcriptic’s robotic infrastructure can also synthesize samples for users.

When the job is done, researchers get their results. That process can take anywhere from a day to weeks, Hodak explained, in part because the company’s operation is still pretty small and in part because “cells only grow and divide so quickly.”

Transcriptic was founded in 2012 and so far has raised $4 million in venture capital from Google Ventures and others.

The molecular cloning process with Transcriptic.

The molecular cloning process with Transcriptic.

Still, using Transcriptic’s service touts a number of advantages for scientists over doing lab work themselves. For starters, robots don’t get tired after long days and so are less prone to mistakes that could end up costing a lot of time to redo later, Hodak said. Because the process is asynchronous, scientists can start analyzing a given job whenever it suits them, and they don’t have to worry about storing the samples or the results in the meantime.

Early users have been university researchers at Caltech, Stanford, Harvard and the University of California, San Diego, but Hodak sees a bright future in the pharmaceutical industry, as well. Already, large pharmaceutical companies are trying to cut costs by by licensing the the discoveries of smaller, nimbler companies. The way he sees it, if Transcriptic can provide these smaller firms with cheap, easy access to research infrastructure, they’ll be more flexible and be able to conduct more-innovative experiments.

“Really, it’s a research problem,” he said, noting that concerns over the cost and difficulty of clinical trials might be overblown. “The resources that you have access to really change the questions you can ask,” he added.

If research labs buy into Transcriptic’s pitch, the company is ready to grow, Hodak said. It will add new services and new instructions for existing services, and has designed its physical infrastructure to scale pretty easily. The company has a dedicated hardware team that designs equipment specially designed for Transcriptic’s unique environment, and that saves the company a lot of money. Its liquid handlers, for example, cost less than 10 percent of commercially available gear and actually improved precision.

“Every time we’ve built infrastructure,” Hodak said, “we’ve saved one or two orders of magnitude on the cost.”

 

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