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What Makes Automation Work? Whitehead Guru Reveals His Secret

PALM SPRINGS, Calif., Jan. 30 - Humans got the credit for sequencing the human genome, but the robots made much of it possible.


And the human who deserves the credit for getting the robots up to speed is Andrew Sheridan, automation coordinator at the Whitehead Institute's Center for Genome Research.


Schedule changes for the Human Genome Project "required our facility to scale ten fold in less than a year," explained Sheridan, who spoke on Tuesday here at the LabAutomation conference. He added that it took his team approximately eight months to reach that goal, and a 20-fold increase was achieved at the 12-month mark.


"Pretty good for a research lab," he allowed.


So how'd he do it? Sheridan advocates buying pieces of a system, an approach toted on the conference exhibition floor and one now being marketed by manufacturers.


"We tried to buy tools, not a package," said Sheridan. "You can't make a lot of progress if you can't get into code and make changes."


The robotic systems used in Whitehead's sequencing effort, which contributed one third of the human genome sequence to Genbank, included seven colony pickers, about 150 detection units, two units each for inoculations and resuspensions, and three primary and two secondary DNA prep units.


Sheridan also minimized cycle times by impedance matching. "If you paid for instrumentation that is not being used all the time, you aren't impedance matched," according to Sheridan, who suggested subtracting steps from protocols and matching component outputs to reduce cycle times.


He also advised cutting out batch processing and racks in favor of continuous feed systems.


"Stacks are the way to go," he stressed.


Sheridan also recommended uncoupling robotics from a network to avoid work stoppages caused by database crashes or network outages. "We hate to stop if we don't have a network," he explained.


And the number one secret for maximizing robotics? People.


"The most important [factor is] the types of people," said Sheridan. "Everyone's fairly amazed at the team we had, [with people of] different backgrounds working on a common goal."


To get the best results it is best to get those people--biologists, computer scientists, and others--working as close as possible, said Sheridan. "The manpower cooperation factor dissipates with the distance people are away from each other," he emphasized.

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