|On the right track|
|Going to high-throughput meant that the automation specialists razed their arms and took up tracks.
The Whitehead Institutes Center for Genome Research (Cambridge, MA) was involved in a National Institutes of Health pilot program from 1996 to 1999 to develop methods of high-throughput DNA sequencing for the Human Genome Project. Whiteheads efforts relied heavily on automation, which provided the speed, precision, reliability, and ease of scale-up that this ever-accelerating project required. Institute scientists and engineers had already built a medium-throughput automated pipeline that processed 40005000 samples a day.
However, to feed the more than 100 capillary-based DNA sequence detectors, 50,000100,000 samples would need to be processed each day. To comfortably accomplish this, a 96-well plate would need to be processed every minute.
The robotics components came from a limited number of sources. Using a small set of suppliers makes maintenance, finding spare parts, and upgrades and modifications easier, but it can also work against you when you are subject to a single vendors equipment, prices, timelines, and customer service.
A farewell to arms
For example, our DNA purification protocol requires the addition of two reagents, agitation on a shaker for 4 min, incubation on a magnetic plate for 8 min, and a 3-min wash. The pipettor adds the reagents in well under 1 min, and the gantry moves a plate from the track to the shaker, from the shaker to a magnetic plate, and from the magnetic plate back to the track in less than 1 min. Because the gantry is large and expensive, we did not want more than one on a machine. Therefore, basing our system on a 1-plate/min time frame meant that we needed three plate washers, four shaker positions, and eight magnetic plates. The 12 spots dictated the size of the gantry and told us that one pipettor was enough to dispense the reagents. The tracks employed by CCS Packard eliminated the need to factor plate movement, which is nearly instantaneous, into the design, and secondary functions such as plate stacking and barcode reading are easily performed during the decks cycle.
Impedance matching is possible with both conveyors and pick-and-place robots, but there are tradeoffs associated with each. Conveyors eliminate the addition of plate movement and can cover large distances, which allows for easy placement of the required stations and resources. For pick-and-place robots, however, a large coverage area generally means slower processing, more sources of error, and greater cost. It may also be harder to accommodate all the necessary equipment. That being said, retooling a track system is a daunting task, whereas it is easy to add new stations and resources to a pick-and-place unit if space is available, which is useful in prototyping.
Keep it moving
The ability to add samples to a deck at any time without having to stop, remove all the finished samples, add new samples, and restart the machine speeds the process considerably. Because continuous-feed processes remove multiple ramp-ups during the day, implementing this concept is especially important for long protocols.
For example, part of our DNA purification protocol requires a 45-min ramp-upthe time before the first completed plate emerges from the systemafter which a plate is produced every 1.5 min. Running the deck in 50-plate batches means that in the morning, 45 min is spent ramping up, followed by 75 min of plate processing. On completion, time is spent exchanging old plates for new, followed by a 45-min ramp-up and another 75-min run. In a modest 10-h day, this process is repeated three more times. Wasting about 3 h of process time, the protocol runs at 75% of its potential speed.
Benefits of the CCS Packard machines were a flexible software environment and arrays of sensors that signal plate location. State-driven software was the easiest way to write continuous-feed software, in which actions on the decks are the result of the presence or absence of samples. All the robotic actions are not scripted in advance. Previously, plate locations had to be tracked inside the software, but now, sensor feedback ensures that the software and reality match. The software allows users to remove unfit plates, add plates to the machines whenever they arrive, and implement complete error recovery without adverse consequences.
Of course, flexible software is only as good as the hardware that it manages. There needs to be efficient communication between the control software, the status and errors of each hardware component, and the location and status of each sample. Without this information, the software is ignorant of what is going on, which inevitably leads to more frequent mishaps and slower process times. It is also important to remember that robots crash and that some vendors cannot reboot your robots without losing samples, time, data, or all of the above. For protocols that have many plates in play and long ramp-up times, quick and simple error-recovery functions at the end-user level are critical.
Conveyor-based systems were definitely the right decision for our center. Assembly-line-style automation has been used for years by manufacturers worldwide, and it works just as well in the laboratory.
Andrew Sheridan is the automation coordinator for the Whitehead Institutes Center for Genome Research in Cambridge, MA. Send your comments or questions regarding this article to firstname.lastname@example.org or the Editorial Office by fax at 202-776-8166 or by post at 1155 16th Street, NW; Washington, DC 20036.