The First Automated Systems

The architecture developed by Zymark for automating sample preparation seemed to be ideal for the automation of processes in drug discovery research. Initially the developments derived from sample preparation automation were directly transferred to automate drug screening applications. In a way, the early integrated robotic systems were engineering challenges implemented by visionary technology adopters. Early automation projects were often awkward attempts that utilized the capabilities of the robotic arm to emulate the actions of human beings. For example, robots were used to pipette liquids as a human does with singlechannel or multichannel pipette hands, to blot plates, or to tweeze filter paper from the bottom of a Alter cup into a scintillation vial. The flexibility and throughput of these early systems was limited to the finesse and speed of the robot; they were often demanding and unreliable and offered no capability for multitasking.

In addition, most of the early screening methods were performed as single, discrete assays in test tubes or scintillation vials, and the automation was dedicated to one assay. Large volumes were required, typically 1 to 5 mL of reagents, and samples were consumed for each assay. Liquid handling devices offered some benefit as stand-alone workstations, but their productivity was limited in that they pipetted and dispensed liquids from test tube to test tube. Finally, most detection systems could only process one sample at a time; data acquisition rates were slow (30 seconds to several minutes per sample) and there was no data interface other than a hard copy print out. All things considered, automation added value by providing unattended operation.

Obviously, the role of automation through integrated robotic systems applied to the drug discovery process has evolved through the last 15 years. Today's laboratory automation is much more robust and reliable, the beneficiary of years of experience. Also, the standardization of assays into microplates has reduced the challenges for automation by providing a predictable environment to operate

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