HCS road: an enterprise system for integrated HCS data management and analysis.

The effective analysis and interpretation of high-content screening (HCS) data requires joining results to information on experimental treatments and controls, normalizing data, and selecting hits or fitting concentration-response curves. HCS data have unique requirements that are not supported by traditional high-throughput screening databases, including the ability to designate separate positive and negative controls for different measurements in multiplexed assays; the ability to capture information on the cell lines, fluorescent reagents, and treatments in each assay; the ability to store and use individual-cell and image data; and the ability to support HCS readers and software from multiple vendors along with third-party image analysis tools. To address these requirements, the authors developed an enterprise system for the storage and processing of HCS images and results.

Protein expression plasmids produced rapidly: streamlining cloning protocols and robotic handling.

As many processes in the preclinical drug discovery process become highly parallel, the need to also produce a large number of different proteins in parallel has become acute, such as for protein crystallization and activity screening. In turn, the requisite DNA constructions to produce these proteins must now be done at a rate that requires automated cloning procedures, each with an intrinsic low failure probability per sample. The high-throughput cloning solutions presented here achieve production of 192 different expression plasmids at a success rate of greater than 95% of the targeted open reading frames.