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S election of the optimum cell line from large populations can be time consuming and laborious. Compromises are often necessary to meet challenging timelines, but can limit the parameters or cell line construction strategies that can be evaluated. This article describes a new automated cell culture system for cell line selection and characterization. The technologies enable data to be obtained from large numbers of cells lines allowing users to evaluate, in parallel, a wider range of molecular approaches and cell culture processes. This facilitates more rapid and efficient cell line development. Also, presented are initial biological testing data for the new system and descriptions of how highly parallel processing can contribute to significantly reduced cycle times and better decision making through the rapid identification of optimum cell lines and culture conditions.

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