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Reviews

Cell viability assessment: toward content-rich platforms

, MS, & , PhD (Head)
Pages 223-233 | Published online: 29 Jan 2010
 

Abstract

Importance of the field: Monitoring cell viability in vitro is critical in many areas of biomedical research, and the ultimate goal in drug discovery is the ability to predict the in vivo toxicology of drug candidates based on their toxicity profile in vitro. Over the last decade, the contribution of high-throughput screening toward this goal has been tremendous, providing the ability to screen compounds in parallel against multiple cell types. However, the toxic effects of drug candidates uncovered during clinical trials are by far the main reason for their failure. Over the same period, our understanding of programmed cell death has evolved dramatically with the identification of critical control points in the cell death pathways. As a result, cell viability should no longer be characterized solely on the basis of discrete end point measurements such as membrane permeability.

Areas covered in this review: This review summarizes the traditional viability assays currently commercially available, focusing on methods amenable to high density format. Assays categorized into the following classes are discussed: dye exclusion assays, DNA condensation-based assays and assays monitoring a metabolic function.

What the reader will gain: We describe current approaches for assessing cell viability and, using case studies, emphasize their limitations. As an alternative, we propose the use of live, multiplexed readouts to accurately record cell death induction.

Take home message: Current low-content methods based on single parameter readouts are prone to error due to the heterogeneity of cell populations and the multi-faceted nature of cell death. High-content approaches based on continuous, multiplexed readouts are becoming increasingly important for monitoring multiple markers of cell death induction simultaneously on a cell by cell basis. The use of such content-rich platforms is a necessity to predict the toxicology of drug candidates accurately.

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