Adaptation of robust Z′ factor for assay quality assessment in microelectrode array based screening using adult dorsal root ganglion neurons

Background: Cell-based assays comprising primary sensory neurons cultured in vitro are an emerging tool for the screening and identification of potential analgesic compounds and chronic pain treatments. High-content screening (HCS) platforms for drug screening are characterized by a measure of assay quality indicator, such as the Z'-factor, which considers the signal dynamic range and data variation using control compounds only. Although widely accepted as a quality metric in high throughput screening (HTS), standard Z'-factor are not well-suited to indicate the quality of complex cell-based assays. New Method: The present study describes a method to assess assay quality in the context of extracellular recordings from dorsal root ganglion (DRG) sensory neurons cultured on multi-well microelectrode arrays. Data transformations are applied to electrophysiological parameters, such as electrode and well spike rates, for valid normality assumptions and suitability for use as a sample signal. Importantly, using transformed well-wide metrics, a robust version of the Z'-factor was applied, based on the median and median absolute deviation, to indicate assay quality and assess hit identification of putative pharmacological compounds. Results: Application of appropriately scaled data and robust statistics ensured insensitivity to data variation and approximation of normal distribution. The use median and median absolute deviation of log transformed well spike rates in computing the Z'-factor revealed a value of 0.61, which is accepted as an excellent assay. Known antagonists of nociceptor-specific voltage-gated sodium ion channels were identified as true hits in the present assay format under both spontaneous and thermally stimulated conditions. Comparison with Existing Methods: The present approach demonstrated a large signal dynamic range and reduced sensitivity to data variation compared to standard Z'-factor used widely in HTS. Conclusion: Overall, the present study provides a statistical basis for the implementation of a HCS platform utilizing adult DRG neurons on microelectrode arrays.