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Gene expression analysis by quantitative real-time polymerase chain reaction (RT-qPCR) is routinely used in biomedical studies. The reproducibility and reliability of the data fundamentally depends on experimental design and data interpretation. Despite the wide application of this assay, there is significant variation in the validation process of gene expression data from research laboratories. Since the validity of results depends on appropriate normalisation, it is crucial to select appropriate reference gene(s), where transcription of the selected gene is unaffected by experimental setting. In this study we have applied geNorm technology to investigate the transcription of 12 'housekeeping' genes for use in the normalisation of RT-qPCR data acquired using a widely accepted HepaRG hepatic cell line in studies examining models of pre-clinical drug testing. geNorm data identified a number of genes unaffected by specific drug treatments and showed that different genes remained invariant in response to different drug treatments, whereas the transcription of 'classical' reference genes such as GAPDH (glyceralde- hyde-3-phosphate dehydrogenase) was altered by drug treatment. Comparing data normalised using the reference genes identified by geNorm with normalisation using classical housekeeping genes demonstrated substantial differences in the final results. In light of cell therapy application, RT-qPCR analyses has to be carefully evaluated to accurately interpret data obtained from dynamic cellular models undergoing sequential stages of phenotypic change.