@misc{9240444,
  abstract     = {{Small interfering RNAs (siRNAs) are a rapidly growing class of oligonucleotide therapeutics that modulate gene expression by inducing targeted mRNA degradation. siRNAs are potent and their effect is long-lasting, making them promising candidates for chronic neurodegenerative disease. However, siRNAs can elicit both on- and off-target toxicity, and while acute neurotoxicity has been characterized, long-term toxic effects remain poorly studied despite their relevance for chronic treatment. This study aims to optimize a protocol for in vitro screening of long-term siRNA toxicity (6 days to 3 weeks), to enable earlier triage of neurotoxic drug candidates, in line with the 3R principle of replacement, reduction, and refinement of animal testing. Fluorescently tagged siRNA was transfected into cortical neuron-astrocyte cultures from E17.5 rats using Lipofectamine RNAiMAX at varying siRNA concentrations, RNAiMAX dilutions, and complexing times. Cell health was evaluated using immunocytochemistry. Staining was done for morphological markers MAP2 and NeuN for neurons, GFAP for astrocytes, as well as all cell nuclei. The optimized transfection condition was used to evaluate a panel of siRNAs with known in vivo toxicity profiles. This revealed that the optimized method could identify siRNAs exhibiting substantial toxicity, while detection of milder in vivo toxic effects was more limited. Limitations in detecting mildly toxic effects may stem from low transfection efficiency in neurons, overshadowing by transfection-related toxicity or the lack of the immunoreactive cell type microglia in the cultures. These findings provide a foundation for in vitro long-term siRNA neurotoxicity screening.}},
  author       = {{Alexandersson, Linnéa and Envall, Tora}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Optimization and evaluation of an in vitro siRNA transfection protocol for preclinical toxicity screening in rat cortical cultures}},
  year         = {{2026}},
}

