Determination of the transport rate of xenobiotics and nanomaterials across the placenta using the ex vivo human placental perfusion model.

Decades ago the human placenta was thought to be an impenetrable barrier between mother and unborn child. However, the discovery of thalidomide-induced birth defects and many later studies afterwards proved the opposite. Today several harmful xenobiotics like nicotine, heroin, methadone or drugs as well as environmental pollutants were described to overcome this barrier. With the growing use of nanotechnology, the placenta is likely to come into contact with novel nanoparticles either accidentally through exposure or intentionally in the case of potential nanomedical applications. Data from animal experiments cannot be extrapolated to humans because the placenta is the most species-specific mammalian organ (1). Therefore, the ex vivo dual recirculating human placental perfusion, developed by Panigel et al. in 1967 (2) and continuously modified by Schneider et al. in 1972 (3), can serve as an excellent model to study the transfer of xenobiotics or particles. Here, we focus on the ex vivo dual recirculating human placental perfusion protocol and its further development to acquire reproducible results. The placentae were obtained after informed consent of the mothers from uncomplicated term pregnancies undergoing caesarean delivery. The fetal and maternal vessels of an intact cotyledon were cannulated and perfused at least for five hours. As a model particle fluorescently labelled polystyrene particles with sizes of 80 and 500 nm in diameter were added to the maternal circuit. The 80 nm particles were able to cross the placental barrier and provide a perfect example for a substance which is transferred across the placenta to the fetus while the 500 nm particles were retained in the placental tissue or maternal circuit. The ex vivo human placental perfusion model is one of few models providing reliable information about the transport behavior of xenobiotics at an important tissue barrier which delivers predictive and clinical relevant data.