Computational modelling to evaluate, understand and predict the placental transfer of xenobiotics as an integrated system

During pregnancy the baby in the womb can be exposed to medicines the mother is taking and other poisonous substances she might be exposed to. These drugs and poisons are transferred from the mother to the baby via the placenta, which is the organ that connects the baby in the womb to the mother via the umbilical cord. There is currently a lot of uncertainty around exactly how certain substances cross the placenta and to what extent. This lack of information has resulted in pregnant mothers taking drugs that are potentially unsafe, or in contrast led to the advice to avoid drugs required to make the mother better when that was in fact not necessary. To address these issues it is essential that we understand better how the placenta works. Placental transfer is very complex, therefore in this project we propose to use computer simulations to understand better how substances such as drugs and poisonous substances cross the placenta.

Within the placenta the blood from the mother and the baby's blood coming from the umbilical cord do not mix, instead they are kept separated by particular barrier membranes. These placental membranes contain specific transporter molecules that can take certain substances across (for example nutrients needed by the baby), while excluding others. Transporters can also play an active role, allowing the placenta to protect the fetus by pumping out harmful substances. Although we understand how transport proteins work in isolation, we now need to understand how they all work together, and that is where our computer simulations are needed.

We will use laboratory experiments in which placental cells are grown on a porous filter to form a barrier layer. We will then do experiments with lots of different situations to see how much is being transferred across the membranes and then use our computer simulations to work out what all the membrane transporters were doing. We will then compare these results with those from the so called 'placenta-on-a-chip', which is a little laboratory system in which we mimic the effect of the blood flow in the placenta.

Finally we will take real placentas (donated after birth) into the laboratory and connect them up with pumps on both the maternal and fetal side. This will allow us to study the transfer of medicines without endangering the baby. We can then test precisely if our computer simulations can accurately predict what is going on in the real placenta. By combining computer simulations and experiments in this way we will be able to understand better how the placenta works and to what extent drugs and poisonous substances go across from the mother to the baby in the womb.

The transfer of xenobiotics from mother to fetus via the placenta is critical in ensuring the safety of pharmaceutical compounds and the evaluation of the impact of environmental toxins. However, understanding placental transfer poses significant challenges of a practical, ethical and fundamental biological nature. Current pharmacokinetic models for placental transfer are largely phenomenological and the key biological question is to unravel the complexity arising from the interactions between the multiple different uptake and efflux transporter proteins on the apical and basal membranes of the placenta.

We propose that computational modelling of placental xenobiotics transfer as an integrated physiological system will allow us to determine the role of individual membrane transporters, as well as their interactions. We will first use human trophoblast cell culture in the Transwell setup to systematically evaluate the placental barrier function in vitro. This will be compared to transfer in the placenta-on-a-chip microfluidic system under well-defined physiological flow conditions. We will measure the transfer of selected probe substrates over a wide range of conditions and combinations of transporter inhibitors, in apical to basal and basal to apical directions. In combination with the model, this will provide enough information to allow us to identify uniquely the contributions of the individual transporters on each placental membrane.

Importantly, the final model will be validated thoroughly using a series of ex-vivo placental perfusion experiments to evaluate its ability to predict transfer for specific new conditions not previously encountered. Thus, this project presents a unique combination of system level computational modelling bridging the gap between in vitro and ex-vivo experiments to obtain for the first time a comprehensive quantitative insight in the transporter interactions governing the placental transfer of xenobiotics from mother to fetus.

Drug development and safety:
This project will have significant long term impact on drug safety in pregnancy, which will be achieved via advances in quantitative methodologies and biological understanding underpinning treatment, drug development and regulation. This will reduce the costs of drug development and testing and ultimately will impact on quality of life across the life course and in a corresponding reduction in healthcare costs.

Regulation and policy:
In their guidance for industry on pharmacokinetics in pregnancy the FDA highlight the issue of the widespread use of drugs in pregnancy, combined with a severe lack of data even after years of marketing. Supportive evidence from modelling and the critical role of membrane transporters in drug clearance and drug-drug interaction have been recognised by the FDA. In the long term, the biological insight generated using combined experimental-computational methods will impact significantly on government policy by informing regulation on allowable substances, safety and exposure limits. This project will also impact on public engagement in the form of influencing health advice to pregnant women and its implications for lifelong health and wellbeing, with all the associated socioeconomic costs.

Replacement, Reduction and Refinement (3Rs):
This project will benefit the wider pharmaceutical industry via improved in vitro-in vivo extrapolation, avoiding costly late stage failures and leading to savings in drug development. Computational modelling will also avoid ethical issues by reducing the need for animal experiments (including primates), facing reduced societal acceptance.

Biotechnology sector:
This project will create new opportunities in physiologically based computational modelling, which will underpin emerging industries specialised in pharmaceutical modelling and biomedical data analysis. The project will impact directly on training a new generation of highly interdisciplinary scientists, with the ability to combine the analysis of biological systems with an understanding of mathematical and physical principles to deal with real world complexity. This is essential for maintaining UK economic competitiveness in the rapidly developing field of biotechnology and represents one of the key opportunities to maintain our standard of living in the future in the light of ever increasing competition overseas in traditional industry.