Soluble epoxide hydrolase in the human placenta throughout gestation

Physiologically based pharmacokinetic modeling to predict maternal pharmacokinetics and fetal carbamazepine exposure during pregnancy

Carbamazepine is an antiepileptic drug commonly used in pregnant women, during which the physiological changes may affect its efficacy. The aim of this study was to establish a physiologically based pharmacokinetic (PBPK) model of carbamazepine and its active metabolite carbamazepine-10,11-epoxide, and simulate maternal and fetal pharmacokinetic changes of carbamazepine and carbamazepine-10,11-epoxide in different trimesters and propose dose adjustment. We established pregnancy PBPK models for carbamazepine and carbamazepine-10,11-epoxide in PK-Sim® and Mobi® and validated the models with observed data from clinical reports. The placental transfer parameters obtained using different methods were also imported into the model and compared with the observed data to establish and validate fetal pharmacokinetic curves. The simulated results showed that mean steady-state trough plasma concentration of carbamazepine decreased by 27, 43.1, and 52 % during the first, second, and third trimesters, respectively. Therefore, to achieve an optimum therapeutic concentration, administering at least 1.4, 1.8, and 2.1 times the baseline dose of carbamazepine in the first, second, and third trimesters, respectively can be used as a dose reference. In conclusion, this study established and validated a pregnancy PBPK model of carbamazepine and carbamazepine-10,11-epoxide to assess exposure in pregnant women and fetuses, which provided a reference for the dosage adjustment of carbamazepine during pregnancy.

Evaluation of nanoplastics toxicity to the human placenta in systems

Following the discovery of plastics in the human placenta, this study evaluated the toxicity of ten different nanoplastics (NPs) in the human placenta. Since the placenta performs metabolic and excretion functions by the enzymatic system, the NPs were docked on these human enzymes including soluble epoxide hydrolase, uracil phosphoribosyltransferase, beta 1,3-glucuronyltransferase I, sulfotransferase, N-acetyltransferase 2, and cytochrome P450 1A1at their active sites with toxicity (binding affinity) determined and compared to control compounds. Density functional theory analysis were conducted on the NPs to identify their global reactivity descriptors and Artificial Neural Networks to predict toxicity based on reactivity descriptors. Polycarbonate (PC), polyethylene terephthalate (PET) and polystyrene (PS) showed the highest toxicity to all enzymes and thus the most toxic polymers due to the presence of an electron-withdrawing group in their aromatic rings, which demonstrated an improved recognition of the enzyme active site by pi- and alkyl interactions. A 2^10-6 fractional factorial design approach was used in conjunction with a fixed effects model to assess the primary and secondary effects of NPs in a composite system on binding affinity to the placental enzymes. The simulation results suggest that NPs mixture may pose significant risks to the placenta through inhibition of its key enzymes.

Predicting Human Fetal Drug Exposure Through Maternal-Fetal PBPK Modeling and In Vitro or Ex Vivo Studies

Medication (drug) use in human pregnancy is prevalent. Determining fetal safety and efficacy of drugs is logistically challenging. However, predicting (not measuring) fetal drug exposure (systemic and tissue) throughout pregnancy is possible through maternal-fetal physiologically based pharmacokinetic (PBPK) modeling and simulation. Such prediction can inform fetal drug safety and efficacy. Fetal drug exposure can be quantified in 2 complementary ways. First, the ratio of the steady-state unbound plasma concentration in the fetal plasma (or area under the plasma concentration-time curve) to the corresponding maternal plasma concentration (ie, Kp,uu ). Second, the maximum unbound peak (Cu,max,ss,f ) and trough (Cu,min,ss,f ) fetal steady-state plasma concentrations. We (and others) have developed a maternal-fetal PBPK model that can successfully predict maternal drug exposure. To predict fetal drug exposure, the model needs to be populated with drug specific parameters, of which transplacental clearances (active and/or passive) and placental/fetal metabolism of the drug are critical. Herein, we describe in vitro studies in cells/tissue fractions or the perfused human placenta that can be used to determine these drug-specific parameters. In addition, we provide examples whereby this approach has successfully predicted systemic fetal exposure to drugs that passively or actively cross the placenta. Apart from maternal-fetal PBPK models, animal studies also have the potential to estimate fetal drug exposure by allometric scaling. Whether such scaling will be successful is yet to be determined. Here, we review the above approaches to predict fetal drug exposure, outline gaps in our knowledge to make such predictions and map out future research directions that could fill these gaps.