Quantification of Fetal Renal Function Using Fetal Urine Production Rate and Its Reflection on the Amniotic and Fetal Creatinine Levels During Pregnancy

Mechanistic Framework to Predict Maternal-Placental-Fetal Pharmacokinetics of Nifedipine Employing Physiologically Based Pharmacokinetic Modeling Approach

Nifedipine is used for treating mild to severe hypertension and preventing preterm labor in pregnant women. Nevertheless, concerns about nifedipine fetal exposure and safety are always raised. The aim of this study was to develop and validate a maternal-placental-fetal nifedipine physiologically based pharmacokinetic (PBPK) model and apply the model to predict maternal, placental, and fetal exposure to nifedipine at different pregnancy stages. A nifedipine PBPK model was verified with nonpregnant data and extended to the pregnant population after the inclusion of the fetoplacental multicompartment model that accounts for the placental tissue and different fetal organs within the Simcyp Simulator version 22. Model parametrization involved scaling nifedipine transplacental clearance based on Caco-2 permeability, and fetal hepatic clearance was obtained from in vitro to in vivo extrapolation encompassing cytochrome P450 3A7 and 3A4 activities. Predicted concentration profiles were compared with in vivo observations and the transplacental transfer results were evaluated using 2-fold criteria. The PBPK model predicted a mean cord-to-maternal plasma ratio of 0.98 (range, 0.86-1.06) at term, which agrees with experimental observations of 0.78 (range, 0.59-0.93). Predicted nifedipine exposure was 1.4-, 2.0-, and 3.0-fold lower at 15, 27, and 39 weeks of gestation when compared with nonpregnant exposure, respectively. This innovative PBPK model can be applied to support maternal and fetal safety assessment for nifedipine at various stages of pregnancy.

Amniotic fluid metabolic fingerprinting contributes to shaping the unfavourable intrauterine environment in monochorionic diamniotic twins

BACKGROUND & AIMS

Amniotic fluid (AF) is the primary intrauterine environment for fetal growth throughout gestation. Selective fetal growth restriction (sFGR) is an adverse complication characterized by unequal growth in twins with nearly identical genetic makeup. However, the influence of AF-mediated intrauterine environment on the development and progression of sFGR remains unexplored.

METHODS

High-throughput targeted metabolomics analysis (G350) was performed on AF samples collected from sFGR (n = 18) and MCDA twins with birth weight concordance (MCDA-C, n = 20) cases. Weighted correlation network analysis (WGCNA) was used to identify clinical features that may influence the metabolite composition in AF. Subsequently, partial least-squares discriminant analysis (PLS-DA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to compare the different types of sFGR and MCDA-C twins. Receiver operating characteristic (ROC) and multivariate ROC curves were utilized to explore potential AF markers in twins with sFGR.

RESULTS

In our study, 182 metabolites were quantified in 76 AF samples. WGCNA indicated that the metabolite composition in late AF may not be influenced by gestational age. PLSDA demonstrated distinct variations between the metabolite profiles of AF in the sFGR and MCDA-C twins, with a significant emphasis on amino acids as the primary differential metabolite. The dissimilarities observed in sFGR twins were predominantly attributed to lipid metabolism-related metabolites. In particular, the KEGG enrichment metabolic pathway analysis revealed significant associations of both types of sFGR twins with central carbon metabolism in cancer. The multivariate ROC curves indicated that the combination of carnosine, sarcosine, l-alanine, beta-alanine, and alpha-n-phenylacetylglutamine significantly improved the AUC to 0.928. Notably, the ROC curves highlighted creatine (AUC:0.934) may be a potential biomarker for severe sFGR.

CONCLUSION

The data presented in this study offer a comprehensive metabolic map of the AF in cases of sFGR, shedding light on potential biomarkers associated with fetal growth and development in MCDA twins.

Utility of Physiologically Based Pharmacokinetic Modeling to Investigate the Impact of Physiological Changes of Pregnancy and Cancer on Oncology Drug Pharmacokinetics

BACKGROUND

The treatment of cancer during pregnancy remains challenging with knowledge gaps in drug dosage, safety, and efficacy due to the under-representation of this population in clinical trials. Our aim was to investigate physiological changes reported in both pregnancy and cancer populations into a PBPK modeling framework that allows for a more accurate estimation of PK changes in pregnant patients with cancer.

METHODS

Paclitaxel and docetaxel were selected to validate a population model using clinical data from pregnant patients with cancer. The validated population model was subsequently used to predict the PK of acalabrutinib in pregnant patients with cancer.

RESULTS

The Simcyp pregnancy population model reasonably predicted the PK of docetaxel in pregnant patients with cancer, while a modified model that included a 2.5-fold increase in CYP2C8 abundance, consistent with the increased expression during pregnancy, was needed to reasonably predict the PK of paclitaxel in pregnant patients with cancer. Changes in protein binding levels of patients with cancer had a minimal impact on the predicted clearance of paclitaxel and docetaxel. PBPK modeling predicted approximately 60% lower AUC and Cmax for acalabrutinib in pregnant versus non-pregnant patients with cancer.

CONCLUSIONS

Our results suggest that PBPK modeling is a promising approach to investigate the effects of pregnancy and cancer on the PK of oncology drugs and potentially inform dosing for pregnant patients with cancer. Further evaluation and refinement of the population model are needed for pregnant patients with cancer with additional compounds and clinical PK data.

Physiologically Based Pharmacokinetics Modeling in the Neonatal Population-Current Advances, Challenges, and Opportunities

Physiologically based pharmacokinetic (PBPK) modeling is an approach to predicting drug pharmacokinetics, using knowledge of the human physiology involved and drug physiochemical properties. This approach is useful when predicting drug pharmacokinetics in under-studied populations, such as pediatrics. PBPK modeling is a particularly important tool for dose optimization for the neonatal population, given that clinical trials rarely include this patient population. However, important knowledge gaps exist for neonates, resulting in uncertainty with the model predictions. This review aims to outline the sources of variability that should be considered with developing a neonatal PBPK model, the data that are currently available for the neonatal ontogeny, and lastly to highlight the data gaps where further research would be needed.

Influence of foetal position on the degree of isolated antenatal hydronephrosis

BACKGROUNDS

The effect of foetal position on the degree of antenatal hydronephrosis (ANH) is unknown. We hypothesized that foetal position is an important contextual factor in ANH, with consequences on prenatal counselling and postnatal management. The current study aimed to investigate the effect of foetal position on the degree of ANH.

METHODS

A retrospective study was carried out on consecutive pregnancies with isolated ANH over a 10-year period. Gestational age, foetal presentation (cephalic vs. breech), and degree of ANH (as measured by the AP diameter) were retrieved. Foetuses with other ultrasound findings of the renal tract (renal parenchymal abnormality, ureteric dilatation, or bladder abnormalities) were excluded. Logistic regression analysis was conducted to examine the relationship between the anterior-posterior diameter (APD) and the mode of presentation (cephalic or breech). A P-value of <0.05 was considered significant.

RESULTS

Initially 745 scans were identified, with 436 included in the final analysis. Overall, there was an association between foetal presentation and APD regardless of trimester, with cephalic presentations having a greater APD (OR 1.07, 95% CI 1.02-1.11, P = 0.04).

CONCLUSION

Cephalic presentations are associated with a significantly greater APD indicating that foetal position should be considered when stratifying ANH. Furthermore, foetal position may be a contributing factor in the mechanism of 'physiological' hydronephrosis.

Use of Physiologically Based Pharmacokinetic Modeling for Hepatically Cleared Drugs in Pregnancy: Regulatory Perspective

Physiologically based pharmacokinetic modeling could be used to predict changes in exposure during pregnancy and possibly inform medicine use in pregnancy in situations in which there is currently limited or no available clinical PK data. The Medicines and Healthcare Product Regulatory Agency has been evaluating the available models for a number of medicines cleared by hepatic clearance mechanisms. Models were evaluated for metoprolol, tacrolimus, clindamycin, ondansetron, phenytoin, caffeine, fluoxetine, clozapine, carbamazepine, metronidazole, and paracetamol. The hepatic metabolism through cytochrome P450 (CYP) contributes significantly to the elimination of these drugs, and available knowledge of CYP changes during pregnancy has been implemented in the existing pregnancy physiology models. In general, models were able to capture trends in exposure changes in pregnancy to some extent, but the magnitude of pharmacokinetic change for these hepatically cleared drugs was not captured in each case, nor were models always able to capture overall exposure in the populations. A thorough evaluation was hampered by the lack of clinical data for drugs cleared by a specific clearance pathway. The limited clinical data, as well as complex elimination pathways involving CYPs, uridine 5'-diphospho-glucuronosyltransferase and active transporter for many drugs, currently limit the confidence in the prospective use of the models. Pregnancy-related changes in uridine 5'-diphospho-glucuronosyltransferase and transport functions are emerging, and incorporation of such changes in current physiologically based pharmacokinetic modeling software is in progress. Filling this gap is expected to further enhance predictive performance of models and increase the confidence in predicting PK changes in pregnant women for hepatically cleared drugs.

Development of the Urinary Tract in Fetal Rats: A Micro-CT Study

INTRODUCTION

 Micro-computed tomography (micro-CT) is an established tool to study fetal development in rodents. This study aimed to use micro-CT imaging to visualize the development of the urinary tract in fetal rats.

MATERIALS AND METHODS

 Fetal rats from embryonic day (ED) 15, ED17, ED19, ED21, and N0 (newborn) (n = 6 per group; 3 males) were fixed and desiccated using the "critical point" technique. We utilized the micro-CT system (SkyScan) and analyzed the resulting scans with CTAn, DataViewer, and ImageJ to visualize the morphology and quantify the volumes of kidney, bladder, adrenal gland, as well as length of the ureter.

RESULTS

 High-resolution micro-CT showed continuous growth of both kidneys from ED15 to N0, with the highest increase between ED19 and ED21. The length of the ureter increased from ED15 to ED21 and remained stable until birth. The volume of the bladder steadily increased from ED15 to N0.In females, a statistically higher volume of the adrenal gland on ED21 was observed, whereas no sex-specific differences were seen for kidney, ureter, and bladder development.

CONCLUSION

 Micro-CT depicts an excellent tool to study urinary tract development in the fetal and neonatal rat. It enables the metric quantification of longitudinal anatomic changes in high definition without previous destructive tissue preparation. The present study revealed sex-specific differences of the adrenal gland development and provides comprehensive data for the understanding of fetal urinary tract development, inspiring future research on congenital urological malformations.

Erythrocyte Membrane-Camouflaged Aggregation-Induced Emission Nanoparticles for Fetal Intestinal Maturation Assessment

Assessment of fetal maturity is essential for timely termination of pregnancy, especially in pregnant women with pregnancy complications. However, there is a lack of methods to assess the maturity of fetal intestinal function. Here, we constructed erythrocyte membrane-camouflaged aggregation-induced emission (AIE) nanoparticles. Nanocore is formed using a hollow mesoporous silicon nanobox (HMSN) of different particle sizes loaded with AIE luminogens -PyTPA (P), which are then co-extruded with erythrocyte membranes (M) to construct M@HMSN@P. The 100 nm M@HMSN@P has a more effective cellular uptake efficiency in vitro and in vivo. Swallowing and intestinal function in fetal mice mature with the increase in gestational age. After intrauterine injection of M@HMSN@P, they were swallowed and absorbed by fetal mice, and their swallowed and absorbed amount was positively correlated with the gestational age with a correlation coefficient of 0.9625. Using the M@HMSN@P (fluorescence intensity) in fetal mice, the gestational age can be imputed, and the difference between this imputed gestational age and the actual gestational age is less than 1 day. Importantly, M@HMSN@P has no side effect on the health status of pregnant and fetal mice, showing good biocompatibility. In conclusion, we constructed M@HMSN@P nanoparticles with different particle sizes and confirmed that the smaller size M@HMSN@P has more efficient absorption efficiency and it can assess fetal intestinal maturity by the intensity of the fluorescence signal.

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.

The Use of Pregnancy Physiologically Based Pharmacokinetic Modeling for Renally Cleared Drugs

Physiologically based pharmacokinetic modeling (PBPK) could be used to predict changes in exposure during pregnancy and possibly inform medicine use in pregnancy in situations where there are currently no available clinical data. The Medicines and Healthcare Product Regulatory Agency has been evaluating the available models for a number of medicines cleared by the kidney. Models were evaluated for ceftazidime, cefuroxime, metformin, oseltamivir, and amoxicillin. Because the passive renal process contributes significantly to the renal elimination of these drugs and changes of the process during pregnancy have been implemented in existing pregnancy physiology models, simulations using these models can reasonably describe the pharmacokinetics of ceftazidime changes during pregnancy and appears to generally capture the changes in the other medicines; however, there are insufficient data on drugs solely passively cleared to fully qualify the models. In addition, in many cases, active transport processes are involved in a drug's renal clearance. Knowledge of changes in renal transport functions during pregnancy is emerging, and incorporation of such changes in current physiologically based pharmacokinetic modeling software is a work in progress. Filling this gap is expected to further enhance predictive performance of the models and increase the confidence in predicting pharmacokinetic changes in pregnant women for other renally cleared drugs.

Recent findings on the role of microRNAs in genetic kidney diseases

BACKGROUND

MicroRNAs (miRNAs) are non-coding, endogenous, single-stranded, small (21-25 nucleotides) RNAs. Various target genes at the post-transcriptional stage are modulated by miRNAs that are involved in the regulation of a variety of biological processes such as embryonic development, differentiation, proliferation, apoptosis, inflammation, and metabolic homeostasis. Abnormal miRNA expression is strongly associated with the pathogenesis of multiple common human diseases including cardiovascular diseases, cancer, hepatitis, and metabolic diseases.

METHODS AND RESULTS

Various signaling pathways including transforming growth factor-β, apoptosis, and Wnt signaling pathways have also been characterized to play an essential role in kidney diseases. Most importantly, miRNA-targeted pharmaceutical manipulation has represented a promising new therapeutic approach against kidney diseases. Furthermore, miRNAs such as miR-30e-5p, miR-98-5p, miR-30d-5p, miR-30a-5p, miR-194-5p, and miR-192-5p may be potentially employed as biomarkers for various human kidney diseases.

CONCLUSIONS

A significant correlation has also been found between some miRNAs and the clinical markers of renal function like baseline estimated glomerular filtration rate (eGFR). Classification of miRNAs in different genetic renal disorders may promote discoveries in developing innovative therapeutic interventions and treatment tools. Herein, the recent advances in miRNAs associated with renal pathogenesis, emphasizing genetic kidney diseases and development, have been summarized.

Application of a Physiologically Based Pharmacokinetic Approach to Predict Theophylline Pharmacokinetics Using Virtual Non-Pregnant, Pregnant, Fetal, Breast-Feeding, and Neonatal Populations

Perinatal pharmacology is influenced by a myriad of physiological variables that are changing dynamically. The influence of these covariates has not been assessed systemically. The objective of this work was to use theophylline as a model drug and to predict its pharmacokinetics before, during (including prediction of the umbilical cord level), and after pregnancy as well as in milk (after single and multiple doses) and in neonates using a physiological-based pharmacokinetic (PBPK) model. Neonatal theophylline exposure from milk consumption was projected in both normal term and preterm subjects. Predicted infant daily doses were calculated using theophylline average and maximum concentration in the milk as well as an estimate of milk consumption. Predicted concentrations and parameters from the PBPK model were compared to the observed data. PBPK predicted theophylline concentrations in non-pregnant and pregnant populations at different gestational weeks were within 2-fold of the observations and the observed concentrations fell within the 5th-95th prediction interval from the PBPK simulations. The PBPK model predicted an average cord-to-maternal plasma ratio of 1.0, which also agrees well with experimental observations. Predicted postpartum theophylline concentration profiles in milk were also in good agreement with observations with a predicted milk-to-plasma ratio of 0.68. For an infant of 2 kg consuming 150 ml of milk per day, the lactation model predicted a relative infant dose (RID) of 12 and 17% using predicted average (C_avg,ss) and maximum (C_max,ss) concentration in milk at steady state. The maximum RID of 17% corresponds to an absolute infant daily dose of 1.4 ± 0.5 mg/kg/day. This dose, when administered as 0.233 mg/kg every 4 h, to resemble breastfeeding frequency, resulted in plasma concentrations as high as 3.9 (1.9-6.8) mg/L and 2.8 (1.3-5.3) (5th-95th percentiles) on day 7 in preterm (32 GW) and full-term neonatal populations.