Ulgen K. Advances in Physiologically Based Pharmacokinetic (PBPK) Modeling of Nanomaterials

Nanoparticles (NPs) have been widely used to improve the pharmacokinetic properties and tissue distribution of small molecules such as targeting to a specific tissue of interest, enhancing their systemic circulation, and enlarging their therapeutic properties. NPs have unique and complicated in vivo disposition properties compared to small molecule drugs due to their complex multifunctionality. Physiologically based pharmacokinetic (PBPK) modeling has been a powerful tool in the simulation of the absorption, distribution, metabolism, and elimination (ADME) characteristics of the materials, and it can be used in the characterization and prediction of the systemic disposition, toxicity, efficacy, and target exposure of various types of nanoparticles. In this review, recent advances in PBPK model applications related to the nanoparticles with unique properties, and dispositional features in the biological systems, ADME characteristics, the description of transport processes of nanoparticles in the PBPK model, and the challenges in PBPK model development of nanoparticles are delineated and juxtaposed with those encountered in small molecule models. Nanoparticle related, non-nanoparticle-related, and interspecies-scaling methods applied in PBPK modeling are reviewed. In vitro to in vivo extrapolation (IVIVE) methods being a promising computational tool to provide in vivo predictions from the results of in vitro and in silico studies are discussed. Finally, as a recent advancement ML/AI-based approaches and challenges in PBPK modeling in the estimation of ADME parameters and pharmacokinetic (PK) analysis results are introduced.

The impact of pregnancy-related hormonal and physiological changes on antiseizure medications: expert perspective

INTRODUCTION

Epilepsy is a disorder of recurrent, unprovoked seizures affecting approximately 15 million individuals of childbearing potential worldwide. Patients with epilepsy rely on regular daily therapy with antiseizure medications (ASMs). Furthermore, ASMs are also prescribed for other neuropsychiatric indications (e.g. bipolar disorder, pain, migraines) with over 2% of the pregnancies in the United States involving prenatal exposure to ASMs.

AREAS COVERED

ASM concentrations are affected by hormonal and physiological changes in pregnancy, including increases in renal and hepatic blood flow, decreased protein binding, and changes in enzyme activity. Clearance changes typically reverse within a few weeks after delivery. During pregnancy, many ASMs, such as lamotrigine, levetiracetam, and oxcarbazepine, should have serum concentrations monitored and doses increased to maintain the individualized target range for seizure control. ASMs metabolized via glucuronidation, primarily lamotrigine, undergo marked increases in clearance throughout pregnancy, requiring about 3-fold the pre-pregnancy daily dose by delivery. Postpartum, ASM doses are usually decreased over several weeks to prevent drug toxicity.

EXPERT OPINION

In the future, the development of a physiologically-based pharmacokinetic model for various ASMs may enable empiric dose adjustments in pregnancy without the difficulties of frequent therapeutic drug monitoring.

Salivary Therapeutic Monitoring of Buprenorphine in Neonates After Maternal Sublingual Dosing Guided by Physiologically Based Pharmacokinetic Modeling

BACKGROUND

Opioid use disorder (OUD) during pregnancy is associated with high mortality rates and neonatal opioid withdrawal syndrome (NOWS). Buprenorphine, an opioid, is used to treat OUD and NOWS. Buprenorphine active metabolite (norbuprenorphine) can cross the placenta and cause neonatal respiratory depression (EC 50 = 35 ng/mL) at high brain extracellular fluid (bECF) levels. Neonatal therapeutic drug monitoring using saliva decreases the likelihood of distress and infections associated with frequent blood sampling.

METHODS

An adult physiologically based pharmacokinetic model for buprenorphine and norbuprenorphine after intravenous and sublingual administration was constructed, vetted, and scaled to newborn and pregnant populations. The pregnancy model predicted that buprenorphine and norbuprenorphine doses would be transplacentally transferred to the newborns. The newborn physiologically based pharmacokinetic model was used to estimate the buprenorphine and norbuprenorphine levels in newborn plasma, bECF, and saliva after these doses.

RESULTS

After maternal sublingual administration of buprenorphine (4 mg/d), the estimated plasma concentrations of buprenorphine and norbuprenorphine in newborns exceeded the toxicity thresholds for 8 and 24 hours, respectively. However, the norbuprenorphine bECF levels were lower than the respiratory depression threshold. Furthermore, the salivary buprenorphine threshold levels in newborns for buprenorphine analgesia, norbuprenorphine analgesia, and norbuprenorphine hypoventilation were observed to be 22, 2, and 162 ng/mL.

CONCLUSIONS

Using neonatal saliva for buprenorphine therapeutic drug monitoring can facilitate newborn safety during the maternal treatment of OUD using sublingual buprenorphine. Nevertheless, the suitability of using adult values of respiratory depression EC 50 for newborns must be confirmed.

Model-informed drug development in pediatric, pregnancy and geriatric drug development: States of the art and future

The challenges of drug development in pediatric, pregnant and geriatric populations are a worldwide concern shared by regulatory authorities, pharmaceutical companies, and healthcare professionals. Model-informed drug development (MIDD) can integrate and quantify real-world data of physiology, pharmacology, and disease processes by using modeling and simulation techniques to facilitate decision-making in drug development. In this article, we reviewed current MIDD policy updates, reflected on the integrity of physiological data used for MIDD and the effects of physiological changes on the drug PK, as well as summarized current MIDD strategies and applications, so as to present the state of the art of MIDD in pediatric, pregnant and geriatric populations. Some considerations are put forth for the future improvements of MIDD including refining regulatory considerations, improving the integrity of physiological data, applying the emerging technologies, and exploring the application of MIDD in new therapies like gene therapies for special populations.

Utility of life stage-specific chemical risk assessments based on New Approach Methodologies (NAMs)

The safety assessments for chemicals targeted for use or expected to be exposed to specific life stages, including infancy, childhood, pregnancy and lactation, and geriatrics, need to account for extrapolation of data from healthy adults to these populations to assess their human health risk. However, often adequate and relevant toxicity or pharmacokinetic (PK) data of chemicals in specific life stages are not available. For such chemicals, New Approach Methodologies (NAMs), such as physiologically based pharmacokinetic (PBPK) modeling, biologically based dose response (BBDR) modeling, in vitro to in vivo extrapolation (IVIVE), etc. can be used to understand the variability of exposure and effects of chemicals in specific life stages and assess their associated risk. A life stage specific PBPK model incorporates the physiological and biochemical changes associated with each life stage and simulates their impact on the absorption, distribution, metabolism, and elimination (ADME) of these chemicals. In our review, we summarize the parameterization of life stage models based on New Approach Methodologies (NAMs) and discuss case studies that highlight the utility of a life stage based PBPK modeling for risk assessment. In addition, we discuss the utility of artificial intelligence (AI)/machine learning (ML) and other computational models, such as those based on in vitro data, as tools for estimation of relevant physiological or physicochemical parameters and selection of model. We also discuss existing gaps in the available toxicological datasets and current challenges that need to be overcome to expand the utility of NAMs for life stage-specific chemical risk assessment.

Direct-Acting Antiviral Agents in Prevention of Maternal-Fetal Transmission of Hepatitis C Virus in Pregnancy

Prior to the Food and Drug Administration approval of ledipaspavir/sofosbuvir (Harvoni®) in 2014, the treatment of hepatitis C was interferon plus or minus ribavirin. This treatment had low cure rates for hepatitis C virus and was teratogenic and therefore avoided in pregnant patients. Vertical transmission is the most common transmission of hepatitis C in pediatric patients, whereas medical equipment that was not properly cleaned and sterilized, blood products which were not checked (historically), sharing and reusing syringes and needles, and dialysis are the most common forms of hepatitis C transmission in adults. The treatment of pregnant women with direct-acting antivirals is important because the treatment of pediatric patients cannot begin until three years of age and does not always occur prior to the symptom development of hepatitis C. This review article will include glecaprevir/pibrentasvir (Mayvret®), sofosbuvir/velpatasvir (Epclusa®), and sofosbuvir/velpatasvir plus voxilaprevir (Vosevi®). We aim to review the teratogenic risk of direct-acting antivirals as well as currently published clinical trials and ongoing research on direct-acting antiviral hepatitis C treatment in pregnancy in this publication.

Pharmacokinetics and Safety of Remdesivir in Pregnant and Non-Pregnant Women with COVID-19: Results from IMPAACT 2032

BACKGROUND

Pregnant people with COVID-19 experience higher risk for severe disease and adverse pregnancy outcomes, but no pharmacokinetic (PK) data exist to support dosing of COVID-19 therapeutics during pregnancy. We report PK and safety data for intravenous remdesivir in pregnancy.

METHODS

IMPAACT 2032 was a phase IV prospective, open-label, non-randomized opportunistic study of hospitalized pregnant and non-pregnant women receiving intravenous remdesivir as part of clinical care. Intensive PK sampling was performed on infusion days 3, 4, or 5 with collection of plasma and peripheral blood mononuclear cells (PBMCs). Safety data were recorded from first infusion through 4 weeks post-last infusion and at delivery. Geometric mean ratios (GMR) (90% confidence intervals [CI]) of PK parameters between pregnant and non-pregnant women were calculated.

RESULTS

Fifty-three participants initiated remdesivir (25 pregnant; median (IQR) gestational age 27.6 (24.9, 31.0) weeks). Plasma exposures of remdesivir, its two major metabolites (GS-704277 and GS-441524), and the free remdesivir fraction were similar between pregnant and non-pregnant participants. Concentrations of the active triphosphate (GS-443902) in PBMCs increased 2.04-fold (90% CI 1.35, 3.03) with each additional infusion in non-pregnant versus pregnant participants. Three adverse events in non-pregnant participants were related to treatment (one Grade 3; two Grade 2 resulting in treatment discontinuation). There were no treatment-related adverse pregnancy outcomes or congenital anomalies detected.

CONCLUSIONS

Plasma remdesivir PK parameters were comparable between pregnant and non-pregnant women, and no safety concerns were identified based on our limited data. These findings suggest no dose adjustments are indicated for intravenous remdesivir during pregnancy.

Prenatal arsenic metabolite exposure is associated with increased newborn mitochondrial DNA copy number: evidence from a birth cohort study

While mitochondria are susceptible to environmental detriments, little is known about potential associations between arsenic metabolites and mitochondria DNA copy number (mtDNAcn). We attempted to examine whether maternal urinary arsenic metabolite levels in different trimesters were related to neonatal cord blood mtDNAcn. We included 819 mother-newborn pairs embedded in an in-progress birth cohort survey performed from April 2014 to October 2016 in Wuhan, China. We determined maternal urinary arsenic species concentrations in different trimesters. We determined cord blood mtDNAcn using quantitative real-time polymerase chain reaction. In covariate-adjusted models, each one-unit increment of dimethylated arsenic (DMA) and total arsenic (TAs) in the third trimester was related to 8.43% (95% CI 1.13%, 16.26%) and 12.15% (95% CI 4.35%, 20.53%) increases in mtDNAcn, respectively. The dose-response trend with statistical significance was observed across tertiles of DMA and TAs in the third trimester with mtDNAcn (DMA percent changes (%Δ) = 25.60 (95% CI 6.73, 47.82), for the highest vs the lowest tertile (P = 0.02); TAs %Δ = 40.31 (95% CI 19.25, 65.10), for the highest vs the lowest tertile (P = 0.0002)). These findings may prove the relationships between prenatal arsenic species levels and neonatal mitochondrial dysfunction.

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.

Evaluation of Various Approaches to Estimate Transplacental Clearance of Vancomycin for Predicting Fetal Concentrations using a Maternal-Fetal Physiologically Based Pharmacokinetic Model

BACKGROUND

Evaluating drug transplacental clearance is vital for forecasting fetal drug exposure. Ex vivo human placenta perfusion experiments are the most suitable approach for this assessment. Various in silico methods are also proposed. This study aims to compare these prediction methods for drug transplacental clearance, focusing on the large molecular weight drug vancomycin (1449.3 g/mol), using maternal-fetal physiologically based pharmacokinetic (m-f PBPK) modeling.

METHODS

Ex vivo human placenta perfusion experiments, in silico approaches using intestinal permeability as a substitute (quantitative structure property relationship (QSPR) model and Caco-2 permeability in vitro-in vivo correlation model) and midazolam calibration model with Caco-2 scaling were assessed for determining the transplacental clearance (CLPD) of vancomycin. The m-f PBPK model was developed stepwise using Simcyp, incorporating the determined CLPD values as a crucial input parameter for transplacental kinetics.

RESULTS

The developed PBPK model of vancomycin for non-pregnant adults demonstrated excellent predictive performance. By incorporating the CLPD parameterization derived from ex vivo human placenta perfusion experiments, the extrapolated m-f PBPK model consistently predicted maternal and fetal concentrations of vancomycin across diverse doses and distinct gestational ages. However, when the CLPD parameter was derived from alternative prediction methods, none of the extrapolated maternal-fetal PBPK models produced fetal predictions in line with the observed data.

CONCLUSION

Our study showcased that combination of ex vivo human placenta perfusion experiments and m-f PBPK model has the capability to predict fetal exposure for the large molecular weight drug vancomycin, whereas other in silico approaches failed to achieve the same level of accuracy.

Assessing chronic gestational exposure to environmental chemicals in pregnant women: Advancing the co-PBK model

Vulnerable populations, such as pregnant women and their fetuses, confront potential health risks due to exposure to environmental toxic compounds. Computational methods have been popular in assessing chemical exposure to populations, contrasting with traditional cohort studies for human biomonitoring. This study proposes a screening-level approach based on physiologically based kinetic (PBK) modeling to evaluate the steady-state exposure of pregnant women to environmental chemicals throughout pregnancy. To exemplify the modeling application, naphthalene was chosen. Simulation results indicated that maternal fat exhibited significant bioaccumulation potential, with the log-transformed BTF of naphthalene at 0.51 mg kg-1 per mg d-1 in the steady state. The placenta was primarily exposed to 0.83 mg/d naphthalene for a 75.2 kg pregnant woman, considering all exposure routes. In the fetal structure, single-organ fetal PBK modeling estimated a naphthalene exposure of 123.64 mg/d to the entire fetus, while multiple-organ fetal PBK modeling further revealed the bioaccumulation highest in fat tissue. The liver identified as the vital organ for metabolism, kBioT,LiverM was demonstrated with the highest sensitivity among rate constants in the maternal body. Furthermore, the first-order kinetic rate constants related to the placenta and blood were found to impact the distribution process of naphthalene in the fetus, influencing gestational exposure. In conclusion, urgent attention is needed to develop a computational biomonitoring tool for assessing toxic chemical exposure in vulnerable populations.

An Application of a Physiologically Based Pharmacokinetic Approach to Predict Ceftazidime Pharmacokinetics in a Pregnant Population

Physiological changes during pregnancy can alter maternal and fetal drug exposure. The objective of this work was to predict maternal and umbilical ceftazidime pharmacokinetics during pregnancy. Ceftazidime transplacental permeability was predicted from its physicochemical properties and incorporated into the model. Predicted concentrations and parameters from the PBPK model were compared to the observed data. PBPK predicted ceftazidime concentrations in non-pregnant and pregnant subjects of 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 calculated transplacental clearance (0.00137 L/h/mL of placenta volume) predicted an average umbilical cord-to-maternal plasma ratio of 0.7 after the first dose, increasing to about 1.0 at a steady state, which also agrees well with clinical observations. The developed maternal PBPK model adequately predicted the observed exposure and kinetics of ceftazidime in the pregnant population. Using a verified population-based PBPK model provides valuable insights into the disposition of drug concentrations in special individuals that are otherwise difficult to study and, in addition, offers the possibility of supplementing sparse samples obtained in vulnerable populations with additional knowledge, informing the dosing adjustment and study design, and improving the efficacy and safety of drugs in target populations.

Forecasting Fetal Buprenorphine Exposure through Maternal-Fetal Physiologically Based Pharmacokinetic Modeling

Buprenorphine readily crosses the placenta, and with greater prenatal exposure, neonatal opioid withdrawal syndrome (NOWS) likely grows more severe. Current dosing strategies can be further improved by tailoring doses to expected NOWS severity. To allow the conceptualization of fetal buprenorphine exposure, a maternal-fetal physiologically based pharmacokinetic (PBPK) model for sublingual buprenorphine was developed using Simcyp (v21.0). Buprenorphine transplacental passage was predicted from its physicochemical properties. The maternal-fetal PBPK model integrated reduced transmucosal absorption driven by lower salivary pH and induced metabolism observed during pregnancy. Maternal pharmacokinetics was adequately predicted in the second trimester, third trimester, and postpartum period, with the simulated area under the curve from 0 to 12 h, apparent clearance, and peak concentration falling within the 1.25-fold prediction error range. Following post hoc adjustment of the likely degree of individual maternal sublingual absorption, umbilical cord blood concentrations at delivery (n = 21) were adequately predicted, with a geometric mean ratio between predicted and observed fetal concentrations of 1.15 and with 95.2% falling within the 2-fold prediction error range. The maternal-fetal PBPK model developed in this study can be used to forecast fetal buprenorphine exposure and would be valuable to investigate its correlation to NOWS severity.

Supplementing clinical lactation studies with PBPK modeling to inform drug therapy in lactating mothers: Prediction of primaquine exposure as a case example

Evaluating the safety of primaquine (PQ) during breastfeeding requires an understanding of its pharmacokinetics (PKs) in breast milk and its exposure in the breastfed infant. Physiologically-based PK (PBPK) modeling is primed to assess the complex interplay of factors affecting the exposure of PQ in both the mother and the nursing infant. A published PBPK model for PQ describing the metabolism by monoamine oxidase A (MAO-A; 90% contribution) and cytochrome P450 2D6 (CYP2D6; 10%) in adults was applied to predict the exposure of PQ in mothers and their breastfeeding infants. Plasma exposures following oral daily dosing of 0.5 mg/kg in the nursing mothers in a clinical lactation study were accurately captured, including the observed ranges. Reported infant daily doses based on milk data from the clinical study were used to predict the exposure of PQ in breastfeeding infants greater than or equal to 28 days. On average, the predicted exposures were less than or equal to 0.13% of the mothers. Furthermore, in simulations involving neonates less than 28 days, PQ exposures remain less than 0.16% of the mothers. Assuming that MAO-A increases slowly with age, the predicted relative exposure of PQ remains low in neonates (<0.46%). Thus, the findings of our study support the recommendation made by the authors who reported the results of the clinical lactation study, that is, that when put into context of safety data currently available in children, PQ should not be withheld in lactating women as it is unlikely to cause adverse events in breastfeeding infants greater than or equal to 28 days old.

Prenatal phthalate exposure and neurodevelopmental differences in twins at 2 years of age

BACKGROUND

Previous studies of singletons evaluating prenatal phthalate exposure and early neurodevelopment reported mixed results and the associations could be biased by parental, obstetrical, and genetic factors.

METHODS

A co-twin control design was employed to test whether prenatal phthalate exposure was associated with children's neurocognitive development. We collected information from 97 mother-twin pairs enrolled in the Wuhan Twin Birth Cohort between March 2016 and October 2018. Fourteen phthalate metabolites were measured in maternal urine collected at each trimester. Neurodevelopmental differences in twins at the age of two were examined as the outcome of interest. Multiple informant model was used to examine the covariate-adjusted associations of prenatal phthalate exposure with mental development index (MDI) and psychomotor development index (PDI) scores assessed at 2 years of age based on Bayley Scales of Infant Development (Second Edition). This model also helps to identify the exposure window of susceptibility.

RESULTS

Maternal urinary levels of mono-2-ethyl-5-oxohexyl phthalate (MEOHP) (β = 1.91, 95% CI: 0.43, 3.39), mono (2-ethyl-5-hydroxyhexyl) phthalate (MEHHP) (β = 1.56, 95% CI: 0.33, 2.79), and the sum of di-(2-ethylhexyl) phthalate metabolites (∑DEHP) (β = 1.85, 95% CI: 0.39, 3.31) during the first trimester showed the strongest and significant positive associations with intra-twin MDI difference. When stratified with twin chorionicity, the positive associations of monoethyl phthalate (MEP), monoisobutyl phthalate (MiBP), mono-n-butyl phthalate (MBP), monobenzyl phthalate (MBzP), individual DEHP metabolites, and ∑DEHP exposure during pregnancy with intra-twin neurodevelopmental differences were more significant in monochorionic diamniotic (MCDA) twins than those in dichorionic diamniotic (DCDA) twins.

CONCLUSIONS

Neurodevelopmental differences in MCDA twins were strongly associated with prenatal phthalate exposure. Our findings warrant further confirmation in longitudinal studies with larger sample sizes.

Association between prenatal exposure to rare earth elements and the neurodevelopment of children at 24-months of age: A prospective cohort study

The increasing consumption of rare earth elements (REEs) has resulted in a considerable risk of environmental exposure. However, the adverse effects of prenatal REEs exposure on children's neurodevelopment are not yet fully recognized. Therefore, we investigated the individual and joint effects of prenatal exposure to 13 REEs on children's neurocognitive development based on 809 mother-child pairs from a large birth cohort in Wuhan, China. Maternal urinary concentrations of 13 REEs were repeatedly measured by inductively coupled plasma mass spectrometry. Children's neurodevelopment [e.g., mental and psychomotor development index (MDI/PDI)] at 24-months was assessed using Bayley Scales of Infant Development of Chinese Revision. GEE and BKMR models were applied to estimate the individual and joint effects of prenatal REE exposure on child neurodevelopment level. After controlling for typical confounders, we observed that exposure to 9 REEs during the first trimester were significantly associated with decreased MDI scores [βs and 95% confidence intervals (CIs) ranging from -2.24 (-3.86 ∼ -0.63) to -1.44 (-2.26∼ -0.26)], and 7 REEs during third trimester were significantly associated decreased PDI scores [β and 95% CIs ranging from -1.95 (-3.19 ∼ -0.71) to -1.25 (-2.34 ∼ -0.16)]. Higher quantiles of REE mixture in first and third trimester were associated with decreased MDI and PDI score. Thulium, erbium in the first trimester and cerium, lanthanum in the third trimester accounted most importance to joint effects on MDI and PDI, respectively. In conclusion, prenatal exposure to higher concentrations of REEs during the first and third trimester were negative associated with children's neurodevelopment.

Associations of maternal urinary rare earth elements individually and in mixtures with neonatal size at birth

Prenatal rare earth elements (REEs) exposure is linked to unfavorable health consequences. Epidemiologic research on repeated measurements of REEs during gestation correlated with fetal growth is exiguous. Until now, few studies have characterized exposure characteristics of REEs in pregnant women. We aimed to ascertain the characteristics and predictors of REEs exposure over three trimesters among pregnant women and examine the possible effects of prenatal REEs exposure on size at birth. Urinary REEs concentrations exhibited considerable within-subject variation with intraclass correlation coefficients ranging from 0.16 to 0.58. Maternal age, household income, gestational weight gain, passive smoking during pregnancy, parity, and neonatal gender were associated with maternal urinary REEs concentrations. Elevated maternal urinary holmium and thulium concentrations in the 3rd trimester were significantly related to reductions in birth weight. Weighted quantile sum (WQS) regression model identified that urinary REEs mixture in the 3rd trimester were negatively related to birth weight (WQSREEs β = -26.22; 95% confidence interval [CI]: -47.62, -4.82), with holmium (40%) and thulium (24%) receiving the highest weights. Male infants received the most weight (>50%) related to decreased birth weight. This study revealed a significant association between individual and mixture REE exposure in late pregnancy with a reduction in birth weight.

PBPK Modeling Approach to Predict the Behavior of Drugs Cleared by Metabolism in Pregnant Subjects and Fetuses

This study aimed to develop a physiologically based pharmacokinetic (PBPK) model that simulates metabolically cleared compounds' pharmacokinetics (PK) in pregnant subjects and fetuses. This model accounts for the differences in tissue sizes, blood flow rates, enzyme expression levels, plasma protein binding, and other physiological factors affecting the drugs' PK in both the pregnant woman and the fetus. The PBPKPlus™ module in GastroPlus® was used to model the PK of metoprolol, midazolam, and metronidazole for both non-pregnant and pregnant groups. For each of the three compounds, the model was first developed and validated against PK data in healthy non-pregnant volunteers and then applied to predict the PK in the pregnant groups. The model accurately described the PK in both the non-pregnant and pregnant groups and explained well the differences in the plasma concentration due to pregnancy. When available, the fetal plasma concentration, placenta, and fetal tissue concentrations were also predicted reasonably well at different stages of pregnancy. The work described the use of a PBPK approach for drug development and demonstrates the ability to predict differences in PK in pregnant subjects and fetal exposure for metabolically cleared compounds.

A physiologically based toxicokinetic model of P-glycoprotein transporter-mediated placenta perfusion of dexamethasone in the pregnant rat

The present dosage of Dexamethasone (DEX) administered to pregnant women may pose a risk of toxicity to their unborn offspring. We aimed to develop a maternal-fetal physiologically based toxicokinetic (PBTK) model for DEX in pregnant rats, with a specific focus on the role of the P-glycoprotein (P-gp) transporter in placenta perfusion, and finally facilitate the optimization of clinical DEX dosage. We conducted animal experiments to determine DEX concentrations in various rat tissues, and constructed the PBTK model using MATLAB software. Sensitivity analysis was performed to assess input parameters and the model stability, with fold error (FE) values serving as evaluation indices. Our results indicate the successful construction of the PBTK model, with the fitting key parameters such as the absorption rate constant (Ka), intrinsic hepatic clearance (CLh,int) and intrinsic P-gp clearance (CLint,P-gp). The median concentration of DEX in maternal plasma, fetal plasma, fetal lung, and fetal brain were determined, which allowed us to fit the tissue-to-plasma partition coefficients for the fetal lung (Kp,lung,f) and fetal brain (Kp,brain,f). After making adjustments, all calculated FE values were found to be less than 2, demonstrating the acceptability and accuracy of our model's predictions. Our model integrated external literature data and internal animal experimentation to comprehensively evaluate the maternal-fetal PK characteristics of DEX. These findings provide valuable support for the optimization of clinical DEX dosing.

The impact of pregnancy and associated hormones on the pharmacokinetics of Δ9-tetrahydrocannabinol

INTRODUCTION

(-)-Δ9-tetrahydrocannabinol (THC) is the main psychoactive component of cannabis. Cannabis is the most widely used drug of abuse by pregnant individuals, but its maternal-fetal safety is still unclear. The changes in THC disposition during pregnancy may affect THC safety and pharmacology.

AREAS COVERED

This review summarizes the current literature on THC metabolism and pharmacokinetics in humans. It provides an analysis of how hormonal changes during pregnancy may alter the expression of cannabinoid metabolizing enzymes and THC and its metabolite pharmacokinetics. THC is predominately (>70%) cleared by hepatic metabolism to its psychoactive active metabolite, 11-OH-THC by cytochrome P450 (CYP) 2C9 and to other metabolites (<30%) by CYP3A4. Other physiological processes that change during pregnancy and may alter cannabinoid disposition are also reviewed.

EXPERT OPINION

THC and its metabolites disposition likely change during pregnancy. Hepatic CYP2C9 and CYP3A4 are induced in pregnant individuals and in vitro by pregnancy hormones. This induction of CYP2C9 and CYP3A4 is predicted to lead to altered THC and 11-OH-THC disposition and pharmacodynamic effects. More in vitro studies of THC metabolism and induction of the enzymes metabolizing cannabinoids are necessary to improve the prediction of THC pharmacokinetics in pregnant individuals.

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.

Pregnancy-related maternal physiological adaptations and fetal chemical exposure

Prenatal life represents a susceptible window of development during which chemical exposures can permanently alter fetal development, leading to an increased likelihood of disease later in life. Therefore, it is essential to assess exposure in the fetus. However, direct assessment in human fetuses is challenging, so most research measures maternal exposure. Pregnancy induces a range of significant physiological changes in women that may affect chemical metabolism and responses. Moreover, placental function, fetal sex, and pregnancy complications may further modify these exposures. The purpose of this narrative review is to give an overview of major pregnancy-related physiological changes, including placental function and impacts of pregnancy complications, to summarize existing studies assessing chemical exposure in human fetal organs, and to discuss possible interactions between physiological changes and exposures. Our review reveals major knowledge gaps in factors affecting fetal chemical exposure, highlighting the need to develop more sophisticated tools for chemical health risk assessment in fetuses.

Animal-free assessment of developmental toxicity: Combining PBPK modeling with the ReproTracker assay

in vitro screening platforms to assess teratogenic potential of compounds are emerging rapidly. ReproTracker is a human induced pluripotent stem cells (hiPSCs)-based biomarker assay that is shown to identify the teratogenicity potential of new pharmaceuticals and chemicals reliably. In its current state, the assay is limited to identifying the potential teratogenic effects and does not immediately quantify a clinical dose relevant to the exposure of chemicals or drugs observable in mothers or fetuses. The goal of this study was to evaluate whether the ReproTracker assay can be extrapolated in vivo and quantitatively predict developmental toxicity exposure levels of two known human teratogens, thalidomide, and carbamazepine. Here, we utilized Physiologically Based Pharmacokinetic (PBPK) modeling to describe the pharmacokinetic behavior of these compounds and conducted an in vitro to in vivo extrapolation (IVIVE) approach to predict human equivalent effect doses (HEDs) that correspond with in vitro concentrations potentially associated with adverse outcomes in ReproTracker. The HEDs derived from the ReproTracker concentration predicted to cause developmental toxicity were close to the reported teratogenic human clinical doses and the HED derived from the rat or rabbit developmental toxicity study. The ReproTracker derived-HED revealed to be sensitive and protective of humans. Overall, this pilot study demonstrated the importance of integrating PBPK model in extrapolating and assessing developmental toxicity in vitro. The combination of these tools demonstrated that they could improve the safety assessment of drugs and chemicals without animal testing.

Pharmacokinetics and Safety of Group A and B Anti-Tuberculosis Drugs Used in Treatment of Rifampicin-Resistant Tuberculosis during Pregnancy and Post-Partum: A Narrative Review

Recommendations for treatment of rifampicin-resistant tuberculosis (RR-TB) during pregnancy and post-partum now include Group A and B antituberculosis drugs. While pharmacokinetic data for most of these drugs among adults receiving treatment for RR-TB are limited, the data from pregnant patients and their infants are extremely scarce. Existing data suggest that fluoroquinolones, bedaquiline, clofazimine and terizidone may be used safely in pregnancy. Pharmacokinetic exposures, particularly between trimesters, are potentially sub-optimal; however, there is currently no evidence to support dose adjustment during pregnancy. Linezolid poses a potentially serious toxicity risk, particularly as exposures appear to be high in the later stages of pregnancy and post-partum following extended use, but this should be considered alongside the benefits of this extremely effective drug in the treatment of this life-threatening disease. While plenty of questions remain regarding the exposure to Group A and B antituberculosis drugs through breastmilk, existing literature suggests minimal harm to the breastfed infant. Pregnant patients and their infants should be included in therapeutic trials and pharmacokinetic studies of effective antituberculosis drugs.

Application of a physiologically based pharmacokinetic model to predict isoniazid disposition during pregnancy

Pregnancy can increase the risk of latent tuberculosis infection (LTBI) progression to tuberculosis (TB) disease. Isoniazid (INH) is the preferred preventative treatment for LTBI in pregnancy. INH is mainly cleared by N-acetyltransferase 2 (NAT2) but the pharmacokinetics (PK) of INH in different NAT2 phenotypes during pregnancy is not well characterized. To address this knowledge gap, we used physiologically based pharmacokinetic (PBPK) modeling to evaluate NAT2 phenotype-specific effects of pregnancy on INH disposition. A whole-body PBPK model for INH was developed and verified for non-pregnant NAT2 fast (FA), intermediate (IA), and slow (SA) acetylators. Model predictive performance was assessed using a drug-specific model acceptance criterion for mean plasma area under the curve (AUC) and peak plasma concentration (Cmax ), and the absolute average fold error (AAFE) for individual plasma concentrations. The verified model was extended to simulate INH disposition during pregnancy in NAT2 SA, IA, and FA populations. A sensitivity analysis was conducted using the verified PBPK model and known changes in INH disposition during pregnancy to determine whether NAT2 activity changes during pregnancy or other INH clearance pathways are altered. This analysis suggested that NAT2 activity is unchanged while other INH clearance pathways increase by ~80% during pregnancy. The model was applied to explore the effect of pregnancy on INH disposition in two ethnic populations with different NAT2 phenotype distributions and with high TB burden. Our PBPK model can be used to predict INH disposition during pregnancy in diverse populations and expanded to other drugs cleared by NAT2 during pregnancy.

Altered cord blood mitochondrial DNA content and prenatal exposure to arsenic metabolites in low-arsenic areas

While mitochondria are susceptible to environmental detriments, little is known about potential associations between arsenic metabolites and mitochondria DNA copy number (mtDNAcn). We attempted to examine whether arsenic metabolism in different trimesters was related to cord blood mtDNAcn alteration. We included 819 mother-newborn pairs embedded in an in-progress birth cohort survey performed from April 2014 to October 2016 in Wuhan, China. We determined maternal urinary arsenic species concentrations in different trimesters using HPLC-ICPMS. We decided on cord blood mtDNAcn using quantitative real-time polymerase chain reaction. In covariate-adjusted models, each two-fold increment of dimethylated arsenic (DMA) and total arsenic (TAs) in the 3rd trimester were related to 8.43% (95% CI: 1.13%, 16.26%) and 12.15% (95% CI:4.35%, 20.53%) increases in mtDNAcn, respectively. The dose-response trend with statistical significance was observed across tertiles of DMA and TAs in the 3rd trimester with mtDNAcn. These findings may prove the relationships between arsenic species and mitochondrial dysfunction.

The Application of a Physiologically Based Toxicokinetic Model in Health Risk Assessment

Toxicokinetics plays a crucial role in the health risk assessments of xenobiotics. Classical compartmental models are limited in their ability to determine chemical concentrations in specific organs or tissues, particularly target organs or tissues, and their limited interspecific and exposure route extrapolation hinders satisfactory health risk assessment. In contrast, physiologically based toxicokinetic (PBTK) models quantitatively describe the absorption, distribution, metabolism, and excretion of chemicals across various exposure routes and doses in organisms, establishing correlations with toxic effects. Consequently, PBTK models serve as potent tools for extrapolation and provide a theoretical foundation for health risk assessment and management. This review outlines the construction and application of PBTK models in health risk assessment while analyzing their limitations and future perspectives.

Total and Free Blood and Plasma Concentration Changes in Pregnancy for Medicines Highly Bound to Plasma Proteins: Application of Physiologically Based Pharmacokinetic Modelling to Understand the Impact on Efficacy

Free drug concentrations are generally considered the pharmacologically active moiety and are important for cellular diffusion and distribution. Pregnancy-related changes in plasma protein binding and blood partitioning are due to decreases in plasma albumin, alpha-1-acid glycoprotein, and haematocrit; this may lead to increased free concentrations, tissue distribution, and clearance during pregnancy. In this paper we highlight the importance and challenges of considering changes in total and free concentrations during pregnancy. For medicines highly bound to plasma proteins, such as tacrolimus, efavirenz, clindamycin, phenytoin, and carbamazepine, differential changes in concentrations of free drug during pregnancy may be clinically significant and have important implications for dose adjustment. Therapeutic drug monitoring usually relies on the measurement of total concentrations; this can result in dose adjustments that are not necessary when changes in free concentrations are considered. We explore the potential of physiologically based pharmacokinetic (PBPK) models to support the understanding of the changes in plasma proteins binding, using tacrolimus and efavirenz as example drug models. The exposure to either drug was predicted to be reduced during pregnancy; however, the decrease in the exposure to the total tacrolimus and efavirenz were significantly larger than the reduction in the exposure to the free drug. These data show that PBPK modelling can support the impact of the changes in plasma protein binding and may be used for the simulation of free concentrations in pregnancy to support dosing decisions.

Development of a physiologically based toxicokinetic model for lead in pregnant women: The role of bone tissue in the maternal and fetal internal exposure

Epidemiological studies have shown associations between prenatal exposure to lead (Pb) and neurodevelopmental effects in young children. Prenatal exposure is generally characterized by measuring the concentration in the umbilical cord at delivery or in the maternal blood during pregnancy. To assess internal Pb exposure during prenatal life, we developed a pregnancy physiologically based pharmacokinetic (p-PBPK) model that to simulates Pb levels in blood and target tissues in the fetus, especially during critical periods for brain development. An existing Pb PBPK model was adapted to pregnant women and fetuses. Using data from literature, both the additional maternal bone remodeling, that causes Pb release into the blood, and the Pb placental transfers were estimated by Bayesian inference. Additional maternal bone remodeling was estimated to start at 21.6 weeks. Placental transfers were estimated between 4.6 and 283 L.day-1 at delivery with high interindividual variability. Once calibrated, the p-PBPK model was used to simulate fetal exposure to Pb. Internal fetal exposure greatly varies over the pregnancy with two peaks of Pb levels in blood and brain at the end of the 1st and 3rd trimesters. Sensitivity analysis shows that the fetal blood lead levels are affected by the maternal burden of bone Pb via maternal bone remodeling and by fetal bone formation at different pregnancy stages. Coupling the p-PBPK model with an effect model such as an adverse outcome pathway could help to predict the effects on children's neurodevelopment.

Virtual twin for healthcare management

Healthcare is increasingly fragmented, resulting in escalating costs, patient dissatisfaction, and sometimes adverse clinical outcomes. Strategies to decrease healthcare fragmentation are therefore attractive from payer and patient perspectives. In this commentary, a patient-centered smart phone application called Virtual Twin for Healthcare Management (VTHM) is proposed, including its organizational layout, basic functionality, and potential clinical applications. The platform features a virtual twin hub that displays the body and its health data. This is a physiologically based human model that is "virtualized" for the patient based on their unique genetic, molecular, physiological, and disease characteristics. The spokes of the system are a full service and interoperable electronic-health record, accessible to healthcare providers with permission on any device with internet access. Theoretical case studies based on real scenarios are presented to show how VTHM could potentially improve patient care and clinical efficiency. Challenges that must be overcome to turn VTHM into reality are also briefly outlined. Notably, the VTHM platform is designed to operationalize current and future precision medicine initiatives, such as access to molecular diagnostic results, pharmacogenomics-guided prescribing, and model-informed precision dosing.

MIESRA mHealth: Marital satisfaction during pregnancy

The transition of a pregnant woman's role often causes emotional changes that have an impact on marital satisfaction. We develop MIESRA mHealth and evaluate its impact on satisfaction of husband-wife relationship during pregnancy. A quasi-experimental study was conducted on 82 couples of pregnant women and divided into control, single, and paired group. We implemented MIESRA mHealth for four weeks. In the couple group, the wife did mindfulness based on the information in the MIESRA mHealth together with her husband. In a single group, the wife sees the video as an initial guide to doing mindfulness. In the control group, respondents received programme interventions from hospitals which included education and consultation with obstetricians. Husband-wife relationship is evaluated using Compatibility of Husband-and-Wife Relationships / Kesesuaian Hubungan Suami Istri (KHSI) questionnaire and the generalised estimating equations (GEE) was used to analyse the data. The women's KHSI scores in the couple and single intervention groups (β = -7.46, p = 0.002; β = -9.11, p = 0.001) were better than the control group. The husbands' KHSI scores in the paired and individual intervention groups (β = -7.04, p<0.001; β = -3.74, p = 0.024) were better than the control group. Nursing interventions to build emotional bonds between parents and foetuses based on mHealth can be a promising intervention for marital harmony during the perinatal period. MIESRA m-Health is a promising intervention on marital satisfaction during pregnancy and can be implemented as a part of the antenatal care programme to increase marital satisfaction.

Semi-physiological Enriched Population Pharmacokinetic Modelling to Predict the Effects of Pregnancy on the Pharmacokinetics of Cytotoxic Drugs

BACKGROUND AND OBJECTIVE

As a result of changes in physiology during pregnancy, the pharmacokinetics (PK) of drugs can be altered. It is unclear whether under- or overexposure occurs in pregnant cancer patients and thus also whether adjustments in dosing regimens are required. Given the severity of the malignant disease and the potentially high impact on both the mother and child, there is a high unmet medical need for adequate and tolerable treatment of this patient population. We aimed to develop and evaluate a semi-physiological enriched model that incorporates physiological changes during pregnancy into available population PK models developed from non-pregnant patient data.

METHODS

Gestational changes in plasma protein levels, renal function, hepatic function, plasma volume, extracellular water and total body water were implemented in existing empirical PK models for docetaxel, paclitaxel, epirubicin and doxorubicin. These models were used to predict PK profiles for pregnant patients, which were compared with observed data obtained from pregnant patients.

RESULTS

The observed PK profiles were well described by the model. For docetaxel, paclitaxel and doxorubicin, an overprediction of the lower concentrations was observed, most likely as a result of a lack of data on the gestational changes in metabolizing enzymes. For paclitaxel, epirubicin and doxorubicin, the semi-physiological enriched model performed better in predicting PK in pregnant patients compared with a model that was not adjusted for pregnancy-induced changes.

CONCLUSION

By incorporating gestational changes into existing population pharmacokinetic models, it is possible to adequately predict plasma concentrations of drugs in pregnant patients which may inform dose adjustments in this population.

Pharmacokinetics of Antiretroviral Agents in Pregnant Individuals Living With HIV: Current Status and Considerations for Study Design and Interpretation

Determining the appropriate dosing regimens of antiretroviral (ARV) drugs for pregnant individuals living with HIV-1 infection is critical to maximize maternal health and prevent perinatal HIV transmission. Throughout pregnancy, pharmacokinetics (PK) of ARVs can be significantly altered due to physiological, anatomic, and metabolic changes. As such, conducting PK studies of ARVs during pregnancy is crucial to optimize dosing regimens. In this article, we summarize available data, key issues, challenges, and considerations in interpreting results of ARV PK studies in pregnant individuals. Discussion topics include the choice of the reference population (postpartum vs historical control), pregnancy trimester-dependent changes in ARV PK, effects of pregnancy on once- versus twice-daily dosing, factors to consider for ARVs that are administered with a PK booster such as ritonavir and cobicistat, and considerations when evaluating the effects of pregnancy on unbound ARV concentrations. Common approaches for the translation of the results into clinical recommendations and rationales and considerations when making clinical recommendations are summarized. Currently, limited PK data in pregnancy are available with long-acting ARVs. Collection of PK data to characterize the PK profile of long-acting ARVs is an important goal shared by many stakeholders.

Landscape and Regulatory Perspective on Oncology Drugs in Pregnancy

Cancers affecting pregnant women include breast cancer, melanoma, thyroid cancer, cervical cancer, lymphomas, and leukemias. The medical management of cancer during pregnancy with molecularly targeted oncology drugs remains quite challenging, with knowledge gaps about the drugs' safety and efficacy due to exclusion of pregnant women from cancer clinical trials, discontinuation of individuals who become pregnant during clinical trials, and limited information on appropriate dosing of molecularly targeted oncology drugs during pregnancy. Physiological changes occur during pregnancy and may result in alterations in the absorption, distribution, metabolism, and excretion of drugs used in pregnant women. Physiologically based pharmacokinetic modeling that incorporates physiological changes induced by both the cancer disease state and pregnancy has the potential to inform dosing of molecularly targeted oncology drugs for pregnant women, improve our understanding of the pharmacokinetic changes associated with pregnancy in patients with cancer, facilitate the design of potential studies of molecularly targeted oncology drugs in pregnant women to support dosing recommendations, and provide model-informed pharmacokinetic data to support regulatory decision making.

Opportunities for Systems Biology and Quantitative Systems Pharmacology to Address Knowledge Gaps for Drug Development in Pregnancy

Pregnant women are still viewed as therapeutic orphans to the extent that they are avoided as participants in mainstream clinical trials and not considered a priority for targeted drug research despite the fact that many clinical conditions exist during pregnancy for which pharmacotherapy is warranted. Part of the challenge is the uncertain risk potential that pregnant women represent in the absence of timely and costly toxicology and developmental pharmacology studies, which only partly mitigate such risks. Even when clinical trials are conducted in pregnant women, they are often underpowered and absent biomarkers and exclude evaluation across multiple stages of pregnancy where relevant development risk could have been assessed. Quantitative systems pharmacology model development has been proposed as one solution to fill knowledge gaps, make earlier and perhaps more informed risk assessment, and design more informative trials with better recommendations for biomarker and end point selection including design and sample size optimality. Funding for translational research in pregnancy is limited but will fill some of these gaps, especially when joined with ongoing clinical trials in pregnancy that also fill certain knowledge gaps, especially biomarker and end point evaluation across pregnancy states linked to clinical outcomes. Opportunities exist for further advances in quantitative systems pharmacology model development with the inclusion of real-world data sources and complimentary artificial intelligence/machine learning approaches. The successful coordination of the approach reliant on these new data sources will require commitments to share data and a diverse multidisciplinary group that seeks to develop open science models that benefit the entire research community, ensuring that such models can be used with high fidelity. New data opportunities and computational resources are highlighted in an effort to project how these efforts can move forward.

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.

Pharmacokinetic Evaluation in Pregnancy-Current Status and Future Considerations: Workshop Summary

As pregnant individuals have traditionally been excluded from clinical trials, there is a gap in knowledge at the time of drug approval regarding safety, efficacy, and appropriate dosing for most prescription medications used during pregnancy. Physiologic changes in pregnancy can result in changes in pharmacokinetics that can impact safety or efficacy. This highlights the need to foster further research and collection of pharmacokinetic data in pregnancy to ensure appropriate drug dosing in pregnant individuals. Therefore, the US Food and Drug Administration and the University of Maryland Center of Excellence in Regulatory Science and Innovation hosted a workshop on May 16 and 17, 2022, titled "Pharmacokinetic Evaluation in Pregnancy." This is a summary of the workshop proceedings.

The MPRINT Hub Data, Model, Knowledge and Research Coordination Center: Bridging the gap in maternal-pediatric therapeutics research through data integration and pharmacometrics

Maternal and pediatric populations have historically been considered "therapeutic orphans" due to their limited inclusion in clinical trials. Physiologic changes during pregnancy and lactation and growth and maturation of children alter pharmacokinetics (PK) and pharmacodynamics (PD) of drugs. Precision therapy in these populations requires knowledge of these effects. Efforts to enhance maternal and pediatric participation in clinical studies have increased over the past few decades. However, studies supporting precision therapeutics in these populations are often small and, in isolation, may have limited impact. Integration of data from various studies, for example through physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) modeling or bioinformatics approaches, can augment the value of data from these studies, and help identify gaps in understanding. To catalyze research in maternal and pediatric precision therapeutics, the Obstetric and Pediatric Pharmacology and Therapeutics Branch of the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) established the Maternal and Pediatric Precision in Therapeutics (MPRINT) Hub. Herein, we provide an overview of the status of maternal-pediatric therapeutics research and introduce the Indiana University-Ohio State University MPRINT Hub Data, Model, Knowledge and Research Coordination Center (DMKRCC), which aims to facilitate research in maternal and pediatric precision therapeutics through the integration and assessment of existing knowledge, supporting pharmacometrics and clinical trials design, development of new real-world evidence resources, educational initiatives, and building collaborations among public and private partners, including other NICHD-funded networks. By fostering use of existing data and resources, the DMKRCC will identify critical gaps in knowledge and support efforts to overcome these gaps to enhance maternal-pediatric precision therapeutics.

Patient-Centered Care in the Management of Cancer During Pregnancy

The management of cancer during pregnancy requires a patient-centered, multidisciplinary approach to balance maternal and fetal well-being given the rarity of this clinical scenario and lack of substantial data. Involvement of oncology and nononcology medical specialists and ethical, legal, and psychosocial supports, as needed, is instrumental in navigating the complexities of care for this patient population. Critical periods of fetal development and physiological changes in pregnancy must be considered when planning diagnostic and therapeutic approaches during pregnancy. The complexity of symptom recognition and interventional approaches contributes to diagnostic delays of cancers during pregnancy. Ultrasound and whole-body diffusion-weighted magnetic resonance imaging are safe throughout pregnancy. Surgery can be safely performed throughout pregnancy, with the early second trimester preferred for intra-abdominal surgery. Chemotherapy can be safely administered after 12-14 weeks of gestation until 1-3 weeks before the anticipated delivery. Most targeted and immunotherapeutic agents are contraindicated during pregnancy because of limited data. Pelvic radiation during pregnancy is absolutely contraindicated, while if radiation to the upper body is needed, administration should only be considered early in pregnancy. To ensure that the total cumulative fetal exposure to ionizing radiation does not exceed 100 mGy, early inclusion of the radiology team in the care plan is required. Closer prenatal monitoring is recommended for maternal and fetal treatment-related toxicities. Delivery before 37 weeks of gestation should be avoided if possible, and vaginal delivery is preferred unless obstetrically indicated or specific clinical scenarios. Postpartum, breastfeeding should be discussed, and the neonate should receive blood work to assess for acute toxicities with follow-up arranged for long-term monitoring.

A mathematical model of vascular and hemodynamics changes in early and late forms of preeclampsia

Preeclampsia-eclampsia syndrome is a leading cause of maternal mortality. The precise etiology of preeclampsia is still not well-defined and different forms exist, including early and late forms or preeclampsia, which may arise via distinctly different mechanisms. Low-dose aspirin administered at the end of the first trimester in women identified as high risk has been shown to reduce the incidence of early, but not late, preeclampsia; however, current risk factors show only fair predictive capability. There is a pressing need to develop accurate descriptions for the different forms of preeclampsia. This paper presents 1D fluid, solid, growth, and remodeling models for pregnancies complicated with early and late forms of preeclampsia. Simulations affirm a broad set of literature results that early forms of preeclampsia are characterized by elevated uterine artery pulsatility index (UA-PI) and total peripheral resistance (TPR) and lower cardiac output (CO), with modestly increased mean arterial blood pressure (MAP) in the first half of pregnancy, with elevation of TPR and MAP beginning at 20 weeks. Conversely, late forms of preeclampsia are characterized by only slightly elevated UA-PI and normal pre-term TPR, and slightly elevated MAP and CO throughout pregnancy, with increased TPR and MAP beginning after 34 weeks. Results suggest that preexisting arterial stiffness may be elevated in women that develop both early forms and late forms of preeclampsia; however, data that verify these results are lacking in the literature. Pulse wave velocity increases in early- and late-preeclampsia, coincident with increases in blood pressure; however, these increases are mainly due to the strain-stiffening response of larger arteries, rather than arterial remodeling-derived changes in material properties. These simulations affirm that early forms of preeclampsia may be associated with abnormal placentation, whereas late forms may be more closely associated with preexisting maternal cardiovascular factors; simulations also highlight several critical gaps in available data.

PBPK-based dose finding for sildenafil in pregnant women for antenatal treatment of congenital diaphragmatic hernia

Sildenafil is a potent vasodilator and phosphodiesterase type five inhibitor, commercially known as Revatio® and approved for the treatment of pulmonary arterial hypertension. Maternal administration of sildenafil during pregnancy is being evaluated for antenatal treatment of several conditions, including the prevention of pulmonary hypertension in fetuses with congenital diaphragmatic hernia. However, determination of a safe and effective maternal dose to achieve adequate fetal exposure to sildenafil remains challenging, as pregnancy almost always is an exclusion criterion in clinical studies. Physiologically-based pharmacokinetic (PBPK) modelling offers an attractive approach for dose finding in this specific population. The aim of this study is to exploit physiologically-based pharmacokinetic modelling to predict the required maternal dose to achieve therapeutic fetal exposure for the treatment congenital diaphragmatic hernia. A full-PBPK model was developed for sildenafil and N-desmethyl-sildenafil using the Simcyp simulator V21 platform, and verified in adult reference individuals, as well as in pregnant women, taking into account maternal and fetal physiology, along with factors known to determine hepatic disposition of sildenafil. Clinical pharmacokinetic data in mother and fetus were previously obtained in the RIDSTRESS study and were used for model verification purposes. Subsequent simulations were performed relying either on measured values for fetal fraction unbound (fu = 0.108) or on values predicted by the simulator (fu = 0.044). Adequate doses were predicted according to the efficacy target of 15 ng/mL (or 38 ng/mL) and safety target of 166 ng/mL (or 409 ng/mL), assuming measured (or predicted) fu values, respectively. Considering simulated median profiles for average steady state sildenafil concentrations, dosing regimens of 130 mg/day or 150 mg/day (administered as t.i.d.), were within the therapeutic window, assuming either measured or predicted fu values, respectively. For safety reasons, dosing should be initiated at 130 mg/day, under therapeutic drug monitoring. Additional experimental measurements should be performed to confirm accurate fetal (and maternal) values for fu. Additional characterization of pharmacodynamics in this specific population is required and may lead to further optimization of the dosing regimen.

Association between rare earth element exposure during pregnancy and newborn telomere length

Telomere length (TL) is considered a marker of biological aging and lifetime health, and some epidemiological studies report that the environmental exposures may influence TL at birth. We aimed to investigate the associations between prenatal rare earth elements (REE) exposure and newborn TL. A total of 587 mother-newborn pairs were recruited during 2013 to 2015 in Wuhan, China. Maternal urinary concentrations of REE collected during three trimesters were measured by inductively coupled plasma mass spectrometry. Quantitative real-time polymerase chain reaction was used to measure relative cord blood TL. The trimester-specific associations between prenatal REE exposure and cord blood TL were evaluated using multiple informant models. Weighted quantile sum regression was used to estimate the mixture effect of urinary REE on cord blood TL. After adjustment for potential confounders, per doubling of urinary REE (Dy, Yb, Pr, Nd, and Tm) concentrations (μg/g creatinine) during the second trimester was respectively associated with 1.94% (95% CI 0.19%, 3.72%), 2.10% (95% CI 0.31%, 3.92%), 2.11% (95% CI 0.35%, 3.89%), 2.08% (95% CI 0.01%, 4.20%), and 1.38% (95% CI 0.09%, 2.70%) increase in cord blood TL. Furthermore, exposure to the mixture of REE during the second trimester was also significantly associated with increased cord blood TL (percent change 1.20%, 95% CI 0.30%, 2.11%). However, these associations were not statistically significant in the first and third trimesters. This study provides new evidence on the potential effect of prenatal REE exposure on the initial (newborn) setting of offspring's telomere biology. Further epidemiological studies are warranted to confirm our findings.

Associations between exposure to brominated flame retardants and metabolic syndrome and its components in U.S. adults

BACKGROUND

Humans are simultaneously exposed to numerous of environmental brominated flame retardants (BFRs). We aim to explore the overall associations of BFRs mixture on metabolic syndrome (MetS) and its components and further identify significant chemicals.

METHODS

This study included 4641 adults from the National Health and Nutrition Examination Survey (NHANES) in 2007-2016. The weighted logistic regression was conducted to estimate the association of a single BFR exposure with MetS and its components. Meanwhile, the weighted quantile sum (WQS) regression and Bayesian kernel machine regression (BKMR) were adopted to evaluate the overall associations of BFRs mixture on MetS and its components, and to identify significant chemicals. We also evaluated potential associations modified by sex.

RESULTS

In the weighted logistic regression model, PBB153 were positively associated with MetS in a dose-dependent manner (P_trend < 0.05). For its components, increasing quartiles of most BFRs were positively associated with abdominal obesity, hypertriglyceridemia, and low HDL. However, we found no statistically significant associations between BFRs and hypertension and hyperglycemia. WQS analyses found that BFRs mixture was positively associated with MetS (OR: 1.30; 95%CI:1.14, 1.46), abdominal obesity (OR: 1.15; 95%CI:1.03, 1.27), hypertriglyceridemia (OR:1.43; 95%CI:1.19, 1.67), and low HDL (OR: 1.15; 95%CI:1.01, 1.29). BKMR showed associations in a similar direction as WQS for BFRs mixture. For MetS, hypertriglyceridemia and Low HDL, PBB153, PBDE28 and PBDE209 were the most heavily weighting chemicals and had the highest the posterior inclusion probabilities in the WQS and BKMR, respectively. BFRs showed stronger associations of MetS and its components in males than in females.

CONCLUSIONS

The present study suggested exposure to BFRs mixture was positively associated with MetS and its components in adults, and PBB153, PBDE28 and PBDE209 were the significant chemicals. However, prospective cohort studies are still needed to confirm the causal effect between BFRs mixture and MetS.

Physiologically-based pharmacokinetic model to investigate the effect of pregnancy on risperidone and paliperidone pharmacokinetics: Application to a pregnant woman and her neonate

This study aimed to determine the effects of pregnancy and ontogeny on risperidone and paliperidone pharmacokinetics by assessing their serum concentrations in two subjects and constructing a customized physiologically-based pharmacokinetic (PBPK) model. Risperidone and paliperidone serum concentrations were determined in a pregnant woman and her newborn. PBPK models for risperidone and paliperidone in adults, pediatric, and pregnant populations were developed and verified using the Simcyp simulator. These models were then applied to our two subjects, generating their "virtual twins." Effects of pregnancy on both drugs were examined using models with fixed pharmacokinetic parameters. In the neonatal PBPK simulation, 10 different models for estimating the renal function of neonates were evaluated. Risperidone was not detected in the serum of both pregnant woman and her newborn. Maternal and neonatal serum paliperidone concentrations were between 2.05-3.80 and 0.82-1.03 ng/ml, respectively. Developed PBPK models accurately predicted paliperidone's pharmacokinetics, as shown by minimal bias and acceptable precision across populations. The individualized maternal model predicted all observed paliperidone concentrations within the 90% prediction interval. Fixed-parameter simulations showed that CYP2D6 activity largely affects risperidone and paliperidone pharmacokinetics during pregnancy. The Flanders metadata equation showed the lowest absolute bias (mean error: 22.3% ± 6.0%) and the greatest precision (root mean square error: 23.8%) in predicting paliperidone plasma concentration in the neonatal population. Our constructed PBPK model can predict risperidone and paliperidone pharmacokinetics in pregnant and neonatal populations, which could help with precision dosing using the PBPK model-informed approach in special populations.

Patterns of Medication Use and Their Determinants in Pregnancy among Women Admitted to the Obstetrics Wards of a Tertiary Care Hospital: A Cross-Sectional Study: Patterns of Medication Use and Their Determinants in Pregnancy

Background

To assess the patterns and factors affecting medication use during antenatal and perinatal periods and to examine maternal and fetal outcomes among pregnant women admitted to a tertiary care hospital in a developing country.

Methods

A cross-sectional study was conducted in the obstetrics wards from 2017 to 2019. Data on patient demographics, co-existent medical conditions, medications, and patient outcomes were collected. Descriptive statistics were used to analyze baseline data, chi-square test was used for categorical variables, and multivariate logistic regression was used for factors influencing drug prescription.

Results

Out of 442 pregnant women, 56% were primigravida with a mean age of 24.7 ± 3.9 years. Approximately 32% experienced at least one disease condition during pregnancy; hypothyroidism (9.7%) was the commonest. The mean number of medications was 2.7 and 38.9% received drugs for a disease condition. Antimicrobials (24.5%) were the commonest drug class. Maternal age of over 25 [(OR (CI): 1.508 (1.191–2.716) ( p = .005)] and maternal illness [OR (CI) 2.934 (1.8–4.7) ( p = .00)] were identified as factors affecting drug prescription. Approximately 39.8% of deliveries were cesarean. Of the newborns, 12.6% had low birth weight, 9.2% were admitted to the newborn intensive care unit, and 14.9% were premature.

Conclusions

Most patients were primigravida and under 25 years. Antimicrobials were the most prescribed drug class. Maternal age over 25 years and maternal illness were identified as the factors affecting medication use. The prevalence of cesareans and prematurity was similar to previous studies.

A simple LC-MS/MS method for the simultaneous quantification of drug metabolic enzymes

OBJECTIVE

The aim of this study is to develop a LC-MS/MS method for the quantitation of seven cytochrome P450 (CYP450) enzymes.

METHODS

A high-performance liquid chromatography-tandem mass spectrometry method was developed using multiple reaction monitoring mode with positive electrospray ionization. The method was validated with selectivity, linearity, stability, accuracy and precious. In addition, the abundance of seven CYP450 enzymes in human liver microsomes and CYP3A4 in placenta were determined using the current method.

RESULTS

The linear range for CYP1A2, CYP2B6 and CYP2C8 was 0.036-3.6 nM and for CYP2C9, CYP2C19, CYP2D6 and CYP3A4 was 0.090-9.0 nM. No interference was found between the blank matrix and each specific peptides. The accuracy and precious results were in accord with the requirement of analytical methods for biological samples in Chinese Pharmacopoeia. In addition, the peptides were stable under current stability conditions. The content of CYP3A4 in placenta and the seven CYP450 enzymes in human liver microsomes were accurately quantified.

CONCLUSION

The developed method is sensitive and specific and can be applied to the quantification of enzymes abundance in different human derived samples like placenta and liver microsomes.

Evaluation of Bisphenol A in Pregnant Women from 10 Caribbean Countries

Bisphenol A (BPA), a phenolic chemical incorporated into many plastic products, has been found to act as an endocrine disruptor that potentially is linked to adverse neurodevelopmental outcomes. Prenatal BPA concentration levels were assessed in 10 English-speaking Caribbean countries by randomly selecting 15 maternal urine samples from approximately 50 pregnant women samples collected in each island and then comparing the findings with comparable data from Canada and the U.S. BPA was detected in all samples ranging from a low geometric mean of 1.46 μg/L (St. Lucia) to a high of 4.88 μg/L (St. Kitts & Nevis). All of the Caribbean islands sampled had geometric mean concentration levels that were higher than those recorded in two Canadian biomonitoring surveys (1.26 μg/L and 0.80 μg/L) and the U.S. NHANES survey (1.39 μg/L). This first biomonitoring survey of BPA concentration levels in maternal urine samples taken from Caribbean countries clearly points to the need for Caribbean governments and public health officials to first engage in legislative and regulatory efforts to ban or minimize the importation and use of BPA products used the Caribbean and, second, to continue to conduct biomonitoring surveys so as to ensure that these laws and regulations are indeed leading to a decrease of BPA concentrations in Caribbean populations.

Predicting fetal exposure of crizotinib during pregnancy: Combining human ex vivo placenta perfusion data with physiologically-based pharmacokinetic modeling

Commercially available physiologically-based pharmacokinetic (PBPK) modeling platforms increasingly allow estimations of fetal exposure to xenobiotics. We aimed to explore a physiology-based approach in which literature data from ex vivo placenta perfusion studies are used to parameterize Simcyp's pregnancy-PBPK (p-PBPK) model, taking crizotinib as an example. First, a physiologically-based semi-mechanistic placenta (PBMP) model was developed in MATLAB to analyze placenta perfusion data of crizotinib. Mixed-effects modeling was performed to derive intrinsic unbound clearance values across the maternal-placental barrier and fetal-placental barrier. Values were then used for parameterization of the p-PBPK model. The PBMP model adequately described the perfusion data. Clearance was estimated to be 71 mL/min and 535 mL/min for the maternal placental uptake and efflux, and 8 mL/min and 163 mL/min for fetal placental uptake and efflux, respectively. For oral dosing of 250 mg twice daily, p-PBPK modeling predicted a C_max and AUC_0-τ of 0.08 mg/L and 0.78 mg/L*h in the umbilical vein at steady-state, respectively. In placental tissue, a C_max of 5.04 mg/L was predicted. In conclusion, PBMP model-based data analysis and the associated p-PBPK modeling approach illustrate how ex vivo placenta perfusion data may be used for fetal exposure predictions.

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.

Optimizing Maternal Nutrition: The Importance of a Tailored Approach

Improving nutritional status during pregnancy is a global interest. Frequently, women either fail to meet or exceed nutrient recommendations. Current strategies to improve maternal nutrition focus on a "one-size-fits-all" approach and fail to consider individual factors that affect the mother's overall nutritional status. The objectives of this review were to determine the importance of key nutrients for optimal maternal and fetal health, to explore to what extent current recommendations consider individual factors, and to explore novel strategies to close the gap between current guidelines and real-world challenges through more personalized approaches. This review intercalated different nutritional guidelines and recent scientific publications and research initiatives related to maternal nutrition. Based on that, an overview of current recommendations, challenges related to present approaches, and perspectives for future directions are described. Current guidelines are not optimally supporting adequate nutrient intake and health of expectant mothers and their offspring. Existing recommendations are not consistent and do not sufficiently take into account how interindividual variation leads to differences in nutrient status. Personalized nutrition offers women the opportunity to improve their health by using strategies that are tailored to their unique nutritional needs. Such strategies can include personalized supplementation, holistic lifestyle interventions, digital and application-based technologies, and dietary assessment through blood biomarker and genetic analysis. However, these approaches warrant further investigation and optimization. More personalized approaches have the potential to optimize mothers' and their offspring's health outcomes more appropriately to their nutritional needs before, during, and after pregnancy. Moving away from a generalized "one-size-fits-all" approach can be achieved through a variety of means. Future aims should be to provide supporting evidence to create customized subpopulation-based or individualized recommendations, improve nutrition education, and develop novel approaches to improve adherence to dietary and lifestyle interventions.