Physiologically Based Pharmacokinetic Modeling in Pregnancy: A Systematic Review of Published Models

Physiologically Based Pharmacokinetic modelling of drugs in pregnancy: A mini-review on availability and limitations

Physiologically based pharmacokinetic (PBPK) modelling in pregnancy is a relatively new approach that is increasingly being used to assess drug systemic exposure in pregnant women to potentially inform dosing adjustments. Physiological changes throughout pregnancy are incorporated into mathematical models to simulate drug disposition in the maternal and fetal compartments as well as the transfer of drugs across the placenta. This mini-review gathers currently available pregnancy PBPK models for drugs commonly used during pregnancy. In addition, information about the main PBPK modelling platforms used, metabolism pathways, drug transporters, data availability and drug labels were collected. The aim of this mini-review is to provide a concise overview, demonstrate trends in the field, highlight understudied areas and identify current gaps of PBPK modelling in pregnancy. Possible future applications of this PBPK approach are discussed from a clinical, regulatory and industry perspective.

Impact of Pregnancy on the Pharmacokinetics and Metabolism of Nicotinamide in Humans

In pre-eclampsia models, nicotinamide (NAM) has protective effects in pre-eclampsia and is being evaluated as a therapeutic nutraceutical in clinical studies. NAM undergoes extensive hepatic metabolism by NAM N-methyltransferase to methylnicotinamide (MNA), which is subsequently metabolized to methyl-2-pyridone-5-carboxamide (M2PY) by aldehyde oxidase. However, the pharmacokinetics of NAM and its major metabolites has never been studied in pregnant individuals. Blood samples were collected before and 1, 2, 4, 8, and 24 hours after single 1 g oral NAM dose in healthy pregnant (gestational age 24-33 weeks) and nonpregnant female volunteers (n = 6/group). Pooled urine was collected from 0 to 8 hours. NAM, MNA, and M2PY area under the concentration-time curve (AUC) data were analyzed by noncompartmental analysis. No difference in the plasma AUC0→24 of NAM (median (25%-75%): 463 (436-576) vs. 510 (423, 725) μM*hour, P = 0.430) and its intermediate metabolite MNA (89.1 (60.4, 124.4) vs. 83.8 (62.7, 93.7) μM*hour, P = 0.515) was observed in pregnant and nonpregnant volunteers, respectively; however, the terminal metabolite M2PY AUC0 → 24 was significantly lower in pregnant individuals (218 (188, 254) vs. 597 (460, 653) μM*hour, P < 0.001). NAM renal clearance (CLR ; P = 0.184), MNA CLR (P = 0.180), and total metabolite formation clearance (P = 0.405) did not differ across groups; however, M2PY CLR was significantly higher in pregnant individuals (10.5 (9.3-11.3) vs. 7.5 (6.4-8.5) L/h, P = 0.002). These findings demonstrate that the PK of NAM and systemic exposure to its intermediate metabolite MNA are not significantly altered during pregnancy, and systemic exposure to NAM's major metabolite M2PY was reduced during pregnancy due to increased renal elimination.

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.

Pregnancy related hormones increase CYP3A mediated buprenorphine metabolism in human hepatocytes: a comparison to CYP3A substrates nifedipine and midazolam

Introduction: Pregnancy increases the clearance of CYP3A4 substrate drugs and pregnancy-related hormones (PRHs) induce hepatic CYP3A4 expression and metabolism. However, it remains unclear to what extent the magnitude of PRH-evoked changes in hepatic CYP3A metabolism varies across multiple substrates. This study quantified the impact of PRHs on CYP3A protein concentrations and buprenorphine metabolism in human hepatocytes, and compared the magnitude of these effects to nifedipine and midazolam metabolism. Methods: Sandwich-cultured human hepatocytes (SCHH) from female donors were exposed to PRHs, administered in combination across a range of physiologically relevant concentrations, for 72 h. Absolute protein concentrations of CYP3A4, CYP3A5, and CYP3A7 in SCHH membrane fractions were quantified by nanoLC-MS/MS, and norbuprenorphine (nor-BUP), dehydro-nifedipine (dehydro-NIF), and 1-hydroxy-midazolam (1-OH-MDZ) formation was evaluated. Results: Compared to control, PRH exposure increased CYP3A4, CYP3A7, and total CYP3A protein concentrations, but not CYP3A5 concentrations, and increased nor-BUP, dehydro-NIF, and 1-OH-MDZ formation in a concentration-dependent manner. The formation of nor-BUP, dehydro-NIF, and 1-OH-MDZ each positively correlated with PRH-mediated changes in total CYP3A protein concentrations. The PRH-evoked increase in nor-BUP formation was evident in all donors; however, the PRH induction of dehydro-NIF and 1-OH-MDZ formation was diminished in a hepatocyte donor with high basal CYP3A5 expression. Discussion: These findings demonstrate that PRHs increase buprenorphine, nifedipine, and midazolam metabolism in SCHH via induction of CYP3A4 and total CYP3A protein concentrations, and the magnitude of these effects vary across hepatocyte donors in a substrate-specific manner. These data provide insight into the contribution of PRH induction of CYP3A4 metabolism to increased buprenorphine clearance during pregnancy.

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.

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.

Considering developmental neurotoxicity in vitro data for human health risk assessment using physiologically-based kinetic modeling: deltamethrin case study

Developmental neurotoxicity (DNT) is a potential hazard of chemicals. Recently, an in vitro testing battery (DNT IVB) was established to complement existing rodent in vivo approaches. Deltamethrin (DLT), a pyrethroid with a well-characterized neurotoxic mode of action, has been selected as a reference chemical to evaluate the performance of the DNT IVB. The present study provides context for evaluating the relevance of these DNT IVB results for the human health risk assessment of DLT by estimating potential human fetal brain concentrations after maternal exposure to DLT. We developed a physiologically based kinetic (PBK) model for rats which was then translated to humans considering realistic in vivo exposure conditions (acceptable daily intake [ADI] for DLT). To address existing uncertainties, we designed case studies considering the most relevant drivers of DLT uptake and distribution. Calculated human fetal brain concentrations were then compared with the lowest benchmark concentration achieved in the DNT IVB. The developed rat PBK model was validated on in vivo rat toxicokinetic data of DLT over a broad range of doses. The uncertainty based case study evaluation confirmed that repeated exposure to DLT at an ADI level would likely result in human fetal brain concentrations far below the in vitro benchmark. The presented results indicate that DLT concentrations in the human fetal brain are highly unlikely to reach concentrations associated with in vitro findings under realistic exposure conditions. Therefore, the new in vitro DNT results are considered to have no impact on the current risk assessment approach.

Mechanistic modeling of ophthalmic, nasal, injectable, and implant generic drug products: A workshop summary report

For approval, a proposed generic drug product must demonstrate it is bioequivalent (BE) to the reference listed drug product. For locally acting drug products, conventional BE approaches may not be feasible because measurements in local tissues at the sites of action are often impractical, unethical, or cost-prohibitive. Mechanistic modeling approaches, such as physiologically-based pharmacokinetic (PBPK) modeling, may integrate information from drug product properties and human physiology to predict drug concentrations in these local tissues. This may allow clinical relevance determination of critical drug product attributes for BE assessment during the development of generic drug products. In this regard, the Office of Generic Drugs of the US Food and Drug Administration has recently established scientific research programs to accelerate the development and assessment of generic products by utilizing model-integrated alternative BE approaches. This report summarizes the presentations and panel discussion from a public workshop that provided research updates and information on the current state of the use of PBPK modeling approaches to support generic product development for ophthalmic, injectable, nasal, and implant drug products.

Physiologically-based pharmacokinetic modeling of remdesivir and its metabolites in pregnant women with COVID-19

Pregnant individuals are at high risk for severe illness from COVID-19, and there is an urgent need to identify safe and effective therapeutics for this population. Remdesivir (RDV) is a SARS-CoV-2 nucleotide analog RNA polymerase inhibitor. Limited RDV pharmacokinetic (PK) and safety data are available for pregnant women receiving RDV. The aims of this study were to translate a previously published nonpregnant adult physiologically based PK (PBPK) model for RDV to pregnancy and evaluate model performance with emerging clinical PK data in pregnant women with COVID-19. The pregnancy model was built in the Open Systems Pharmacology software suite (Version 10) including PK-Sim® and MoBi® with pregnancy-related changes of relevant enzymes applied. PK were predicted in a virtual population of 1000 pregnant subjects, and prediction results were compared with in vivo PK data from the International Maternal, Pediatric, Adolescent AIDS Clinical Trials (IMPAACT) Network  2032 study. The developed PBPK model successfully captured RDV and its metabolites' plasma concentrations during pregnancy. The ratios of prediction versus observation for RDV area under the curve from time 0 to infinity (AUC0-∞ ) and maximum concentration (Cmax ) were 1.61 and 1.17, respectively. For GS-704277, the ratios of predicted versus observed were 0.94 for AUC0-∞ and 1.20 for Cmax . For GS-441524, the ratios of predicted versus observed were 1.03 for AUC0-24 , 1.05 for Cmax , and 1.07 for concentrations at 24 h. All predictions of AUC and Cmax for RDV and its metabolites were within a twofold error range, and about 60% of predictions were within a 10% error range. These findings demonstrate the feasibility of translating PBPK models to pregnant women to potentially guide trial design, clinical decision making, and drug development.

Evaluation of a rapid, generic human gestational dose model

Chemical risk assessment considers potentially susceptible populations including pregnant women and developing fetuses. Humans encounter thousands of chemicals in their environments, few of which have been fully characterized. Toxicokinetic (TK) information is needed to relate chemical exposure to potentially bioactive tissue concentrations. Observational data describing human gestational exposures are unavailable for most chemicals, but physiologically based TK (PBTK) models estimate such exposures. Development of chemical-specific PBTK models requires considerable time and resources. As an alternative, generic PBTK approaches describe a standardized physiology and characterize chemicals with a set of standard physical and TK descriptors - primarily plasma protein binding and hepatic clearance. Here we report and evaluate a generic PBTK model of a human mother and developing fetus. We used a published set of formulas describing the major anatomical and physiological changes that occur during pregnancy to augment the High-Throughput Toxicokinetics (httk) software package. We simulated the ratio of concentrations in maternal and fetal plasma and compared to literature in vivo measurements. We evaluated the model with literature in vivo time-course measurements of maternal plasma concentrations in pregnant and non-pregnant women. Finally, we prioritized chemicals measured in maternal serum based on predicted fetal brain concentrations. This new model can be used for TK simulations of 859 chemicals with existing human-specific in vitro TK data as well as any new chemicals for which such data become available. This gestational model may allow for in vitro to in vivo extrapolation of point of departure doses relevant to reproductive and developmental toxicity.

Impact of pregnancy related hormones on drug metabolizing enzyme and transport protein concentrations in human hepatocytes

Pregnancy alters the disposition and exposure to multiple drugs indicated for pregnancy-related complications. Previous in vitro studies have shown that pregnancy-related hormones (PRHs) alter the expression and function of certain cytochrome P450s (CYPs) in human hepatocytes. However, the impact of PRHs on hepatic concentrations of non-CYP drug-metabolizing enzymes (DMEs) and transport proteins remain largely unknown. In this study, sandwich-cultured human hepatocytes (SCHH) from five female donors were exposed to vehicle or PRHs (estrone, estradiol, estriol, progesterone, cortisol, and placental growth hormone), administered individually or in combination, across a range of physiologically relevant PRH concentrations for 72 h. Absolute concentrations of 33 hepatic non-CYP DMEs and transport proteins were quantified in SCHH membrane fractions using a quantitative targeted absolute proteomics (QTAP) isotope dilution nanoLC-MS/MS method. The data revealed that PRHs altered the absolute protein concentration of various DMEs and transporters in a concentration-, isoform-, and hepatocyte donor-dependent manner. Overall, eight of 33 (24%) proteins exhibited a significant PRH-evoked net change in absolute protein concentration relative to vehicle control (ANOVA p &lt; 0.05) across hepatocyte donors: 1/11 UGTs (9%; UGT1A4), 4/6 other DMEs (67%; CES1, CES2, FMO5, POR), and 3/16 transport proteins (19%; OAT2, OCT3, P-GP). An additional 8 (24%) proteins (UGT1A1, UGT2B4, UGT2B10, FMO3, OCT1, MRP2, MRP3, ENT1) exhibited significant PRH alterations in absolute protein concentration within at least two individual hepatocyte donors. In contrast, 17 (52%) proteins exhibited no discernable impact by PRHs either within or across hepatocyte donors. Collectively, these results provide the first comprehensive quantitative proteomic evaluation of PRH effects on non-CYP DMEs and transport proteins in SCHH and offer mechanistic insight into the altered disposition of drug substrates cleared by these pathways during pregnancy.

Maternal-Fetal Drug Development: An Industry Perspective

Medicines and vaccines prescribed to pregnant women often have not had pregnant women or lactating women included in clinical trials and products are often not approved by regulatory agencies for use in pregnant women. As a result, practitioners may need to prescribe medicines and give vaccines to this special population with limited drug efficacy and safety information available. Multiple regulatory guidance documents regarding the development of medications for pregnant and lactating women have been developed to encourage drug development and the investigation of medicines and vaccines used in this population. However, clinical, regulatory, ethical, and drug development challenges are encountered when designing clinical trials that include pregnant women and their fetuses, in which innovative methods and trial designs are essential. This article provides an overview of an industry perspective on maternal–fetal drug development that includes a review of the regulatory landscape for developing medicines for pregnant women and their fetuses, trial designs that include pregnant women, identification of gaps and challenges, and strategies for potential maternal–fetal drug development considerations for the future development of medicines and vaccines for pregnant women. Early involvement and discussion of drug and vaccine products with multiple stakeholders, including therapeutic experts, patients, physicians, and regulators, is encouraged to optimize the development of safe and effective medicines and vaccines for pregnant women and their fetuses.

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.

Improving Development of Drug Treatments for Pregnant Women and the Fetus

The exclusion of pregnant populations, women of reproductive age, and the fetus from clinical trials of therapeutics is a major global public health issue. It is also a problem of inequity in medicines development, as pregnancy is a protected characteristic. The current regulatory requirements for drugs in pregnancy are being analyzed by a number of agencies worldwide. There has been considerable investment in developing expertise in pregnancy clinical trials (for the pregnant person and the fetus) such as the Obstetric-Fetal Pharmacology Research Centers funded by the National Institute of Child Health and Human Development. Progress has also been made in how to define and grade clinical trial safety in pregnant women, the fetus, and neonate. Innovative methods to model human pregnancy physiology and pharmacology using computer simulations are also gaining interest. Novel ways to assess fetal well-being and placental function using magnetic resonance imaging, computerized cardiotocography, serum circulating fetoplacental proteins, and mRNA may permit better assessment of the safety and efficacy of interventions in the mother and fetus. The core outcomes in women’s and newborn health initiative is facilitating the consistent reporting of data from pregnancy trials. Electronic medical records integrated with pharmacy services should improve the strength of pharmacoepidemiologic and pharmacovigilance studies. Incentives such as investigational plans and orphan disease designation have been taken up for obstetric, fetal, and neonatal diseases. This review describes the progress that is being made to better understand the extent of the problem and to develop applicable solutions.

Prediction of Maternal and Fetal Doravirine Exposure by Integrating Physiologically Based Pharmacokinetic Modeling and Human Placenta Perfusion Experiments

Background and Objective

Doravirine is currently not recommended for pregnant women living with human immunodeficiency virus because efficacy and safety data are lacking. This study aimed to predict maternal and fetal doravirine exposure by integrating human placenta perfusion experiments with pregnancy physiologically based pharmacokinetic (PBPK) modeling.

Methods

Ex vivo placenta perfusions were performed in a closed–closed configuration, in both maternal-to-fetal and fetal-to-maternal directions (n = 8). To derive intrinsic placental transfer parameters from perfusion data, we developed a mechanistic placenta model. Next, we developed a maternal and fetal full-body pregnancy PBPK model for doravirine in Simcyp, which was parameterized with the derived intrinsic placental transfer parameters to predict in vivo maternal and fetal doravirine exposure at 26, 32, and 40 weeks of pregnancy. The predicted total geometric mean (GM) trough plasma concentration (C_trough) values were compared with the target (0.23 mg/L) derived from in vivo exposure–response analysis.

Results

A decrease of 55% in maternal doravirine area under the plasma concentration–time curve (AUC)_0–24h was predicted in pregnant women at 40 weeks of pregnancy compared with nonpregnant women. At 26, 32, and 40 weeks of pregnancy, predicted maternal total doravirine GM C_trough values were below the predefined efficacy target of 0.23 mg/L. Perfusion experiments showed that doravirine extensively crossed the placenta, and PBPK modeling predicted considerable fetal doravirine exposure.

Conclusion

Substantially reduced maternal doravirine exposure was predicted during pregnancy, possibly resulting in impaired efficacy. Therapeutic drug and viral load monitoring are advised for pregnant women treated with doravirine. Considerable fetal doravirine exposure was predicted, highlighting the need for clinical fetal safety data.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40262-022-01127-0.

Physiologically Based Pharmacokinetic Modeling in Pregnant Women Suggests Minor Decrease in Maternal Exposure to Olanzapine

Pregnancy is accompanied by significant physiological changes that might affect the in vivo drug disposition. Olanzapine is prescribed to pregnant women with schizophrenia, while its pharmacokinetics during pregnancy remains unclear. This study aimed to develop a physiologically based pharmacokinetic (PBPK) model of olanzapine in the pregnant population. With the contributions of each clearance pathway determined beforehand, a full PBPK model was developed and validated in the non-pregnant population. This model was then extrapolated to predict steady-state pharmacokinetics in the three trimesters of pregnancy by introducing gestation-related alterations. The model adequately simulated the reported time-concentration curves. The geometric mean fold error of Cmax and AUC was 1.14 and 1.09, respectively. The model predicted that under 10 mg daily dose, the systematic exposure of olanzapine had minor changes (less than 28%) throughout pregnancy. We proposed that the reduction in cytochrome P4501A2 activity is counteracted by the induction of other enzymes, especially glucuronyltransferase1A4. In conclusion, the PBPK model simulations suggest that, at least at the tested stages of pregnancy, dose adjustment of olanzapine can hardly be recommended for pregnant women if effective treatment was achieved before the onset of pregnancy and if fetal toxicity can be ruled out.

A review of pregnancy-induced changes in opioid pharmacokinetics, placental transfer, and fetal exposure: Towards fetomaternal physiologically-based pharmacokinetic modeling to improve the treatment of neonatal opioid withdrawal syndrome

Physiologically-based pharmacokinetic (PBPK) modeling has emerged as a useful tool to study pharmacokinetics (PK) in special populations, such as pregnant women, fetuses, and newborns, where practical hurdles severely limit the study of drug behavior. PK in pregnant women is variable and everchanging, differing greatly from that in their nonpregnant female and male counterparts typically enrolled in clinical trials. PBPK models can accommodate pregnancy-induced physiological and metabolic changes, thereby providing mechanistic insights into maternal drug disposition and fetal exposure. Fueled by the soaring opioid epidemic in the United States, opioid use during pregnancy continues to rise, leading to an increased incidence of neonatal opioid withdrawal syndrome (NOWS). The severity of NOWS is influenced by a complex interplay of extrinsic and intrinsic factors, and varies substantially between newborns, but the extent of prenatal opioid exposure is likely the primary driver. Fetomaternal PBPK modeling is an attractive approach to predict in utero opioid exposure. To facilitate the development of fetomaternal PBPK models of opioids, this review provides a detailed overview of pregnancy-induced changes affecting the PK of commonly used opioids during gestation. Moreover, the placental transfer of these opioids is described, along with their disposition in the fetus. Lastly, the implementation of these factors into PBPK models is discussed. Fetomaternal PBPK modeling of opioids is expected to provide improved insights in fetal opioid exposure, which allows for prediction of postnatal NOWS severity, thereby opening the way for precision postnatal treatment of these vulnerable infants.

The impact of pregnancy on antihypertensive drug metabolism and pharmacokinetics: current status and future directions

INTRODUCTION

Hypertensive disorders of pregnancy (HDP) are rising in prevalence, and increase risk of adverse maternal and fetal outcomes. Physiologic changes occur during pregnancy that alter drug pharmacokinetics. However, antihypertensive drugs lack pregnancy-specific dosing recommendations due to critical knowledge gaps surrounding the extent of gestational changes in antihypertensive drug pharmacokinetics and underlying mechanisms.

AREAS COVERED

This review (1) summarizes currently recommended medications and dosing strategies for non-emergent HDP treatment, (2) reviews and synthesizes existing literature identified via a comprehensive Pubmed search evaluating gestational changes in the maternal pharmacokinetics of commonly prescribed HDP drugs (notably labetalol and nifedipine), and (3) offers insight into the metabolism and clearance mechanisms underlying altered HDP drug pharmacokinetics during pregnancy. Remaining knowledge gaps and future research directions are summarized.

EXPERT OPINION

A series of small pharmacokinetic studies illustrate higher oral clearance of labetalol and nifedipine during pregnancy. Pharmacokinetic modeling and preclinical studies suggest these effects are likely due to pregnancy-associated increases in hepatic UGT1A1- and CYP3A4-mediated first-pass metabolism and lower bioavailability. Accordingly, higher and/or more frequent doses may be needed to lower blood pressure during pregnancy. Future research is needed to address various evidence gaps and inform the development of more precise antihypertensive drug dosing strategies.

Model-Informed Dose Optimization in Pregnancy

Pregnancy is associated with several physiological changes that can alter the pharmacokinetics (PK) and pharmacodynamics of drugs. These may require dosing changes in pregnant women to achieve drug exposures comparable to the nonpregnant population. There is, however, limited information available on the PK and pharmacodynamics of drugs used during pregnancy. Practical difficulties in performing PK studies and potential liability issues are often the reasons for the availability of limited information. Over the past several years, there has been a rapid development in the application of various modeling strategies such as population PK and physiologically based PK modeling to provide guidance on drug dosing in this special patient population. Population PK models rely on measured PK data, whereas physiologically based PK models integrate physiological, preclinical, and clinical data to quantify changes in PK of drugs in various patient populations. These modeling strategies offer a promising approach to identify the drugs with PK changes during pregnancy and guide dose adjustment in pregnant women. This review focuses on PBPK modeling to guide drug therpay in pregnancy.

The Role of the 3Rs for Understanding and Modeling the Human Placenta

Modeling the physiology of the human placenta is still a challenge, despite the great number of scientific advancements made in the field. Animal models cannot fully replicate the structure and function of the human placenta and pose ethical and financial hurdles. In addition, increasingly stricter animal welfare legislation worldwide is incentivizing the use of 3R (reduction, refinement, replacement) practices. What efforts have been made to develop alternative models for the placenta so far? How effective are they? How can we improve them to make them more predictive of human pathophysiology? To address these questions, this review aims at presenting and discussing the current models used to study phenomena at the placenta level: in vivo, ex vivo, in vitro and in silico. We describe the main achievements and opportunities for improvement of each type of model and critically assess their individual and collective impact on the pursuit of predictive studies of the placenta in line with the 3Rs and European legislation.

PBPK Modeling Approach to Predict the Behavior of Drugs Cleared by Kidney in Pregnant Subjects and Fetus

The purpose of this study was to develop a physiologically based pharmacokinetic (PBPK) model predicting the pharmacokinetics (PK) of different compounds in pregnant subjects. This model considers the differences in tissue sizes, blood flow rates, enzyme expression levels, glomerular filtration rates, plasma protein binding, and other factors affected during pregnancy in both the maternal and fetal models. The PBPKPlus™ module in GastroPlus^® was used to model the PK of cefuroxime and cefazolin. For both compounds, the model was first validated against PK data in healthy non-pregnant volunteers and then applied to predict pregnant groups PK. The model accurately described the PK in both non-pregnant and pregnant groups and explained well differences in the plasma concentration due to pregnancy. The fetal plasma and amniotic fluid concentrations were also predicted reasonably well at different stages of pregnancy. This work describes 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 compounds excreted renally. The prediction for pregnant groups is also improved when the model is calibrated with postpartum or non-pregnant female group if such data are available.

Physiologically Based Pharmacokinetic Modeling to Characterize Acetaminophen Pharmacokinetics and N-Acetyl-p-Benzoquinone Imine (NAPQI) Formation in Non-Pregnant and Pregnant Women

Background and Objective

Little is known about acetaminophen (paracetamol) pharmacokinetics during pregnancy. The aim of this study was to develop a physiologically based pharmacokinetic (PBPK) model to predict acetaminophen pharmacokinetics throughout pregnancy.

Methods

PBPK models for acetaminophen and its metabolites were developed in non-pregnant and pregnant women. Physiological and enzymatic changes in pregnant women expected to impact acetaminophen pharmacokinetics were considered. Models were evaluated using goodness-of-fit plots and by comparing predicted pharmacokinetic profiles with in vivo pharmacokinetic data. Predictions were performed to illustrate the average concentration at steady state (C_ss,avg) values, used as an indicator for efficacy, of acetaminophen achieved following administration of 1000 mg every 6 h. Furthermore, as a measurement of potential hepatotoxicity, the molar dose fraction of acetaminophen converted to N-acetyl-p-benzoquinone imine (NAPQI) was estimated.

Results

PBPK models successfully predicted the pharmacokinetics of acetaminophen and its metabolites in non-pregnant and pregnant women. Predictions resulted in the lowest C_ss,avg in the third trimester (median [interquartile range]: 4.5 [3.8–5.1] mg/L), while C_ss,avg was 6.7 [5.9–7.4], 5.6 [4.7–6.3], and 4.9 [4.1–5.5] mg/L in non-pregnant, first trimester, and second trimester populations, respectively. Assuming a constant raised cytochrome P450 2E1 activity throughout pregnancy, the molar dose fraction of acetaminophen converted to NAPQI was highest during the first trimester (median [interquartile range]: 11.0% [9.1–13.4%]), followed by the second (9.0% [7.5–11.0%]) and third trimester (8.2% [6.8–10.1%]), compared with non-pregnant women (7.7% [6.4–9.4%]).

Conclusion

Acetaminophen exposure is lower in pregnant than in non-pregnant women, and is related to pregnancy duration. Despite these findings, higher dose adjustments cannot be advised yet as it is unknown whether pregnancy affects the toxicodynamics of NAPQI. Information on glutathione abundance during pregnancy and NAPQI in vivo data are required to further refine the presented model.

Electronic supplementary material

The online version of this article (10.1007/s40262-019-00799-5) contains supplementary material, which is available to authorized users.

Opening a debate on open-source modeling tools: Pouring fuel on fire versus extinguishing the flare of a healthy debate

As model‐informed drug development becomes an integral part of modern approaches to the discovery of new therapeutic entities and showing their safety and effectiveness, modalities of incorporating the paradigm into widespread practice require a revisit. Traditionally, modeling and simulation (M&S) have been performed by specialized teams who create bespoke models for each case and have reservations about letting modeling be done by the greater mass of scientists engaged in various stages of drug development. An analogy can be drawn between M&S and automobiles: typical drivers of ordinary cars use them for daily tasks, such as going from point A to B whereas specialized Formula 1 drivers using bespoke individually made cars to test the latest technologies. The reliability and robustness of ordinary cars for the first group requires elements related to quality and endurance that are very different from those applicable to any Formula 1 car supported by a large team of engineers. In this commentary, we frame and analyze the problems concerning the structure and setup of various M&S tools, and their pros and cons. We demonstrate that many misconceptions have precluded having an open discussion on what each modality of M&S tools strives to achieve, and we provide data and evidence that support the move of M&S to main stream use by many, as opposed to specialized usage by few. Parallels are drawn in many other areas involving laboratory instrumentation, statistical analyses, and so on.

Pregnancy-Related Hormones Increase UGT1A1-Mediated Labetalol Metabolism in Human Hepatocytes

Pregnancy-related hormones (PRH) are recognized as important regulators of hepatic cytochrome P450 enzyme expression and function. However, the impact of PRH on the hepatic expression and function of uridine diphosphate glucuronosyltransferases (UGTs) remains unclear. Using primary human hepatocytes, we evaluated the effect of PRH exposure on mRNA levels and protein concentrations of UGT1A1, UGT2B7, and other key UGT enzymes, and on the metabolism of labetalol (a UGT1A1 and UGT2B7 substrate commonly prescribed to treat hypertensive disorders of pregnancy). Sandwich-cultured human hepatocytes (SCHH) from female donors were exposed to the PRH estradiol, estriol, estetrol, progesterone, and cortisol individually or in combination. We quantified protein concentrations of UGT1A1, UGT2B7, and four additional UGT1A isoforms in SCHH membrane fractions and evaluated the metabolism of labetalol to its glucuronide metabolites in SCHH. PRH exposure increased mRNA levels and protein concentrations of UGT1A1 and UGT1A4 in SCHH. PRH exposure also significantly increased labetalol metabolism to its UGT1A1-derived glucuronide metabolite in a concentration-dependent manner, which positively correlated with PRH-induced changes in UGT1A1 protein concentrations. In contrast, PRH did not alter UGT2B7 mRNA levels or protein concentrations in SCHH, and formation of the UGT2B7-derived labetalol glucuronide metabolite was decreased following PRH exposure. Our findings demonstrate that PRH alter expression and function of UGT proteins in an isoform-specific manner and increase UGT1A1-mediated labetalol metabolism in human hepatocytes by inducing UGT1A1 protein concentrations. These results provide mechanistic insight into the increases in labetalol clearance observed in pregnant individuals.

Application of Model Informed Precision Dosing to Address the Impact of Pregnancy Stage and CYP2D6 Phenotype on Foetal Morphine Exposure

Guidance regarding the effect of codeine and its metabolites on foetal development is limited by small studies and inconsistent findings. The primary objective was to use physiologically based pharmacokinetic modelling to investigate the impact of gestational stage and maternal CYP2D6 phenotype on foetal morphine exposure following codeine administration. Full body physiologically based pharmacokinetic models were developed and verified for codeine and morphine using Simcyp (version 19.1). The impact of gestational age and maternal CYP2D6 phenotype on foetal and maternal morphine and codeine exposure following oral codeine administration was modelled in a cohort of 250 pregnant females and foetuses at gestational weeks 0 (mothers only), 6, 12, 24 and 36. Consistent with the known effect on codeine metabolism, a clinically meaningful (> 1.65-fold) increase in foetal morphine AUC was observed in the CYP2D6 UM phenotype cohort compared to the CYP2D6 EM and PM phenotype cohorts. The mean (95% CI) foetal morphine AUC in the CYP2D6 UM cohort of 0.988 (0.902 to 1.073) ng/mL.h was 1.8-fold higher than the CYP2D6 EM cohort of 0.546 (0.492 to 0.600) ng/mL.h (p < 0.001). Despite a 2.8-fold increase in maternal CYP2D6 protein abundance between gestational weeks 6 and 36, the mean foetal morphine AUC in the CYP2D6 EM and UM phenotype cohorts reduced by 1.55- and 1.75-fold, respectively, over this period. Maternal CYP2D6 phenotype is a significant determinant of foetal morphine AUC. Simulations suggest that the greatest risk with respect to foetal morphine exposure is during the first trimester of pregnancy, particularly in CYP2D6 UM phenotype mothers.

Maternal-Fetal Pharmacology of Drugs: A Review of Current Status of the Application of Physiologically Based Pharmacokinetic Models

Pregnancy and the postpartum period are associated with several physiological changes that can alter the pharmacokinetics (PK) and pharmacodynamics (PD) of drugs. For certain drugs, dosing changes may be required during pregnancy and postpartum to achieve drug exposures comparable to what is observed in non-pregnant subjects. There is very limited data on fetal exposure of drugs during pregnancy, and neonatal exposure through transfer of drugs via human milk during breastfeeding. Very few systematic clinical pharmacology studies have been conducted in pregnant and postpartum women due to ethical issues, concern for the fetus safety as well as potential legal ramifications. Over the past several years, there has been an increase in the application of modeling and simulation approaches such as population PK (PopPK) and physiologically based PK (PBPK) modeling to provide guidance on drug dosing in those special patient populations. Population PK models rely on measured PK data, whereas physiologically based PK models incorporate physiological, preclinical, and clinical data into the model to predict drug exposure during pregnancy. These modeling strategies offer a promising approach to identify the drugs with PK changes during pregnancy to guide dose optimization in pregnancy, when there is lack of clinical data. PBPK modeling is also utilized to predict the fetal exposure of drugs and drug transfer via human milk following maternal exposure. This review focuses on the current status of the application of PBPK modeling to predict maternal and fetal exposure of drugs and thereby guide drug therapy during pregnancy.

Assessing the impacts on fetal dosimetry of the modelling of the placental transfers of xenobiotics in a pregnancy physiologically based pharmacokinetic model

The developmental origin of health and diseases theory supports the critical role of the fetal exposure to children's health. We developed a physiologically based pharmacokinetic model for human pregnancy (pPBPK) to simulate the maternal and fetal dosimetry throughout pregnancy. Four models of the placental exchanges of chemicals were assessed on ten chemicals for which maternal and fetal data were available. These models were calibrated using non-animal methods: in vitro (InV) or ex vivo (ExV) data, a semi-empirical relationship (SE), or the limitation by the placental perfusion (PL). They did not impact the maternal pharmacokinetics but provided different profiles in the fetus. The PL and InV models performed well even if the PL model overpredicted the fetal exposure for some substances. The SE and ExV models showed the lowest global performance and the SE model a tendency to underprediction. The comparison of the profiles showed that the PL model predicted an increase in the fetal exposure with the pregnancy age, whereas the ExV model predicted a decrease. For the SE and InV models, a small decrease was predicted during the second trimester. All models but the ExV one, presented the highest fetal exposure at the end of the third trimester. Global sensitivity analyses highlighted the predominant influence of the placental transfers on the fetal exposure, as well as the metabolic clearance and the fraction unbound. Finally, the four transfer models could be considered depending on the framework of the use of the pPBPK model and the availability of data or resources to inform their parametrization.

Innovative Approaches for Pharmacology Studies in Pregnant and Lactating Women: A Viewpoint and Lessons from HIV

Medication use during pregnancy in the absence of pharmacokinetic and safety data is common, particularly for antiretrovirals, as pregnant women are not usually included in clinical trials leading to drug licensure. To date, data are typically generated through opportunistic pregnancy studies performed in the postmarketing setting, leading to a substantial time-lag between initial regulatory approval of a drug and availability of essential pregnancy-specific pharmacokinetic and safety data. During this period, health care providers lack key information on human placental transfer, fetal exposure, optimal maternal dosing in pregnancy, and maternal and fetal drug toxicity, including teratogenicity risk. We discuss new approaches that could facilitate the acquisition of these critical data earlier in the drug development process, aiding clinicians and patients in making informed decisions on drug selection and dosing during pregnancy. An integrated approach utilizing multiple novel methodologies (in vitro, ex vivo, in silico and in vivo) is needed to accelerate the availability of pharmacology data in pregnancy and lactation.

Predictive Pediatric Modeling and Simulation Using Ontogeny Information

Food and Drug Administration submissions of physiologically based pharmacokinetic (PBPK) modeling and simulation of small-molecule drugs document the relevance of pediatric drug development and, in particular, information on dosing strategies in children. The most relevant prerequisite for reliable PBPK-based translation of adult pharmacokinetics of a small molecule to children is knowledge of the drug-specific absorption, distribution, metabolism, and elimination (ADME) processes in adults together with existing information about ontogeny of ADME processes relevant for the drug. All mechanisms driving a drug's clearance are of specific importance. For other drug modalities, our knowledge of ADME processes and ontogeny is still limited. More research is required, for example, to understand why some therapeutic proteins show complex differences in pharmacokinetics between adults and children, whereas other proteins seem to follow simple allometric scaling rules. Ontogeny information originates from various sources, such as (semi)quantitative mRNA expression, in vitro activity data, and deconvolution of in vivo pharmacokinetic data. The workflow for pediatric predictions is well described in several articles documenting successful translation from adults to children. The technical hurdles for PBPK modeling are low. State-of-the-art PBPK modeling software tools provide integrated pediatric translation workflows. For example, PK-Sim and MoBi are freely available as fully transparent open-source software via Open Systems Pharmacology (OSP). With the latest 2019 software release, version 8.0, OSP even provides a fully integrated technical framework for the qualification (and requalification) of any specific intended PBPK use in line with Food and Drug Administration and European Medicines Agency PBPK guidance. Qualification packages for pediatric translation are available on the OSP platform.

Pregnancy-Related Hormones Increase Nifedipine Metabolism in Human Hepatocytes by Inducing CYP3A4 Expression

Pregnancy-related hormones (PRH) have emerged as key regulators of hepatic cytochrome P450 (CYP) enzyme expression and function. The impact of PRH on protein levels of CYP3A4 and other key CYP enzymes, and the metabolism of nifedipine (a CYP3A4 substrate commonly prescribed during pregnancy), was evaluated in primary human hepatocytes. Sandwich-cultured human hepatocytes (SCHH) from female donors were exposed to PRH (estradiol, estriol, estetrol, progesterone, and cortisol), individually or in combination as a cocktail. Absolute protein concentrations of twelve CYP isoforms in SCHH membrane fractions were quantified by nanoLC-MS/MS, and metabolism of nifedipine to dehydronifedipine in SCHH was evaluated. PRH significantly increased CYP3A4 protein concentrations and nifedipine metabolism to dehydronifedipine in a concentration-dependent manner. CYP3A4 mRNA levels in hepatocyte-derived exosomes positively correlated with CYP3A4 protein levels and dehydronifedipine formation in SCHH. PRH also increased CYP2B6, CYP2C8 and CYP2A6 levels. Our findings demonstrate that PRH increase nifedipine metabolism in SCHH by inducing CYP3A4 expression and alter expression of other key CYP proteins in an isoform-specific manner, and suggest that hepatocyte-derived exosomes warrant further investigation as biomarkers of hepatic CYP3A4 metabolism. Together, these results offer mechanistic insight into the increases in nifedipine metabolism and clearance observed in pregnant women.

Immunomodulatory Therapeutic Proteins in COVID-19: Current Clinical Development and Clinical Pharmacology Considerations

The coronavirus disease 2019 (COVID‐19) pandemic caused by infection with SARS‐CoV‐2 has led to more than 600 000 deaths worldwide. Patients with severe disease often experience acute respiratory distress characterized by upregulation of multiple cytokines. Immunomodulatory biological therapies are being evaluated in clinical trials for the management of the systemic inflammatory response and pulmonary complications in patients with advanced stages of COVID‐19. In this review, we summarize the clinical pharmacology considerations in the development of immunomodulatory therapeutic proteins for mitigating the heightened inflammatory response identified in COVID‐19.

Drug-Drug Interactions with Antiretroviral Drugs in Pregnant Women Living with HIV: Are They Different from Non-Pregnant Individuals?

Background and Objective

Although the separate effects of drug–drug interactions and pregnancy on antiretroviral drug pharmacokinetics have been widely studied and described, their combined effect is largely unknown. Physiological changes during pregnancy may change the extent or clinical relevance of a drug–drug interaction in a pregnant woman. This review aims to provide a detailed overview of the mechanisms, magnitude, and clinical significance of antiretroviral drug–drug interactions in pregnant women.

Methods

We performed a literature search and selected studies that compared the magnitude of drug–drug interactions with antiretroviral drugs in pregnant vs non-pregnant women.

Results

Forty-eight papers examining drug–drug interactions during pregnancy were selected, of which the majority focused on pharmacokinetic boosting. Other selected studies examined the drug–drug interactions between efavirenz and lumefantrine, efavirenz and tuberculosis drugs, etravirine and tenofovir disoproxil fumarate, atazanavir and tenofovir disoproxil, and mefloquine and nevirapine in pregnant compared to non-pregnant women. The clinical significance of antiretroviral drug–drug interactions changed during pregnancy from a minimal effect to a contra-indication. In almost all cases, the clinical significance of a drug–drug interaction was more relevant in pregnant women, owing to the combined effects of pregnancy-induced physiological changes and drug–drug interactions leading to a lower absolute drug exposure.

Conclusions

Multiple studies show that the clinical relevance of a drug–drug interaction can change during pregnancy. Unfortunately, many potential interactions have not been studied in pregnancy, which may place pregnant women living with human immunodeficiency virus and their newborns at risk.

Preliminary physiologically based pharmacokinetic modeling of renally cleared drugs in Chinese pregnant women

AIM

The aim of this study was to build and verify a preliminary physiologically based pharmacokinetic (PBPK) model of Chinese pregnant women. The model was used to predict maternal pharmacokinetics (PK) of 6 predominantly renally cleared drugs.

METHOD

Based on SimCYP Caucasian pregnancy population dataset, the preliminary Chinese pregnant population was built by updating several key parameters and equations according to physiological parameters of Chinese (or Japanese) pregnant women. Drug-specific parameters of 6 renally cleared drugs were validated through PBPK modeling of Caucasian non-pregnant, Caucasian pregnant and Chinese non-pregnant population. The preliminary PBPK model of Chinese pregnant population was then developed by integrating the preliminary Chinese pregnant population and the drug-specific parameters. This model was verified by comparing the predicted maternal PK of these 6 drugs with the observed in vivo data from the literature.

RESULTS

The preliminary Chinese pregnant population PBPK model successfully predicted the PK of 6 target drugs for different pregnancy stages. The predicted plasma concentrations time profiles fitted the observed data well, and most predicted PK parameters were within 2-fold of observed data.

CONCLUSIONS

The preliminary Chinese pregnant population PBPK model provided a useful tool to predict the maternal PK of 6 predominantly renally cleared drugs in Chinese pregnant women.

Drug dosing during pregnancy-opportunities for physiologically based pharmacokinetic models

Drugs can have harmful effects on the embryo or the fetus at any point during pregnancy. Not all the damaging effects of intrauterine exposure to drugs are obvious at birth, some may only manifest later in life. Thus, drugs should be prescribed in pregnancy only if the expected benefit to the mother is thought to be greater than the risk to the fetus. Dosing of drugs during pregnancy is often empirically determined and based upon evidence from studies of non-pregnant subjects, which may lead to suboptimal dosing, particularly during the third trimester. This review collates examples of drugs with known recommendations for dose adjustment during pregnancy, in addition to providing an example of the potential use of PBPK models in dose adjustment recommendation during pregnancy within the context of drug-drug interactions. For many drugs, such as antidepressants and antiretroviral drugs, dose adjustment has been recommended based on pharmacokinetic studies demonstrating a reduction in drug concentrations. However, there is relatively limited (and sometimes inconsistent) information regarding the clinical impact of these pharmacokinetic changes during pregnancy and the effect of subsequent dose adjustments. Examples of using pregnancy PBPK models to predict feto-maternal drug exposures and their applications to facilitate and guide dose assessment throughout gestation are discussed.

Prediction of Maternal and Fetal Pharmacokinetics of Dolutegravir and Raltegravir Using Physiologically Based Pharmacokinetic Modeling

BACKGROUND

Predicting drug pharmacokinetics in pregnant women including placental drug transfer remains challenging. This study aimed to develop and evaluate maternal-fetal physiologically based pharmacokinetic models for two antiretroviral drugs, dolutegravir and raltegravir.

Drugs in pregnancy: Pharmacologic and physiologic changes that affect clinical care

Pharmacologic interventions play a major role in obstetrical care throughout pregnancy, labor and delivery and the postpartum. Traditionally, obstetrical providers have utilized standard dosing regimens developed for non-obstetrical indications based on pharmacokinetic knowledge from studies in men or non-pregnant women. With the recognition of pregnancy as a special pharmacokinetic population in the late 1990s, investigators have begun to study drug disposition in this unique patient dyad. Many of the basic physiologic changes that occur during pregnancy have significant impact on drug absorption, distribution and clearance. Activity of Phase I and Phase II drug metabolizing enzymes are differentially altered by pregnancy, resulting in drug concentrations sufficiently different for some medications that efficacy or toxicity is affected. Placental transporters play a major dynamic role in determining fetal drug exposure. In the past two decades, we have begun to expand our understanding of obstetrical pharmacology; however, to truly optimize pharmacologic care of our pregnant patients and their developing fetus, additional research is critically needed.

Pharmacokinetic studies in pregnancy

The effects of the many biochemical and physiologic changes of pregnancy on the dose-response relationship of drugs administered to pregnant women are poorly understood. The dose-response relationship is affected by pharmacokinetics, or what the body does to a drug, and pharmacodynamics, or what a drug does to the body. Insights into the potential effects of the changes of pregnancy on one aspect of the dose-response relationship of a drug can be obtained by studying the pharmacokinetics of the drug in the various stages of pregnancy and the postpartum period. There are several available approaches to studying pharmacokinetic changes in pregnancy. Single trough screening studies can provide qualitative estimates of elimination clearance, which with the dosing rate determines the steady-state drug concentration, throughout pregnancy and into the postpartum period. Population pharmacokinetic studies such as two stage pharmacokinetic studies and studies using a nonlinear mixed effects pharmacokinetic modeling approach can characterize pharmacokinetic changes more rigorously.

Sildenafil for Antenatal Treatment of Congenital Diaphragmatic Hernia: From Bench to Bedside

BACKGROUND

Persistent pulmonary hypertension (PPH) is one of the main causes of mortality and morbidity in infants affected by congenital diaphragmatic hernia (CDH). Since the structural changes that lead to PPH take place already in utero, a treatment starting in the prenatal phase may prevent the occurrence of this complication.

OBJECTIVE

To summarize the development process of antenatal sildenafil for CDH.

METHODS

The pharmacokinetics and efficacy of sildenafil have been assessed in the rat and the rabbit model. The transfer of the drug through the human placenta has been measured with the ex-vivo placenta perfusion model. Results from this experiment are being incorporated in a pregnancy-physiologically based pharmacokinetic (p- PBPK) model. A phase I-IIb placental transfer and safety study is ongoing.

RESULTS

Sildenafil administration to pregnant rats and rabbits led to therapeutic foetal drug levels without maternal and foetal toxicity, although it was associated with impaired vascular development in foetuses with nonhypoplastic lungs. Peak concentrations and 24-hour exposure were higher in pregnant rabbits compared to nonpregnant ones. In rat and rabbit foetuses with CDH, sildenafil rescued the lung vascular anomalies and partially improved parenchymal development. Sildenafil crossed the human placenta at a high rate ex-vivo, independently from the initial maternal concentration.

CONCLUSION

There is preclinical evidence that maternally administered sildenafil prevents the vascular changes that lead to PPH in CDH newborns. The phase I/IIb clinical study together with the p-PBPK model will define the maternal dose needed for a therapeutic effect in the foetus. Foetal safety will be investigated both in the clinical study and in the sheep. The final step will be a multicentre, randomized, placebo-controlled trial.

Clinical Pharmacokinetic Studies in Pregnant Women and the Relevance of Pharmacometric Tools

BACKGROUND

In clinical pharmacokinetic (PK) studies, pregnant women are significantly underrepresented because of ethical and legal reasons which lead to a paucity of information on potential PK changes in this population. As a consequence, pharmacometric tools became instrumental to explore and quantify the impact of PK changes during pregnancy.

METHODS

We explore and discuss the typical characteristics of population PK and physiologically based pharmacokinetic (PBPK) models with a specific focus on pregnancy and postpartum.

RESULTS

Population PK models enable the analysis of dense, sparse or unbalanced data to explore covariates in order to (partly) explain inter-individual variability (including pregnancy) and to individualize dosing. For population PK models, we subsequently used an illustrative approach with ketorolac data to highlight the relevance of enantiomer specific modeling for racemic drugs during pregnancy, while data on antibiotic prophylaxis (cefazolin) during surgery illustrate the specific characteristics of the fetal compartments in the presence of timeconcentration profiles. For PBPK models, an overview on the current status of reports and papers during pregnancy is followed by a PBPK cefuroxime model to illustrate the added benefit of PBPK in evaluating dosing regimens in pregnant women.

CONCLUSIONS

Pharmacometric tools became very instrumental to improve perinatal pharmacology. However, to reach their full potential, multidisciplinary collaboration and structured efforts are needed to generate more information from already available datasets, to share data and models, and to stimulate cross talk between clinicians and pharmacometricians to generate specific observations (pathophysiology during pregnancy, breastfeeding) needed to further develop the field.

Integration of Placental Transfer in a Fetal-Maternal Physiologically Based Pharmacokinetic Model to Characterize Acetaminophen Exposure and Metabolic Clearance in the Fetus

BACKGROUND AND OBJECTIVE

Although acetaminophen is frequently used during pregnancy, little is known about fetal acetaminophen pharmacokinetics. Acetaminophen safety evaluation has typically focused on hepatotoxicity, while other events (fetal ductal closure/constriction) are also relevant. We aimed to develop a fetal-maternal physiologically based pharmacokinetic (PBPK) model (f-m PBPK) to quantitatively predict placental acetaminophen transfer, characterize fetal acetaminophen exposure, and quantify the contributions of specific clearance pathways in the term fetus.

METHODS

An acetaminophen pregnancy PBPK model was extended with a compartment representing the fetal liver, which included maturation of relevant enzymes. Different approaches to describe placental transfer were evaluated (ex vivo cotyledon perfusion experiments, placental transfer prediction based on Caco-2 cell permeability or physicochemical properties [MoBi^®]). Predicted maternal and fetal acetaminophen profiles were compared with in vivo observations.

RESULTS

Tested approaches to predict placental transfer showed comparable performance, although the ex vivo approach showed highest prediction accuracy. Acetaminophen exposure in maternal venous blood was similar to fetal venous umbilical cord blood. Prediction of fetal acetaminophen clearance indicated that the median molar dose fraction converted to acetaminophen-sulphate and N-acetyl-p-benzoquinone imine was 0.8% and 0.06%, respectively. The predicted mean acetaminophen concentration in the arterial umbilical cord blood was 3.6 mg/L.

CONCLUSION

The median dose fraction of acetaminophen converted to its metabolites in the term fetus was predicted. The various placental transfer approaches supported the development of a generic f-m PBPK model incorporating in vivo placental drug transfer. The predicted arterial umbilical cord acetaminophen concentration was far below the suggested postnatal threshold (24.47 mg/L) for ductal closure.

Physiologically Based Pharmacokinetic Models to Predict Maternal Pharmacokinetics and Fetal Exposure to Emtricitabine and Acyclovir

Pregnancy is associated with physiological changes that may impact drug pharmacokinetics (PK). The goals of this study were to build maternal-fetal physiologically based pharmacokinetic (PBPK) models for acyclovir and emtricitabine, 2 anti(retro)viral drugs with active renal net secretion, and to (1) evaluate the predicted maternal PK at different stages of pregnancy; (2) predict the changes in PK target parameters following the current dosing regimen of these drugs throughout pregnancy; (3) evaluate the predicted concentrations of these drugs in the umbilical vein at delivery; (4) compare the model performance for predicting maternal PK of emtricitabine in the third trimester with that of previously published PBPK models; and (5) compare different previously published approaches for estimating the placental permeability of these 2 drugs. Results showed that the pregnancy PBPK model for acyclovir predicted all maternal concentrations within a 2-fold error range, whereas the model for emtricitabine predicted 79% of the maternal concentrations values within that range. Extrapolation of these models to earlier stages of pregnancy indicated that the change in the median PK target parameters remained well above the target threshold. Concentrations of acyclovir and emtricitabine in the umbilical vein were overall adequately predicted. The comparison of different emtricitabine PBPK models suggested an overall similar predictive performance in the third trimester, but the comparison of different approaches for estimating placental drug permeability revealed large differences. These models can enhance the understanding of the PK behavior of renally excreted drugs, which may ultimately inform pharmacotherapeutic decision making in pregnant women and their fetuses.

Drug Transporters Expressed in the Human Placenta and Models for Studying Maternal-Fetal Drug Transfer

Tremendous efforts have been directed to investigate the ontogeny of drug transporters in fetuses, neonates, infants, and children based on their importance for understanding drug pharmacokinetics. During development (ie, in the fetus and newborn infant), there is special interest in transporters expressed in the placenta that modulate placental drug transfer. Many of these transporters can decrease or increase drug concentrations in the fetus and at birth, stressing the relevance of elucidating expression in the placenta and potential gestational age-dependent changes therein. Hence, the main objective of this review was to summarize the current knowledge about expression and ontogeny of transporters in the human placenta in healthy pregnant women. In addition, various in vitro, ex vivo, and in silico models that can be used to investigate placental drug transfer, namely, placental cancer cell lines, ex vivo cotyledon perfusion experiments, and physiologically based pharmacokinetic (PBPK) models, are discussed together with their advantages and shortcomings. A particular focus was placed on PBPK models because these models can integrate different types of information, such as expression data, ontogeny information, and observations obtained from the ex vivo cotyledon perfusion experiment. Such a mechanistic modeling framework may leverage the available information and ultimately help to improve knowledge about the adequacy and safety of pharmacotherapy in pregnant women and their fetuses.

Pharmacometrics in Pediatrics

Pharmacometrics have advanced from compartmental analysis to noncompartmental analysis and population pharmacokinetics that require complicated mathematical programs. These sophisticated mathematical analyses determine not only the usual pharmacometric measures of clearance and volume of distribution but also the effects of covariates on these measures. Although these analyses are very suitable to studies of small patient populations often encountered in pediatric studies, most pediatric clinicians have not been trained in how these analyses are conducted or the meaning of the results of these analyses expressed in terms of error measures and fixed and variable effects. In addition, clinicians may not be able to evaluate whether their patient population is adequately represented in the analysis. Thorough and clear descriptions of the methodology and the strengths and weaknesses of these analyses need to be published in journals read by clinicians.

Physiologically Based Pharmacokinetic/Pharmacodynamic Model for Caffeine Disposition in Pregnancy

Caffeine is the most consumed active stimulant. About 80% of pregnant women consume caffeine orally on a daily basis. Many reports indicated consumption of >200 mg caffeine during pregnancy could increase the likelihood of miscarriage. In this article, we developed a pregnancy physiological-based pharmacokinetic/pharmacodynamic (PBPK/PD) model for caffeine to examine association between maternal caffeine consumption during pregnancy and caffeine plasma levels at doses lower and higher than 200 mg to predict changes in caffeine concentrations across the 3 trimesters, and to predict associated changes in caffeine PD parameters. Two models were successfully developed using GastroPlus software, a nonpregnant model for validation purposes and a pregnant model for validation and prediction of maternal caffeine plasma concentrations following single and multiple dosing. Using observed and predicted data, we were able to validate and simulate PK changes of caffeine in nonpregnant women and the PD effect of caffeine on certain enzymes and catecholamines associated with caffeine intake. Furthermore, the pregnancy PBPK model successfully predicted changes in caffeine PK across the three trimesters. Caffeine increased exposure during pregnancy was related to reduced activity of caffeine metabolizing enzyme CYP1A2. The model also predicted increased levels of caffeine in the fetoplacental compartment (FPC) due to increased maternal caffeine plasma concentrations. Increased caffeine levels in maternal blood was accompanied by greater inhibition of the phosphodiesterase enzyme, higher cyclic adenosine monophosphate, and greater increase of epinephrine levels, which could increase the risk of pregnancy loss. The application of the developed PBPK model to predict the PD effect could provide a useful tool to help define potential cut-offs for caffeine intake in various stages of pregnancy.

Clinical Pharmacology and Pharmacometrics to Better Understand Physiological Changes During Pregnancy and Neonatal Life

Pregnant women, fetuses, and newborns are particularly vulnerable patient populations. During pregnancy, the body is subject to physiological changes that influence the pharmacokinetics and pharmacodynamics of drugs. Inappropriate dosing in pregnant women can result in sub-therapeutic or toxic effects, putting not only the pregnant woman but also her fetus at risk. During neonatal life, maturation processes also affect pharmacokinetics and pharmacodynamics of drugs. Inappropriate dosing in newborns leads not only to short-term complications but can also have a negative impact on the long-term development of infants and children. For these reasons, it is crucial to characterize physiological changes in pregnant women, describe placental transfer kinetics of drugs, and describe physiological changes related to the transition from intrauterine to extrauterine life and maturation processes in preterm and term neonates. Quantitative pharmacological approaches such as pharmacometric and physiologically-based modeling and model-based simulations can be useful to better understand and predict such physiological changes and their effects on drug exposure and response. This review article (1) gives an overview of physiological changes in pregnant women, their fetuses, and (pre)term neonates, (2) presents case studies to illustrate applications of new modeling and simulation approaches, and (3) discusses challenges and opportunities in optimizing and personalizing treatments during pregnancy and neonatal life.