Assessment of Maternal and Fetal Dolutegravir Exposure by Integrating Ex Vivo Placental Perfusion Data and Physiologically-Based Pharmacokinetic Modeling

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.

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.

Variability in perfusion conditions and set-up parameters used in ex vivo human placenta models: A literature review

The ex vivo human placenta perfusion model has proven to be clinically relevant to study transfer- and fetal exposure of various drugs. Although the method has existed for a long period, the setup of the perfusion model has not been generalized yet. This review aims to summarize the setups of ex vivo placental perfusion models used to examine drug transfer across the placenta to identify generalized properties and differences across setups. A literature search was carried out in PubMed September 26, 2022. Studies were labeled as relevant when information was reported, between 2000 and 2022, on the setups of ex vivo placental perfusion models used to study drug transfer across the placenta. The placenta perfusion process, and the data extraction, was divided into phases of preparation, control, drug, and experimental reflecting the chronological timeline of the different phases during the entire placental perfusion process. 135 studies describing an ex vivo human placental perfusion experiment were included. Among included studies, the majority (78.5%) analyzed drug perfusion in maternal to fetal direction, 18% evaluated bi-directional drug perfusion, 3% under equilibrium conditions, and one study investigated drug perfusion in fetal to maternal direction. This literature review facilitates the comparison of studies that employ similar placenta perfusion protocols for drug transfer studies and reveals significant disparities in the setup of these ex vivo placental perfusion models. Due to interlaboratory variability, perfusion studies are not readily comparable or interchangeable. Therefore, a stepwise protocol with multiple checkpoints for validating placental perfusion is needed.

Physiologically-based pharmacokinetic models to predict drug exposure during pregnancy

As pregnant women are constantly exposed to drugs during pregnancy, either to treat long-term conditions or acute illnesses, drug safety is a major concern for the fetus and the mother. Clinical trials are rarely made in this population due to strict regulation and ethical reasons. However, drug pharmacokinetic (PK) parameters vary during pregnancy with an increase in distribution volume, renal clearance and more. In addition, the fetal distribution should be evaluated with the importance of placental diffusion, both active and passive. Therefore, there is a recent interest in the use of physiologically-based pharmacokinetic (PBPK) modeling to characterize these changes and complete the sparse data available on drug PK during pregnancy. Indeed, PBPK models integrate drug physicochemical and physiological parameters corresponding to each compartment of the body to estimate drug concentrations. This review establishes an overview on the current use of PBPK models in drug dosage determination for the pregnant woman, fetal exposure and drug interactions in the fetal compartment.

Physiologically-based pharmacokinetic modelling of long-acting injectable cabotegravir and rilpivirine in pregnancy

AIMS

Long-acting cabotegravir and rilpivirine have been approved to manage HIV in adults, but data regarding safe use in pregnancy are limited. Physiologically-based pharmacokinetic (PBPK) modelling was used to simulate the approved dosing regimens in pregnancy and explore if Ctrough was maintained above cabotegravir and rilpivirine target concentrations (664 and 50 ng/mL, respectively).

METHODS

An adult PBPK model was validated using clinical data of cabotegravir and rilpivirine in nonpregnant adults. This was modified by incorporating pregnancy-induced metabolic and physiological changes. The pregnancy PBPK model was validated with data on oral rilpivirine and raltegravir (UGT1A1 probe substrate) in pregnancy. Twelve weeks' disposition of monthly and bimonthly dosing of long-acting cabotegravir and rilpivirine was simulated at different trimesters and foetal exposure was also estimated.

RESULTS

Predicted Ctrough at week 12 for monthly long-acting cabotegravir was above 664 ng/mL throughout pregnancy, but below the target in 0.5% of the pregnant population in the third trimester with bimonthly long-acting cabotegravir. Predicted Ctrough at week 12 for monthly and bimonthly long-acting rilpivirine was below 50 ng/mL in at least 40% and over 90% of the pregnant population, respectively, throughout pregnancy. Predicted medians (range) of cord-to-maternal blood ratios were 1.71 (range, 1.55-1.79) for cabotegravir and 0.88 (0.78-0.93) for rilpivirine between weeks 38 and 40.

CONCLUSIONS

Model predictions suggest that monthly long-acting cabotegravir could maintain antiviral efficacy throughout pregnancy, but that bimonthly administration may require careful clinical evaluation. Both monthly and bimonthly long-acting rilpivirine may not adequately maintain antiviral efficacy in pregnancy.

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.

Evaluation of a microphysiological human placental barrier model for studying placental drug transfer

Understanding drug transport across the placental barrier is important for assessing the potential fetal drug toxicity and birth defect risks. Current in vivo and in vitro models have structural and functional limitations in evaluating placental drug transfer and toxicity. Microphysiological systems (MPSs) offer more accurate and relevant physiological models of human tissues and organs on a miniature scale for drug development and toxicology testing. MPSs for the placental barrier have been recently explored to study placental drug transfer. We utilized a multilayered hydrogel membrane-based microphysiological model composed of human placental epithelial and endothelial cells to replicate the key structure and function of the human placental barrier. A macroscale human placental barrier model was created using a transwell to compare the results with the microphysiological model. Placental barrier models were characterized by assessing monolayer formation, intercellular junctions, barrier permeability, and their structural integrity. Three small-molecule drugs (glyburide, rifaximin, and caffeine) that are prescribed or taken during pregnancy were studied for their placental transfer. The results showed that all three drugs crossed the placental barrier, with transfer rates in the following order: glyburide (molecular weight, MW = 494 Da) < rifaximin (MW = 785.9 Da) < caffeine (MW = 194.19 Da). Using non-compartmental analysis, we estimated human pharmacokinetic characteristics based on in vitro data from both MPS and transwell models. While further research is needed, our findings suggest that MPS holds potential as an in vitro tool for studying placental drug transfer and predicting fetal exposure, offering insights into pharmacokinetics.

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.

An update on placental drug transport and its relevance to fetal drug exposure

Pregnant women are often complicated with diseases that require treatment with medication. Most drugs administered to pregnant women are off-label without the necessary dose, efficacy, and safety information. Knowledge concerning drug transfer across the placental barrier is essential for understanding fetal drug exposure and hence drug safety and efficacy to the fetus. Transporters expressed in the placenta, including adenosine triphosphate (ATP)-binding cassette efflux transporters and solute carrier uptake transporters, play important roles in determining drug transfer across the placental barrier, leading to fetal exposure to the drugs. In this review, we provide an update on placental drug transport, including in vitro cell/tissue, ex vivo human placenta perfusion, and in vivo animal studies that can be used to determine the expression and function of drug transporters in the placenta as well as placental drug transfer and fetal drug exposure. We also describe how the knowledge of placental drug transfer through passive diffusion or active transport can be combined with physiologically based pharmacokinetic modeling and simulation to predict systemic fetal drug exposure. Finally, we highlight knowledge gaps in studying placental drug transport and predicting fetal drug exposure and discuss future research directions to fill these gaps.

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.

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

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

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.

Applications, Challenges, and Outlook for PBPK Modeling and Simulation: A Regulatory, Industrial and Academic Perspective

Several regulatory guidances on the use of physiologically based pharmacokinetic (PBPK) analyses and physiologically based biopharmaceutics model(s) (PBBM(s)) have been issued. Workshops are routinely held, demonstrating substantial interest in applying these modeling approaches to address scientific questions in drug development. PBPK models and PBBMs have remarkably contributed to model-informed drug development (MIDD) such as anticipating clinical PK outcomes affected by extrinsic and intrinsic factors in general and specific populations. In this review, we proposed practical considerations for a "base" PBPK model construction and development, summarized current status, challenges including model validation and gaps in system models, and future perspectives in PBPK evaluation to assess a) drug metabolizing enzyme(s)- or drug transporter(s)- mediated drug-drug interactions b) dosing regimen prediction, sampling timepoint selection and dose validation in pediatric patients from newborns to adolescents, c) drug exposure in patients with renal and/or and hepatic organ impairment, d) maternal-fetal drug disposition during pregnancy, and e) pH-mediated drug-drug interactions in patients treated with proton pump inhibitors/acid-reducing agents (PPIs/ARAs) intended for gastric protection. Since PBPK can simulate outcomes in clinical studies with enrollment challenges or ethical issues, the impact of PBPK models on waivers and how to strengthen study waiver is discussed.

Clinical Implications of Altered Drug Transporter Abundance/Function and PBPK Modeling in Specific Populations: An ITC Perspective

The role of membrane transporters on pharmacokinetics (PKs), drug-drug interactions (DDIs), pharmacodynamics (PDs), and toxicity of drugs has been broadly recognized. However, our knowledge of modulation of transporter expression and/or function in the diseased patient population or specific populations, such as pediatrics or pregnancy, is still emerging. This white paper highlights recent advances in studying the changes in transporter expression and activity in various diseases (i.e., renal and hepatic impairment and cancer) and some specific populations (i.e., pediatrics and pregnancy) with the focus on clinical implications. Proposed alterations in transporter abundance and/or activity in diseased and specific populations are based on (i) quantitative transporter proteomic data and relative abundance in specific populations vs. healthy adults, (ii) clinical PKs, and emerging transporter biomarker and/or pharmacogenomic data, and (iii) physiologically-based pharmacokinetic modeling and simulation. The potential for altered PK, PD, and toxicity in these populations needs to be considered for drugs and their active metabolites in which transporter-mediated uptake/efflux is a major contributor to their absorption, distribution, and elimination pathways and/or associated DDI risk. In addition to best practices, this white paper discusses current challenges and knowledge gaps to study and quantitatively predict the effects of modulation in transporter activity in these populations, together with the perspectives from the International Transporter Consortium (ITC) on future directions.

Raltegravir-based Postnatal HIV Prophylaxis Therapy in a Neonate After in Utero Dolutegravir Exposure

We present a case report of a neonate receiving raltegravir-based postnatal HIV prophylaxis after in utero dolutegravir exposure. High levels of raltegravir and dolutegravir can potentially cause bilirubin toxicity as they compete for albumin binding and follow the same metabolic pathway through UGT1A1. This case suggests delaying initiation of raltegravir-based postnatal prophylaxis by 24-48 hours after in utero dolutegravir exposure.

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.

Pharmacokinetics and placental transfer of dolutegravir in pregnancy

Dolutegravir is currently recommended by the WHO as the preferred first-line treatment for all people with HIV, including pregnant women. Estimates indicate that, by 2024, nearly 22 million adults in low- and middle-income countries will have transitioned to dolutegravir-based ART. It is therefore critical that there is a clear appreciation and understanding of the risks that may be associated with in utero exposure to dolutegravir. In this review we consolidate data from studies on dolutegravir and the placenta. The studies have largely focused on the pharmacokinetics and placental transfer of dolutegravir in pregnancy. These include studies on transplacental transfer of dolutegravir, ex vivo placenta perfusion models, physiologically based pharmacokinetic (PBPK) models and animal studies. The data available clearly demonstrate that placental transfer of dolutegravir occurs in moderate to high concentrations. Intracellular placental dolutegravir has been demonstrated in the placental villous tissue. There are limited data suggesting that pregnancy is associated with decreased maternal dolutegravir levels. In addition, PBPK models have great potential in predicting the passage of drugs through the placenta and further contributing towards the elucidation of fetal exposure. The animal studies available demonstrate that in utero dolutegravir exposure can be associated with neural tube defects. Taking into consideration that antiretroviral exposure may be associated with poor placental development or function and increased risk of adverse effects to the fetus, it is crucially important that these risks are evaluated, especially with the rapid scale up of dolutegravir-based ART into national treatment programmes.

Mechanistic Coupling of a Novel in silico Cotyledon Perfusion Model and a Physiologically Based Pharmacokinetic Model to Predict Fetal Acetaminophen Pharmacokinetics at Delivery

Little is known about placental drug transfer and fetal pharmacokinetics despite increasing drug use in pregnant women. While physiologically based pharmacokinetic (PBPK) models can help in some cases to shed light on this knowledge gap, adequate parameterization of placental drug transfer remains challenging. A novel in silico model with seven compartments representing the ex vivo cotyledon perfusion assay was developed and used to describe placental transfer and fetal pharmacokinetics of acetaminophen. Unknown parameters were optimized using observed data. Thereafter, values of relevant model parameters were copied to a maternal-fetal PBPK model and acetaminophen pharmacokinetics were predicted at delivery after oral administration of 1,000 mg. Predictions in the umbilical vein were evaluated with data from two clinical studies. Simulations from the in silico cotyledon perfusion model indicated that acetaminophen accumulates in the trophoblasts; simulated steady state concentrations in the trophoblasts were 4.31-fold higher than those in the perfusate. The whole-body PBPK model predicted umbilical vein concentrations with a mean prediction error of 24.7%. Of the 62 concentration values reported in the clinical studies, 50 values (81%) were predicted within a 2-fold error range. In conclusion, this study presents a novel in silico cotyledon perfusion model that is structurally congruent with the placenta implemented in our maternal-fetal PBPK model. This allows transferring parameters from the former model into our PBPK model for mechanistically exploring whole-body pharmacokinetics and concentration-effect relationships in the placental tissue. Further studies should investigate acetaminophen accumulation and metabolism in the placenta as the former might potentially affect placental prostaglandin synthesis and subsequent fetal exposure.

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.

A Machine Learning Model to Predict Drug Transfer Across the Human Placenta Barrier

The development of computational models for assessing the transfer of chemicals across the placental membrane would be of the utmost importance in drug discovery campaigns, in order to develop safe therapeutic options. We have developed a low-dimensional machine learning model capable of classifying compounds according to whether they can cross or not the placental barrier. To this aim, we compiled a database of 248 compounds with experimental information about their placental transfer, characterizing each compound with a set of ∼5.4 thousand descriptors, including physicochemical properties and structural features. We evaluated different machine learning classifiers and implemented a genetic algorithm, in a five cross validation scheme, to perform feature selection. The optimization was guided towards models displaying a low number of false positives (molecules that actually cross the placental barrier, but are predicted as not crossing it). A Linear Discriminant Analysis model trained with only four structural features resulted to be robust for this task, exhibiting only one false positive case across all testing folds. This model is expected to be useful in predicting placental drug transfer during pregnancy, and thus could be used as a filter for chemical libraries in virtual screening campaigns.

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.

Mechanistic Modeling of Maternal Lymphoid and Fetal Plasma Antiretroviral Exposure During the Third Trimester

Pregnancy-induced changes in plasma pharmacokinetics of many antiretrovirals (ARV) are well-established. Current knowledge about the extent of ARV exposure in lymphoid tissues of pregnant women and within the fetal compartment is limited due to their inaccessibility. Subtherapeutic ARV concentrations in HIV reservoirs like lymphoid tissues during pregnancy may constitute a barrier to adequate virological suppression and increase the risk of mother-to-child transmission (MTCT). The present study describes the pharmacokinetics of three ARVs (efavirenz, dolutegravir, and rilpivirine) in lymphoid tissues and fetal plasma during pregnancy using materno-fetal physiologically-based pharmacokinetic models (m-f-PBPK). Lymphatic and fetal compartments were integrated into our previously validated adult PBPK model. Physiological and drug disposition processes were described using ordinary differential equations. For each drug, virtual pregnant women (n = 50 per simulation) received the standard dose during the third trimester. Essential pharmacokinetic parameters, including Cmax, Cmin, and AUC (0-24), were computed from the concentration-time data at steady state for lymph and fetal plasma. Models were qualified by comparison of predictions with published clinical data, the acceptance threshold being an absolute average fold-error (AAFE) within 2.0. AAFE for all model predictions was within 1.08-1.99 for all three drugs. Maternal lymph concentration 24 h after dose exceeded the reported minimum effective concentration (MEC) for efavirenz (11,514 vs. 800 ng/ml) and rilpivirine (118.8 vs. 50 ng/ml), but was substantially lower for dolutegravir (16.96 vs. 300 ng/ml). In addition, predicted maternal lymph-to-plasma AUC ratios vary considerably (6.431-efavirenz, 0.016-dolutegravir, 1.717-rilpivirine). Furthermore, fetal plasma-to-maternal plasma AUC ratios were 0.59 for efavirenz, 0.78 for dolutegravir, and 0.57 for rilpivirine. Compared with rilpivirine (0 h), longer dose forgiveness was observed for dolutegravir in fetal plasma (42 h), and for efavirenz in maternal lymph (12 h). The predicted low lymphoid tissue penetration of dolutegravir appears to be significantly offset by its extended dose forgiveness and adequate fetal compartment exposure. Hence, it is unlikely to be a predictor of maternal virological failure or MTCT risks. Predictions from our m-f-PBPK models align with recommendations of no dose adjustment despite moderate changes in exposure during pregnancy for these drugs. This is an important new application of PBPK modeling to evaluate the adequacy of drug exposure in otherwise inaccessible compartments.

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.

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.