Prediction of Pregnancy-Induced Changes in Secretory and Total Renal Clearance of Drugs Transported by Organic Anion Transporters

Application of a Physiologically Based Pharmacokinetic Approach to Predict Tenofovir Pharmacokinetics During Pregnancy

Pharmacotherapy during pregnancy requires a better understanding of the impact of changes in maternal physiology on the maternal and fetal drug exposure. The physiologically based pharmacokinetic (PBPK) modelling approach can be applied to predict maternal and fetal exposure. In vitro and in vivo PK data in non-pregnant individuals were compiled and used to develop and verify a PBPK model for tenofovir. The model was then used to predict the maternal and fetal tenofovir exposure during pregnancy, after incorporation of current knowledge on maternal and fetal physiological changes during pregnancy. Predicted concentrations and parameters from the PBPK model were compared to observed data. Predicted tenofovir PK agreed with observations in non-pregnant (13 studies) and pregnant (7 studies with differing gestational weeks) individuals. Observed concentrations fell within the PBPK 5th - 95th prediction intervals. Predicted PK parameters were within twofold of the reported parameters. The predicted tenofovir steady state cord-to-maternal exposure ratio at term was 0.85 (range: 0.62-0.98), which agrees with clinically observed ratios ranging between 0.60-1.00. A PBPK model for tenofovir was constructed and used to simulate the maternal and fetal exposure to tenofovir in virtual pregnant women population at different gestational weeks. Applying a similar approach to other drugs or chemicals may allow exposure prediction and risk assessment in the fetus following maternal administration of drugs or unintended exposure to environmental toxicants.

Optimizing drug therapy during pregnancy: a spotlight on population pharmacokinetic modeling

INTRODUCTION

Optimizing drug therapy during pregnancy is crucial for ensuring the safety of mothers and babiesPhysiological changes that occur during pregnancy can significantly alter the pharmacokinetics of medications. Population pharmacokinetic (PopPK) modeling is a valuable tool to guide drug dosing regimens in pregnant women.

AREAS COVERED

This narrative review summarizes the current literature on the application of PopPK modeling to optimize drug therapy during human pregnancy. It provides an overview of the physiological changes affecting drug disposition in pregnancy and the basic concepts of PopPK modeling including structural, stochastic, and covariate models. We have conducted an exhaustive literature search (PubMed, Web of Science) spanning May 2014-May 2024 to identify PopPK models in the pregnant population. We have highlighted strategies for model building, evaluation, and interpretation with a focus on identifying clinically relevant covariates that inform dose individualization. Case studies illustrating the utility of PopPK models in guiding dosing recommendations for specific drugs are discussed.

EXPERT OPINION

Covariate identification can lead to improved mechanistic understanding of drug disposition and establishment of improved dosing regimens during pregnancy. Insufficient data across trimesters may limit the ability of PopPK models to capture time-varying gestational effects.

Organic anion transporters in remote sensing and organ crosstalk

The organic anion transporters, OAT1 and OAT3, regulate the movement of drugs, toxins, and endogenous metabolites. In 2007, we proposed that OATs and other SLC22 transporters are involved in "remote sensing" and organ crosstalk. This is now known as the Remote Sensing and Signaling Theory (RSST). In the proximal tubule of the kidney, OATs regulate signaling molecules such as fatty acids, bile acids, indoxyl sulfate, kynurenine, alpha-ketoglutarate, urate, flavonoids, and antioxidants. OAT1 and OAT3 function as key hubs in a large homeostatic network involving multi-, oligo- and monospecific transporters, enzymes, and nuclear receptors. The Remote Sensing and Signaling Theory emphasizes the functioning of OATs and other "drug" transporters in the network at multiple biological scales (inter-organismal, organism, organ, cell, organelle). This network plays an essential role in the homeostasis of urate, bile acids, prostaglandins, sex steroids, odorants, thyroxine, gut microbiome metabolites, and uremic toxins. The transported metabolites have targets in the kidney and other organs, including nuclear receptors (e.g., HNF4a, AHR), G protein-coupled receptors (GPCRs), and protein kinases. Feed-forward and feedback loops allow OAT1 and OAT3 to mediate organ crosstalk as well as modulate energy metabolism, redox state, and remote sensing. Furthermore, there is intimate inter-organismal communication between renal OATs and the gut microbiome. Extracellular vesicles containing microRNAs and proteins (exosomes) play a key role in the Remote Sensing and Signaling System as does the interplay with the neuroendocrine, hormonal, and immune systems. Perturbation of function with OAT-interacting drugs (e.g., probenecid, diuretics, antivirals, antibiotics, NSAIDs) can lead to drug-metabolite interactions. The RSST has general applicability to other multi-specific SLC and ABC "drug" transporters (e.g., OCT1, OCT2, SLCO1B1, SLCO1B3, ABCG2, P-gp, ABCC2, ABCC3, ABCC4). Recent high-resolution structures of SLC22 and other transporters, together with chemoinformatic and artificial intelligence methods, will aid drug development and also lead to a deeper mechanistic understanding of polymorphisms.

The effect of pregnancy-related hormones on hepatic transporters: studies with premenopausal human hepatocytes

Introduction

Pregnancy results in significant changes in drug pharmacokinetics (PK). While previous studies have elucidated the impact of pregnancy-related hormones (PRH) on mRNA or protein expression and activity of major hepatic metabolizing enzymes, their effect on hepatic drug transporters remains largely unexplored. Therefore, we investigated the effect of a cocktail of PRH on the mRNA expression and activity of hepatic transporters.

Methods

Plated human hepatocytes (PHH) from 3 premenopausal donors were incubated, in triplicate, for 72 h, with vehicle (DMSO < 0.01%), rifampin (10 μM; positive control) or a cocktail of PRH consisting of estrone, estradiol, estriol, estetrol, progesterone, cortisol, testosterone, oxytocin, and placental growth hormone. The PRH concentrations replicated 0.1×, 1×, or 10× of the plasma concentrations of these hormones observed during each of the three trimesters of pregnancy. After treatment, mRNA expression (quantified by qPCR) of hepatic influx and efflux transporters as well as the activity of influx transporters was quantified (uptake of a selective substrate ± corresponding transporter inhibitor). The data were expressed relative to that in the control (vehicle) group. Significance was evaluated by ANOVA (followed by Dunn's multiple comparisons) or unpaired t-test when the within-lot data were analyzed, or repeated measures ANOVA (followed by Dunn's multiple comparisons) or paired t-test when data from all 3 lots were analyzed (p < 0.05).

Results and Discussion

In general, a) PRH cocktails significantly induced transporter mRNA expression in the following order OAT2 ≈ NTCP ≈ OCT1 > OATP2B1 and repressed mRNA expression in the following order OATP1B3 > OATP1B1; b) these changes translated into significant induction of OAT2 (T1-T3) and NTCP (T2-T3, in only two lots) activity at the 1× PRH concentration. Compared with the influx transporters, the induction of mRNA expression of efflux transporters was modest, with mRNA expression of MRP2 and BSEP being induced the most.

Conclusion

Once these data are verified through in vivo probe drug PK studies in pregnancy, they can be populated into physiologically based pharmacokinetic (PBPK) models to predict, for all trimesters of pregnancy, transporter-mediated clearance of any drug that is a substrate of the affected transporters.

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

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

A Literature Review of Changes in Phase II Drug-Metabolizing Enzyme and Drug Transporter Expression during Pregnancy

The purpose of this literature review is to comprehensively summarize changes in the expression of phase II drug-metabolizing enzymes and drug transporters in both the pregnant woman and the placenta. Using PubMed®, a systematic search was conducted to identify literature relevant to drug metabolism and transport in pregnancy. PubMed was searched with pre-specified terms during the period of 26 May 2023 to 10 July 2023. The final dataset of 142 manuscripts was evaluated for evidence regarding the effect of gestational age and hormonal regulation on the expression of phase II enzymes (n = 16) and drug transporters (n = 38) in the pregnant woman and in the placenta. This comprehensive review exposes gaps in current knowledge of phase II enzyme and drug transporter localization, expression, and regulation during pregnancy, which emphasizes the need for further research. Moreover, the information collected in this review regarding phase II drug-metabolizing enzyme and drug transporter changes will aid in optimizing pregnancy physiologically based pharmacokinetic (PBPK) models to inform dose selection in the pregnant population.

Physiologic Changes During Pregnancy and Impact on Small-Molecule Drugs, Biologic (Monoclonal Antibody) Disposition, and Response

Pregnancy is a unique physiological state that results in many changes in bodily function, including cellular, metabolic, and hormonal changes. These changes can have a significant impact on the way small-molecule drugs and monoclonal antibodies (biologics) function and are metabolized, including efficacy, safety, potency, and adverse effects. In this article, we review the various physiologic changes that occur during pregnancy and their effects on drug and biologic metabolism, including changes in the coagulation, gastrointestinal, renal, endocrine, hepatic, respiratory, and cardiovascular systems. Additionally, we discuss how these changes can affect the processes of drug and biologic absorption, distribution, metabolism, and elimination (pharmacokinetics), and how drugs and biologics interact with biological systems, including mechanisms of drug action and effect (pharmacodynamics) during pregnancy, as well as the potential for drug-induced toxicity and adverse effects in the mother and developing fetus. The article also examines the implications of these changes for the use of drugs and biologics during pregnancy, including consequences of suboptimal plasma drug concentrations, effect of pregnancy on the pharmacokinetics and pharmacodynamics of biologics, and the need for careful monitoring and individualized drug dosing. Overall, this article aims to provide a comprehensive understanding of the physiologic changes during pregnancy and their effects on drug and biologic metabolism to improve the safe and effective use of drugs.

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.

Application of a Physiologically Based Pharmacokinetic Model to Predict Cefazolin and Cefuroxime Disposition in Obese Pregnant Women Undergoing Caesarean Section

Intravenous (IV) cefuroxime and cefazolin are used prophylactically in caesarean sections (CS). Currently, there are concerns regarding sub-optimal dosing in obese pregnant women compared to lean pregnant women prior to CS. The current study used a physiologically based pharmacokinetic (PBPK) approach to predict cefazolin and cefuroxime pharmacokinetics in obese pregnant women at the time of CS as well as the duration that these drug concentrations remain above a target concentration (2, 4 or 8 µg/mL or µg/g) in plasma or adipose tissue. Cefazolin and cefuroxime PBPK models were first built using clinical data in lean and in obese non–pregnant populations. Models were then used to predict cefazolin and cefuroxime pharmacokinetics data in lean and obese pregnant populations. Both cefazolin and cefuroxime models sufficiently described their total and free levels in the plasma and in the adipose interstitial fluid (ISF) in non–pregnant and pregnant populations. The obese pregnant cefazolin model predicted adipose exposure adequately at different reference time points and indicated that an IV dose of 2000 mg can maintain unbound plasma and adipose ISF concentration above 8 µg/mL for 3.5 h post dose. Predictions indicated that an IV 1500 mg cefuroxime dose can achieve unbound plasma and unbound ISF cefuroxime concentration of ≥8 µg/mL up to 2 h post dose in obese pregnant women. Re-dosing should be considered if CS was not completed within 2 h post cefuroxime administration for both lean or obese pregnant if cefuroxime concentrations of ≥8 µg/mL is required. A clinical study to measure cefuroxime adipose concentration in pregnant and obese pregnant women is warranted.

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.

Prediction of Maternal and Fetoplacental Concentrations of Cefazolin, Cefuroxime, and Amoxicillin during Pregnancy Using Bottom-Up Physiologically Based Pharmacokinetic Models

Concerns over maternal and fetal drug exposures highlight the need for a better understanding of drug distribution into the fetus through the placental barrier. This study aimed to predict maternal and fetal drug disposition using physiologically based pharmacokinetic (PBPK) modeling. The detailed maternal-placental-fetal PBPK model within the Simcyp Simulator V20 was used to predict the maternal and fetoplacental exposure of cefazolin, cefuroxime, and amoxicillin during pregnancy and at delivery. The mechanistic dynamic model includes physiologic changes of the maternal, fetal, and placental parameters over the course of pregnancy. Placental kinetics were parametrized using permeability parameters determined from the physicochemical properties of these compounds. Then, the PBPK predictions were compared with the observed data. Fully bottom-up fetoplacental PBPK models were developed for cefuroxime, cefazolin, and amoxicillin without any parameter fitting. Predictions in nonpregnant subjects and in pregnant subjects fall within 2-fold of the observed values. Predictions matched observed pharmacokinetic data reported in nine maternal (five fetoplacental) studies for cefuroxime, 10 maternal (five fetoplacental) studies for cefazolin, and six maternal (two fetoplacental) studies for amoxicillin. Integration of the fetal and maternal system parameters within PBPK models, together with compound-related parameters used to calculate placental permeability, facilitates and extends the applications of the maternal-placental-fetal PBPK model. The developed model can also be used for designing clinical trials and prospectively used for maternal-fetal risk assessment after maternally administered drugs or unintended exposure to environmental toxicants. SIGNIFICANCE STATEMENT: This study investigates the performance of an integrated maternal-placental-fetal PBPK model to predict maternal and fetal tissue exposure of renally eliminated antibiotics that cross the placenta through a passive diffusion mechanism. The transplacental permeability clearance was predicted from the drug physicochemical properties. Results demonstrate that the PBPK approach can facilitate the prediction of maternal and fetal drug exposure simultaneously at any gestational age to support its use in the maternal-fetal exposure assessments.