Drug dosing during pregnancy-opportunities for physiologically based pharmacokinetic models

What Do We Know about Peripartum Cardiomyopathy? Yesterday, Today, Tomorrow

Peripartum cardiomyopathy is a disease that occurs during or after pregnancy and leads to a significant decline in cardiac function in previously healthy women. Peripartum cardiomyopathy has a varying prevalence among women depending on the part of the world where they live, but it is associated with a significant mortality and morbidity in this population. Therefore, timely diagnosis, treatment, and monitoring of this disease from its onset are of utmost importance. Although many risk factors are associated with the occurrence of peripartum cardiomyopathy, such as conditions of life, age of the woman, nutrient deficiencies, or multiple pregnancies, the exact cause of its onset remains unknown. Advances in research on the genetic associations with cardiomyopathies have provided a wealth of data indicating a possible association with peripartum cardiomyopathy, but due to numerous mutations and data inconsistencies, the exact connection remains unclear. Significant insights into the pathophysiological mechanisms underlying peripartum cardiomyopathy have been provided by the theory of an abnormal 16-kDa prolactin, which may be generated in an oxidative stress environment and lead to vascular and consequently myocardial damage. Recent studies supporting this disease mechanism also include research on the efficacy of bromocriptine (a prolactin synthesis inhibitor) in restoring cardiac function in affected patients. Despite significant progress in the research of this disease, there are still insufficient data on the safety of use of certain drugs treating heart failure during pregnancy and breastfeeding. Considering the metabolic changes that occur in different stages of pregnancy and the postpartum period, determining the correct dosing regimen of medications is of utmost importance not only for better treatment and survival of mothers but also for reducing the risk of toxic effects on the fetus.

A User-Driven Framework for Dose Selection in Pregnancy: Proof of Concept for Sertraline

Despite growing knowledge of pregnancy-induced changes in physiology that may alter maternal and fetal pharmacokinetics, evidence-based antenatal doses are lacking for most drugs. Pharmacokinetic modeling and expanding clinical data in pregnancy may support antenatal doses. We aimed to develop and pilot a comprehensive and user-driven Framework for Dose Selection in Pregnancy to support the clinical implementation of a best-evidence antenatal dose for sertraline. After initial development and evaluation by experts, the framework prototype was piloted to formulate an antenatal dosing strategy for sertraline in depression and anxiety disorders. Next, the framework was reviewed and assessed for usability by a multidisciplinary working committee of end-users comprising healthcare practitioners, experts from other disciplines including pharmacometrics, reproductive toxicology and medical ethics, alongside pregnant women and a partner. The resulting framework encompasses the following: rationale for drug selection, a comprehensive analysis of pharmacokinetic and dose-related efficacy and safety data, and implementation aspects including feasibility and desirability of the recommended antenatal dose based on a structured maternal and fetal benefit-risk assessment. An antenatal dose recommendation for sertraline, as a case study, was formulated using this approach and endorsed for clinical use by the working committee. Future applications of the framework for other drugs can further demonstrate its suitability for developing best evidence, acceptable and clinically feasible antenatal doses.

Management of Endocrinopathies During Pregnancy: A Systematic Review

Uncertainty surrounds the efficacy and security of several medications in treating endocrinopathies, such as gestational diabetes mellitus (GDM) in individuals whose normal glucose levels cannot be maintained by diet and exercise alone. To improve pregnancy results for GDM individuals, the present review is conducted to measure the effectiveness of several antidiabetic medications for glucose management. Up until 2024, we looked through PubMed and Google Scholar. Patients with GDM were enrolled in randomized controlled studies that examined several medications. Using the Cochrane risk of bias method, we obtained the pertinent data and evaluated the bias probability. To determine the odds ratio and the surface of the cumulative ranking function of the maternal and neonatal consequences of various therapies in GDM individuals, we first performed pair-wise meta-assessments and subsequently used a systematic review. Macrosomia, higher gestational ages, infant hypoglycemia, and birth weight are the neonatal outcomes. Glycohemoglobin (HbA1c), and pregnancy-induced hypertension (PIH) are the maternal outcomes. This thorough analysis of 25 trial designs found that metformin had fewer cases of macrosomia, higher gestational ages, infant hypoglycemia, and decreased birth weight when compared to glyburide. Metformin was found to be the fastest way to control blood sugar levels in individuals with GDM, whereas glyburide was found to be the most successful medicine for the same purpose.

Willingness-to-use and preferences for model-informed antenatal doses: a cross-sectional study among European healthcare practitioners and pregnant women

Background: Physiological changes in pregnancy may affect drug safety and efficacy, sometimes requiring dose adjustments. Pregnancy-adjusted doses, however, are missing for most medications. Increasingly, pharmacokinetic models can be used for antenatal dose finding. Given the novelty of this technique and questions regarding dose credibility, the acceptability of model-informed antenatal doses should be explored. Objective: We aimed to assess the willingness-to-use and preferred features for model-informed antenatal doses among healthcare practitioners (HCPs) and pregnant women in European countries. Methods: A cross-sectional, web-based study drawing on two open surveys was performed between 8 September and 30 November 2022. Each survey comprised statements drawn from prior focus groups, associated with Likert-scales. Themes included respondents' information needs, search behaviours along with their willingness-to-use and preferred features for model-informed antenatal doses. The surveys were disseminated through professional societies, pregnancy websites and social media. A descriptive analysis was performed. Results: In total, 608 HCPs from different specialties and 794 pregnant women across 15 countries participated, with 81% of respondents across both groups in the Netherlands or Belgium. Among pregnant women, 31% were medical professionals and 85% used medication during pregnancy. Eighty-three percent of HCPs found current antenatal pharmacotherapy suboptimal and 97% believed that model-informed antenatal doses would enhance the quality of antenatal care. Most HCPs (93%) and pregnant women (75%) would be willing to follow model-informed antenatal doses. Most HCPs desired access to the evidence (88%), including from pharmacokinetic modelling (62%). Most pregnant women (96%) wanted to understand antenatal dosing rationales and to be involved in dosing decisions (97%). Conclusion: The willingness-to-use model-informed antenatal doses is high among HCPs and pregnant women provided that certain information needs are met.

Guidelines for assessing maternal cardiovascular physiology during pregnancy and postpartum

Maternal mortality rates are at an all-time high across the world and are set to increase in subsequent years. Cardiovascular disease is the leading cause of death during pregnancy and postpartum, especially in the United States. Therefore, understanding the physiological changes in the cardiovascular system during normal pregnancy is necessary to understand disease-related pathology. Significant systemic and cardiovascular physiological changes occur during pregnancy that are essential for supporting the maternal-fetal dyad. The physiological impact of pregnancy on the cardiovascular system has been examined in both experimental animal models and in humans. However, there is a continued need in this field of study to provide increased rigor and reproducibility. Therefore, these guidelines aim to provide information regarding best practices and recommendations to accurately and rigorously measure cardiovascular physiology during normal and cardiovascular disease-complicated pregnancies in human and animal models.

Perceived barriers and facilitators for model-informed dosing in pregnancy: a qualitative study across healthcare practitioners and pregnant women

BACKGROUND

Most women use medication during pregnancy. Pregnancy-induced changes in physiology may require antenatal dose alterations. Yet, evidence-based doses in pregnancy are missing. Given historically limited data, pharmacokinetic models may inform pregnancy-adjusted doses. However, implementing model-informed doses in clinical practice requires support from relevant stakeholders.

PURPOSE

To explore the perceived barriers and facilitators for model-informed antenatal doses among healthcare practitioners (HCPs) and pregnant women.

METHODS

Online focus groups and interviews were held among healthcare practitioners (HCPs) and pregnant women from eight countries across Europe, Africa and Asia. Purposive sampling was used to identify pregnant women plus HCPs across various specialties prescribing or providing advice on medication to pregnant women. Perceived barriers and facilitators for implementing model-informed doses in pregnancy were identified and categorised using a hybrid thematic analysis.

RESULTS

Fifty HCPs and 11 pregnant women participated in 12 focus groups and 16 interviews between January 2022 and March 2023. HCPs worked in the Netherlands (n = 32), the UK (n = 7), South Africa (n = 5), Uganda (n = 4), Kenya, Cameroon, India and Vietnam (n = 1 each). All pregnant women resided in the Netherlands. Barriers and facilitators identified by HCPs spanned 14 categories across four domains whereas pregnant women described barriers and facilitators spanning nine categories within the same domains. Most participants found current antenatal dosing information inadequate and regarded model-informed doses in pregnancy as a valuable and for some, much-needed addition to antenatal care. Although willingness-to-follow model-informed antenatal doses was high across both groups, several barriers for implementation were identified. HCPs underlined the need for transparent model validation and endorsement of the methodology by recognised institutions. Foetal safety was deemed a critical knowledge gap by both groups. HCPs' information needs and preferred features for model-informed doses in pregnancy varied. Several pregnant women expressed a desire to access information and partake in decisions on antenatal dosing.

CONCLUSIONS

Given the perceived limitations of current pharmacotherapy for pregnant women and foetuses, model-informed dosing in pregnancy was seen as a promising means to enhance antenatal care by pregnant women and healthcare practitioners.

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

Physiological changes during pregnancy can alter maternal and fetal drug exposure. The objective of this work was to predict maternal and umbilical ceftazidime pharmacokinetics during pregnancy. Ceftazidime transplacental permeability was predicted from its physicochemical properties and incorporated into the model. Predicted concentrations and parameters from the PBPK model were compared to the observed data. PBPK predicted ceftazidime concentrations in non-pregnant and pregnant subjects of different gestational weeks were within 2-fold of the observations, and the observed concentrations fell within the 5th-95th prediction interval from the PBPK simulations. The calculated transplacental clearance (0.00137 L/h/mL of placenta volume) predicted an average umbilical cord-to-maternal plasma ratio of 0.7 after the first dose, increasing to about 1.0 at a steady state, which also agrees well with clinical observations. The developed maternal PBPK model adequately predicted the observed exposure and kinetics of ceftazidime in the pregnant population. Using a verified population-based PBPK model provides valuable insights into the disposition of drug concentrations in special individuals that are otherwise difficult to study and, in addition, offers the possibility of supplementing sparse samples obtained in vulnerable populations with additional knowledge, informing the dosing adjustment and study design, and improving the efficacy and safety of drugs in target populations.

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.

Antiretroviral Drug Exposure and Response in Obese and Morbidly Obese People With Human Immunodeficiency Virus (HIV): A Study Combining Modelling and Swiss HIV Cohort Data

BACKGROUND

Obesity is increasingly prevalent among people with HIV (PWH) and can possibly result in suboptimal antiretroviral drug (ARV) exposure and response. However, this has not been thoroughly evaluated given that obese PWH are underrepresented in clinical trials. We performed virtual trials using physiologically based pharmacokinetic (PBPK) modelling combined with observed clinical data to provide ARV dosing guidance in obese individuals.

METHODS

Each trial included a cohort of virtual adults with a body mass index (BMI) between 18.5 and 60 kg/m2. Therapeutic drug-monitoring data from the Swiss HIV Cohort Study (SHCS) were used to verify the predictive performance of the model. Subsequently, the model was applied to predict the pharmacokinetics of ARVs for different obesity classes. The association between ARV plasma concentrations and virological response was investigated in obese and nonobese individuals.

RESULTS

The PBPK model predicted an average reduction in ARV exposure of ∼20% and trough concentrations of ∼6% in obese (BMI ≥30 kg/m2) compared with nonobese (BMI: 18.5-25 kg/m2) individuals, consistent with observed clinical data. Etravirine and rilpivirine were the most impacted, especially in individuals with BMI >40 kg/m2 whose trough concentrations were below the clinical target threshold. Obese PWH in the SHCS did not have a higher rate of unsuppressed viral load than nonobese PWH.

CONCLUSIONS

The concentrations of ARVs are modestly reduced in obese individuals, with no negative impact on the virological response. Our data provide reassurance that standard doses of ARVs are suitable in obese PWH, including those who gained substantial weight with some of the first-line ARVs.

PBPK modeling to predict the pharmacokinetics of pantoprazole in different CYP2C19 genotypes

Pantoprazole is used to treat gastroesophageal reflux disease (GERD), maintain healing of erosive esophagitis (EE), and control symptoms related to Zollinger-Ellison syndrome (ZES). Pantoprazole is mainly metabolized by cytochrome P450 (CYP) 2C19, converting to 4'-demethyl pantoprazole. CYP2C19 is a genetically polymorphic enzyme, and the genetic polymorphism affects the pharmacokinetics and/or pharmacodynamics of pantoprazole. In this study, we aimed to establish the physiologically based pharmacokinetic (PBPK) model to predict the pharmacokinetics of pantoprazole in populations with various CYP2C19 metabolic activities. A comprehensive investigation of previous reports and drug databases was conducted to collect the clinical pharmacogenomic data, physicochemical data, and disposition properties of pantoprazole, and the collected data were used for model establishment. The model was evaluated by comparing the predicted plasma concentration-time profiles and/or pharmacokinetic parameters (AUC and Cmax) with the clinical observation results. The predicted plasma concentration-time profiles in different CYP2C19 phenotypes properly captured the observed profiles. All fold error values for AUC and Cmax were included in the two-fold range. Consequently, the minimal PBPK model for pantoprazole related to CYP2C19 genetic polymorphism was properly established and it can predict the pharmacokinetics of pantoprazole in different CYP2C19 phenotypes. The present model can broaden the insight into the individualized pharmacotherapy for pantoprazole.

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.

Placental Passage of Protopine in an Ex Vivo Human Perfusion System

The placental passage of protopine was investigated with a human ex vivo placental perfusion model. The model was first validated with diazepam and citalopram, 2 compounds known to cross the placental barrier, and antipyrine as a positive control. All compounds were quantified by partially validated U(H)PLC-MS/MS bioanalytical methods. Protopine was transferred from the maternal to the fetal circuit, with a steady-state reached after 90 min. The study compound did not affect placental viability or functionality, as glucose consumption, lactate production, and beta-human chorionic gonadotropin, and leptin release remained constant. Histopathological evaluation of all placental specimens showed unremarkable, age-appropriate parenchymal maturation with no pathologic findings.

Addressing systemic problems with exposure assessments to protect the public's health

BACKGROUND

Understanding, characterizing, and quantifying human exposures to environmental chemicals is critical to protect public health. Exposure assessments are key to determining risks to the general population and for specific subpopulations given that exposures differ between groups. Exposure data are also important for understanding where interventions, including public policies, should be targeted and the extent to which interventions have been successful. In this review, we aim to show how inadequacies in exposure assessments conducted by polluting industries or regulatory agencies have led to downplaying or disregarding exposure concerns raised by communities; that underestimates of exposure can lead regulatory agencies to conclude that unacceptable risks are, instead, acceptable, allowing pollutants to go unregulated; and that researchers, risk assessors, and policy makers need to better understand the issues that have affected exposure assessments and how appropriate use of exposure data can contribute to health-protective decisions.

METHODS

We describe current approaches used by regulatory agencies to estimate human exposures to environmental chemicals, including approaches to address limitations in exposure data. We then illustrate how some exposure assessments have been used to reach flawed conclusions about environmental chemicals and make recommendations for improvements.

RESULTS

Exposure data are important for communities, public health advocates, scientists, policy makers, and other groups to understand the extent of environmental exposures in diverse populations. We identify four areas where exposure assessments need to be improved due to systemic sources of error or uncertainty in exposure assessments and illustrate these areas with examples. These include: (1) an inability of regulatory agencies to keep pace with the increasing number of chemicals registered for use or assess their exposures, as well as complications added by use of 'confidential business information' which reduce available exposure data; (2) the failure to keep assessments up-to-date; (3) how inadequate assumptions about human behaviors and co-exposures contribute to underestimates of exposure; and (4) that insufficient models of toxicokinetics similarly affect exposure estimates.

CONCLUSION

We identified key issues that impact capacity to conduct scientifically robust exposure assessments. These issues must be addressed with scientific or policy approaches to improve estimates of exposure and protect public health.

Optimising Fluvoxamine Maternal/Fetal Exposure during Gestation: A Pharmacokinetic Virtual Clinical Trials Study

Fluvoxamine plasma concentrations have been shown to decrease throughout pregnancy. CYP2D6 polymorphisms significantly influence these changes. However, knowledge of an optimum dose adjustment according to the CYP2D6 phenotype is still limited. This study implemented a physiologically based pharmacokinetic modelling approach to assess the gestational changes in fluvoxamine maternal and umbilical cord concentrations. The optimal dosing strategies during pregnancy were simulated, and the impact of CYP2D6 phenotypes on fluvoxamine maternal and fetal concentrations was considered. A significant decrease in fluvoxamine maternal plasma concentrations was noted during gestation. As for the fetal concentration, a substantial increase was noted for the poor metabolisers (PM), with a constant level in the ultrarapid (UM) and extensive (EM) metabolisers commencing from gestation week 20 to term. The optimum dosing regimen suggested for UM and EM reached a maximum dose of 300 mg daily at gestational weeks (GW) 15 and 35, respectively. In contrast, a stable dose of 100 mg daily throughout gestation for the PM is sufficient to maintain the fluvoxamine plasma concentration within the therapeutic window (60-230 ng/mL). Dose adjustment during pregnancy is required for fluvoxamine, particularly for UM and EM, to maintain efficacy throughout the gestational period.

Pharmacokinetics of the most commonly used antihypertensive drugs throughout pregnancy methyldopa, labetalol, and nifedipine: a systematic review

Purpose

Antihypertensive drugs are among the most prescribed drugs during pregnancy. Methyldopa, labetalol, and nifedipine have been perceived safe to use during pregnancy and are therefore recommended in international guidelines for treatment of hypertension. In this review, we provide a complete overview of what is known on the pharmacokinetics (PK) of the antihypertensive drugs methyldopa, labetalol, and nifedipine throughout pregnancy.

Methods

A systematic search was performed to retrieve studies on the PK of methyldopa, labetalol, and nifedipine used throughout pregnancy. The search was restricted to English and original studies. The systematic search was conducted on July 27, 2021, in Embase, Medline Ovid, Web of Science, Cochrane Library, and Google Scholar. Keywords were methyldopa, labetalol, nifedipine, pharmacokinetics, pregnancy, and placenta.

Results

A total of 1459 unique references were identified of which title and abstract were screened. Based on this screening, 67 full-text papers were assessed, to retain 30 PK studies of which 2 described methyldopa, 12 labetalol, and 16 nifedipine. No fetal accumulation is found for any of the antihypertensive drugs studied.

Conclusion

We conclude that despite decades of prescribing methyldopa, labetalol, and nifedipine throughout pregnancy, descriptions of their PK during pregnancy are hampered by a large heterogeneity in the low number of available studies. Aiming for evidence-based and personalized dosing of antihypertensive medication in the future, further studies on the relationship of both PK and pharmacodynamics (including the optimal blood pressure targeting) during pregnancy and pregnancy-related pathology are urgently needed to prevent undertreatment, overtreatment, and side effects.

Physiologically based pharmacokinetic (PBPK) modeling of flurbiprofen in different CYP2C9 genotypes

The aim of this study was to establish the physiologically based pharmacokinetic (PBPK) model of flurbiprofen related to CYP2C9 genetic polymorphism and describe the pharmacokinetics of flurbiprofen in different CYP2C9 genotypes. PK-Sim® software was used for the model development and validation. A total of 16 clinical pharmacokinetic data for flurbiprofen in different CYP2C9 genotypes, dose regimens, and age groups were used for the PBPK modeling. Turnover number (k_cat) of CYP2C9 values were optimized to capture the observed profiles in different CYP2C9 genotypes. In the simulation, predicted fraction metabolized by CYP2C9, fraction excreted to urine, bioavailability, and volume of distribution were similar to previously reported values. Predicted plasma concentration-time profiles in different CYP2C9 genotypes were visually similar to the observed profiles. Predicted AUC_inf in CYP2C9*1/*2, CYP2C9*1/*3, and CYP2C9*3/*3 genotypes were 1.44-, 2.05-, and 3.67-fold higher than the CYP2C9*1/*1 genotype. The ranges of fold errors for AUC_inf, C_max, and t_1/2 were 0.84-1.00, 0.61-1.22, and 0.74-0.94 in development and 0.59-0.98, 0.52-0.97, and 0.61-1.52 in validation, respectively, which were within the acceptance criterion. Thus, the PBPK model was successfully established and described the pharmacokinetics of flurbiprofen in different CYP2C9 genotypes, dose regimens, and age groups. The present model could guide the decision-making of tailored drug administration strategy by predicting the pharmacokinetics of flurbiprofen in various clinical scenarios.

Physiologically based pharmacokinetic modelling to predict the pharmacokinetics of metoprolol in different CYP2D6 genotypes

Metoprolol, a selective β₁-adrenoreceptor blocking agent used in the treatment of hypertension, angina, and heart failure, is primarily metabolized by the CYP2D6 enzyme, which catalyzes α-hydroxylation and O-desmethylation. As CYP2D6 is genetically highly polymorphic and the enzymatic activity differs greatly depending on the presence of the mutant allele(s), the pharmacokinetic profile of metoprolol is highly variable depending on the genotype of CYP2D6. The aim of study was to develop the physiologically based pharmacokinetic (PBPK) model of metoprolol related to CYP2D6 genetic polymorphism for personalized therapy with metoprolol. For PBPK modelling, our previous pharmacogenomic data were used. To obtain kinetic parameters (K_m, V_max, and CL_int) of each genotype, the recombinant CYP enzyme of each genotype was incubated with metoprolol and metabolic rates were assayed. Based on these data, the PBPK model of metoprolol was developed and validated in different CYP2D6 genotypes using PK-Sim^® software. As a result, the input values for various parameters for the PBPK model were presented and the PBPK model successfully described the pharmacokinetics of metoprolol in each genotype group. The simulated values were within the acceptance criterion (99.998% confidence intervals) compared with observed values. The PBPK model developed in this study can be used for personalized pharmacotherapy with metoprolol in individuals of various races, ages, and CYP2D6 genotypes.

Physiologically based pharmacokinetic (PBPK) modeling of piroxicam with regard to CYP2C9 genetic polymorphism

Piroxicam is a non-steroidal anti-inflammatory drug used to alleviate symptoms of osteoarthritis and rheumatoid arthritis. CYP2C9 genetic polymorphism significantly influences the pharmacokinetics of piroxicam. The objective of this study was to develop and validate the piroxicam physiologically based pharmacokinetic (PBPK) model related to CYP2C9 genetic polymorphism. PK-Sim^® version 10.0 was used for the PBPK modeling. The PBPK model was evaluated by predicted and observed plasma concentration-time profiles, fold errors of predicted to observed pharmacokinetic parameters, and a goodness-of-fit plot. The turnover number (k_cat) of CYP2C9 was adjusted to capture the pharmacokinetics of piroxicam in different CYP2C9 genotypes. The population PBPK model overall accurately described and predicted the plasma concentration-time profiles in different CYP2C9 genotypes. In our simulations, predicted AUC_inf in CYP2C9*1/*2, CYP2C9*1/*3, and CYP2C9*3/*3 genotypes were 1.83-, 2.07-, and 6.43-fold higher than CYP2C9*1/*1 genotype, respectively. All fold error values for AUC, C_max, and t_1/2 were included in the acceptance criterion with the ranges of 0.57-1.59, 0.63-1.39, and 0.65-1.51, respectively. The range of fold error values for predicted versus observed plasma concentrations was 0.11-3.13. 93.9% of fold error values were within the two-fold range. Average fold error, absolute average fold error, and root mean square error were 0.93, 1.27, and 0.72, respectively. Our model accurately captured the pharmacokinetic alterations of piroxicam according to CYP2C9 genetic polymorphism.

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.

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.

Development of a Generic Physiologically-Based Pharmacokinetic Model for Lactation and Prediction of Maternal and Infant Exposure to Ondansetron via Breast Milk

Ondansetron is commonly used in breastfeeding mothers to treat nausea and vomiting. There is limited information in humans regarding safety of ondansetron exposure to nursing infants and no adequate study looking at ondansetron pharmacokinetics during lactation. We developed a generic physiologically-based pharmacokinetic lactation model for small molecule drugs and applied this model to predict ondansetron transfer into breast milk and characterize infant exposure. Drug-specific model inputs were parameterized using data from the literature. Population-specific inputs were derived from a previously conducted systematic literature review of anatomic and physiologic changes in postpartum women. Model predictions were evaluated using ondansetron plasma and breast milk concentration data collected prospectively from 78 women in the Commonly Used Drugs During Lactation and infant Exposure (CUDDLE) study. The final model predicted breast milk and plasma exposures following a single 4 mg dose of intravenous ondansetron in 1,000 simulated women who were 2 days postpartum. Model predictions showed good agreement with observed data. Breast milk median prediction error (MPE) was 18.4% and median absolute prediction error (MAPE) was 53.0%. Plasma MPE was 32.5% and MAPE was 43.2%. The model-predicted daily and relative infant doses were 0.005 mg/kg/day and 3.0%, respectively. This model adequately predicted ondansetron passage into breast milk. The calculated low relative infant dose indicates that mothers receiving ondansetron can safely breastfeed. The model building blocks and population database are open-source and can be adapted to other drugs.

Re-orienting anti-malarial drug development to better serve pregnant women

Malaria is one of the most serious infectious diseases affecting predominantly low- and middle-income countries, where pregnant women are among the populations at risk. There are limited options to prevent or treat malaria in pregnancy, particularly in the first trimester, and existing ones may not work optimally in areas where the threat of drug resistance is rising. As malaria elimination is a key goal of the global health community, the inclusion of pregnant women in the adult population to protect from malaria will be key to achieving success. New, safe, and effective options are needed but it can take decades of evidence-gathering before a medicine is recommended for use in pregnancy. This is because pregnant women are typically not included in pre-registration clinical trials due to fear of causing harm. Data to support dosing and safety in pregnancy are subsequently collected in post-licensure studies. There have been growing calls in recent years that this practice needs to change, amplified by the COVID-19 pandemic and increasing public awareness that newly developed medicines generally cannot be administered to pregnant women from the onset. The development of new anti-malarials should ensure that data informing their use in pregnancy and breastfeeding are available earlier. To achieve this, a mindset change and a different approach to medications for pregnant women are needed. Changes in non-clinical, translational, and clinical approaches in the drug development pathway, in line with recent recommendations from the regulatory bodies are proposed in this Comment. The new approach applies to any malaria-endemic region, regardless of the type of Plasmodium responsible for malaria cases. By incorporating intentional and systematic data collection from pre-registration stages of development through post-licensure, it will be possible to inform on the benefit/risk balance of a new anti-malarial earlier and help ensure that the needs of pregnant individuals are addressed in a more timely and equitable manner in the future.

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.

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

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

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.

Placental Passage of Humulone and Protopine in an Ex Vivo Human Perfusion System

The placental passage of humulone and protopine was investigated with a human ex vivo placental perfusion model. The model was first validated with diazepam and citalopram, 2 compounds known to cross the placental barrier, and antipyrine as a positive control. All compounds were quantified by partially validated U(H)PLC-MS/MS bioanalytical methods. Only a small portion of humulone initially present in the maternal circuit reached the fetal circuit. The humulone concentration in the maternal circuit rapidly decreased, likely due to metabolization in the placenta. Protopine was transferred from the maternal to the fetal circuit, with a steady-state reached after 90 min. None of the study compounds affected placental viability or functionality, as glucose consumption, lactate production, beta-human chorionic gonadotropin, and leptin release remained constant. Histopathological evaluation of all placental specimens showed unremarkable, age-appropriate parenchymal maturation with no pathologic findings.

Sex-Biased Expression of Pharmacogenes across Human Tissues

Individual response to drugs is highly variable and largely influenced by genetic variants and gene-expression profiles. In addition, it has been shown that response to drugs is strongly sex-dependent, both in terms of efficacy and toxicity. To expand current knowledge on sex differences in the expression of genes relevant for drug response, we generated a catalogue of differentially expressed human transcripts encoded by 289 genes in 41 human tissues from 838 adult individuals of the Genotype-Tissue Expression project (GTEx, v8 release) and focused our analysis on relevant transcripts implicated in drug response. We detected significant sex-differentiated expression of 99 transcripts encoded by 59 genes in the tissues most relevant for human pharmacology (liver, lung, kidney, small intestine terminal ileum, skin not sun-exposed, and whole blood). Among them, as expected, we confirmed significant differences in the expression of transcripts encoded by the cytochromes in the liver, CYP2B6, CYP3A7, CYP3A5, and CYP1A1. Our systematic investigation on differences between male and female in the expression of drug response-related genes, reinforce the need to overcome the sex bias of clinical trials.

Physiologically based pharmacokinetic modelling in pregnancy: Model reproducibility and external validation

AIMS

Physiologically based pharmacokinetic (PBPK) models have been previously developed for betamethasone and buprenorphine for pregnant women. The goal of this work was to replicate and reassess these models using data from recently completed studies.

METHODS

Betamethasone and buprenorphine PBPK models were developed in Simcyp V19 based on prior publications using V17 and V15. Ability to replicate models was verified by comparing predictions in V19 to those previously published. Once replication was verified, models were reassessed by comparing predictions to observed data from additional studies in pregnant women. Model performance was based upon visual inspection of concentration vs. time profiles, and comparison of pharmacokinetic parameters. Models were deemed reproducible if parameter estimates were within 10% of previously reported values. External validations were considered acceptable if the predicted area under the concentration-time curve (AUC) and peak plasma concentration fell within 2-fold of the observed.

RESULTS

The betamethasone model was successfully replicated using Simcyp V19, with ratios of reported (V17) to reproduced (V19) peak plasma concentration of 0.98-1.04 and AUC of 0.95-1.07. The model-predicted AUC ratios ranged from 0.98-1.79 compared to external data. The previously published buprenorphine PBPK model was not reproducible, as we predicted intravenous clearance of 70% that reported previously (both in Simcyp V15).

CONCLUSION

While high interstudy variability was observed in the newly available clinical data, the PBPK model sufficiently predicted changes in betamethasone exposure across gestation. Model reproducibility and reassessment with external data are important for the advancement of the discipline. PBPK modelling publications should contain sufficient detail and clarity to enable reproducibility.

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.

The application of precision dosing in the use of sertraline throughout pregnancy for poor and ultrarapid metabolizer CYP 2C19 subjects: A virtual clinical trial pharmacokinetics study

Sertraline is known to undergo changes in pharmacokinetics during pregnancy. CYP 2C19 has been implicated in the interindividual variation in clinical effect associated with sertraline activity. However, knowledge of suitable dose titrations during pregnancy and within CYP 2C19 phenotypes is lacking. A pharmacokinetic modeling virtual clinical trials approach was implemented to: (i) assess gestational changes in sertraline trough plasma concentrations for CYP 2C19 phenotypes, and (ii) identify appropriate dose titration strategies to stabilize sertraline levels within a defined therapeutic range throughout gestation. Sertraline trough plasma concentrations decreased throughout gestation, with maternal volume expansion and reduction in plasma albumin being identified as possible causative reasons. All CYP 2C19 phenotypes required a dose increase throughout gestation. For extensive metabolizer (EM) and ultrarapid metabolizer (UM) phenotypes, doses of 100-150 mg daily are required throughout gestation. For poor metabolizers (PM), 50 mg daily during trimester 1 followed by a dose of 100 mg daily in trimesters 2 and 3 are required.

The Pharmacodynamics of Antipsychotic Drugs in Women and Men

Background: Animal and human experiments have confirmed sex differences in the expression of hepatic enzymes that metabolize antipsychotic drugs and that may, in this way, be partly responsible for the clinical sex/gender differences observed in the efficacy and tolerability of antipsychotic treatment. Aim: The aim of this mini review is to synthesize the literature on the pharmacodynamics of male/female differential response to antipsychotic drugs. Method: Relevant search terms were used to search for pre-clinical and human trials and analysis of antipsychotic differential drug response and occurrence/severity of adverse effects in women and men. Results: The search found that sex influences drug response via the amount of a given drug that enters the brain and the number of neurotransmitter receptors to which it can bind. Consequently, sex partly determines the efficacy of a specific drug and its liability to induce unwanted effects. There are other factors that can overshadow or enhance the dimorphic effect of sex, for instance, the host's age, hormonal status, diet and life style as well as the molecular structure of the drug and its dose, and the method of its administration. Most of all, the host's individual genetics affects each step of a drug's pharmacodynamics. Conclusion: On average, women's psychotic symptoms respond to antipsychotic drugs at doses lower than men's. This means that many women may be de facto overdosed and, thus, experience unnecessary adverse effects. That being said, factors such as genetics and age probably determine drug response and tolerability to a greater degree than do biological sex or gender social roles.