Application of physiologically based pharmacokinetic modeling to predict drug disposition in pregnant populations

Simultaneously Predicting the Pharmacokinetics of CES1-Metabolized Drugs and Their Metabolites Using Physiologically Based Pharmacokinetic Model in Cirrhosis Subjects

Hepatic carboxylesterase 1 (CES1) metabolizes numerous prodrugs into active ingredients or direct-acting drugs into inactive metabolites. We aimed to develop a semi-physiologically based pharmacokinetic (semi-PBPK) model to simultaneously predict the pharmacokinetics of CES1 substrates and their active metabolites in liver cirrhosis (LC) patients. Six prodrugs (enalapril, benazepril, cilazapril, temocapril, perindopril and oseltamivir) and three direct-acting drugs (flumazenil, pethidine and remimazolam) were selected. Parameters such as organ blood flows, plasma-binding protein concentrations, functional liver volume, hepatic enzymatic activity, glomerular filtration rate (GFR) and gastrointestinal transit rate were integrated into the simulation. The pharmacokinetic profiles of these drugs and their active metabolites were simulated for 1000 virtual individuals. The developed semi-PBPK model, after validation in healthy individuals, was extrapolated to LC patients. Most of the observations fell within the 5th and 95th percentiles of simulations from 1000 virtual patients. The estimated AUC and Cmax were within 0.5-2-fold of the observed values. The sensitivity analysis showed that the decreased plasma exposure of active metabolites due to the decreased CES1 was partly attenuated by the decreased GFR. Conclusion: The developed PBPK model successfully predicted the pharmacokinetics of CES1 substrates and their metabolites in healthy individuals and LC patients, facilitating tailored dosing of CES1 substrates in LC patients.

Investigating Tacrolimus Disposition in Paediatric Patients with a Physiologically Based Pharmacokinetic Model Incorporating CYP3A4 Ontogeny, Mechanistic Absorption and Red Blood Cell Binding

Tacrolimus is a crucial immunosuppressant for organ transplant patients, requiring therapeutic drug monitoring due to its variable exposure after oral intake. Physiologically based pharmacokinetic (PBPK) modelling has provided insights into tacrolimus disposition in adults but has limited application in paediatrics. This study investigated age dependency in tacrolimus exposure at the levels of absorption, metabolism, and distribution. Based on the literature data, a PBPK model was developed to predict tacrolimus exposure in adults after intravenous and oral administration. This model was then extrapolated to the paediatric population, using a unique reference dataset of kidney transplant patients. Selecting adequate ontogeny profiles for hepatic and intestinal CYP3A4 appeared critical to using the model in children. The best model performance was achieved by using the Upreti ontogeny in both the liver and intestines. To mechanistically evaluate the impact of absorption on tacrolimus exposure, biorelevant in vitro solubility and dissolution data were obtained. A relatively fast and complete release of tacrolimus from its amorphous formulation was observed when mimicking adult or paediatric dissolution conditions (dose, fluid volume). In both the adult and paediatric PBPK models, the in vitro dissolution profiles could be adequately substituted by diffusion-layer-based dissolution modelling. At the level of distribution, sensitivity analysis suggested that differences in blood plasma partitioning of tacrolimus may contribute to the variability in exposure in paediatric patients.

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.

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

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

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.

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.

Drug-drug interaction comparison between tacrolimus and phenobarbital in different formulations for paediatrics and adults

To compare drug-drug interaction (DDI) between tacrolimus and different formulations of phenobarbital in paediatrics and adults.Physiologically based pharmacokinetics (PBPK) models were used to evaluate DDI between phenobarbital (oral (p.o.) and intravenous (i.v.) formulations) and tacrolimus in paediatrics and adults. All dosing regimens were maintained for 7 days.Compared to i.v. phenobarbital, p.o. phenobarbital could decrease pharmacokinetic (PK) parameters of tacrolimus much more in both paediatrics and adults. On day 7, the results showed that the ratio of C_max for tacrolimus in the presence and absence of phenobarbital were 0.13 (p.o.) and 0.48 (i.v.), respectively, in paediatrics, while 0.54 (p.o.) and 0.73 (i.v.) in adults, respectively. The ratios of the area under the concentration-time curve (AUC) were 0.06 (p.o.) and 0.18 (i.v.) in paediatrics, while 0.46 (p.o.) and 0.53 (i.v.) in adults, respectively. PK parameters of tacrolimus decreased more significantly in paediatrics compared to adults.In paediatric, phenobarbital had a greater impact on PK of tacrolimus than that in adults. P.o. phenobarbital reduced PK parameters of tacrolimus even more than i.v. administration. In clinical practice, the concentration monitoring and dosage adjustment of tacrolimus should be emphasised when co-administrated with phenobarbital, especially in paediatric or in p.o. formulation.Key pointsThe results indicated that p.o. and i.v. phenobarbital both had a significant DDI with tacrolimus in paediatrics and adults.Phenobarbital had a greater impact on the PK of tacrolimus over time in paediatrics.P.o. administration of phenobarbital can reduce the PK parameters of tacrolimus more.

Prediction of maternal and fetal pharmacokinetics of indomethacin in pregnancy

AIMS

Indomethacin is used for the treatment of preterm labour, short cervices and idiopathic polyhydramnios during pregnancy. Few studies have described the pharmacokinetics (PK) of indomethacin during pregnancy. This study aimed to determine maternal and fetal PK of indomethacin during different trimesters of pregnancy using physiologically based PK (PBPK) modelling and simulations.

METHODS

Full PBPK simulations were performed in nonpregnant subjects and pregnant subjects from each trimester of pregnancy at steady state using Simcyp's healthy volunteers and pregnancy PBPK model, respectively. The fetal exposures were predicted using a fetoplacental pregnancy PBPK model. The models were verified by comparing PBPK-based predictions with observed PK profiles.

RESULTS

Predicted exposure (AUC_0-6h ) and clearance of indomethacin in nonpregnant women and pregnant women are similar to the clinical observations. AUC_0-6h of indomethacin is approximately 14, 24 and 32% lower, consistent with 18, 34 and 52% higher clearance in the first, second and third trimesters of pregnancy, respectively, compared to nonpregnant women. Predicted fetal plasma exposures increased by approximately 30% from the second trimester to the third trimester of pregnancy.

CONCLUSION

A mechanistic PBPK model adequately described the maternal and the fetal PK of indomethacin during pregnancy. As the pregnancy progresses, a modest decrease (≤32%) in systemic exposures in pregnant women and a 33% increase in fetal exposures to indomethacin were predicted. Higher fetal exposures in the third trimester of pregnancy may pose safety risks to the fetus. Additional studies are warranted to understand the exposure-response relationship and provide appropriate dosing recommendations during pregnancy that consider both safety and efficacy.

Precision dosing of methadone during pregnancy: A pharmacokinetics virtual clinical trials study

BACKGROUND

Methadone use for the management of opioid dependency during pregnancy is commonplace. Methadone levels are altered during pregnancy due to changes in maternal physiology. Despite this, a paucity of data exist regarding the most appropriate optimal dosing regimens during pregnancy.

METHODS

This study applied a pharmacokinetic modeling approach to examine gestational changes in R- and S-methadone concentrations in maternal plasma and fetal (cord) blood. This study did so to derive a theoretical optimal dosing regimen during pregnancy, and to identify the impact of Cytochromes P450 (CYP) 2B6 and 2C19 polymorphisms on methadone maternal and fetal pharmacokinetics.

RESULTS

The study noted significant decreases in maternal R- and S-methadone plasma concentrations during gestation, with concomitant increases in fetal levels. At a dose of 90 mg once daily, 75% (R-) and 94% (S-) of maternal methadone trough levels were below the lower therapeutic window at term (week 40). The developed optimal dosing regimen escalated doses to 110 mg by week 5, followed by 10 mg increments every 5 weeks up to a maximum of 180 mg once daily near term. This increase resulted in 27% (R-) and 11% (S-) of subjects with trough levels below the lower therapeutic window at term. CYP2B6 poor metabolizers (PM) and either CYP2C19 extensive metabolizers (EM), PM, or ultra-rapid (UM) metabolizer phenotypes demonstrated statistically significant increases in concentrations when compared to their matched CYP2B6 EM counterparts.

CONCLUSIONS

Specific and gestation-dependent dose titrations are required during pregnancy to reduce the risks associated with illicit drug use and to maintain fetal safety.

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

Background and Objective

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

Methods

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

Results

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

Conclusion

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

Electronic supplementary material

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

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.

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

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

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

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

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.

Precision dosing-based optimisation of paroxetine during pregnancy for poor and ultrarapid CYP2D6 metabolisers: a virtual clinical trial pharmacokinetics study

Objective

Paroxetine has been demonstrated to undergo gestation-related reductions in plasma concentrations, to an extent which is dictated by the polymorphic state of CYP 2D6. However, knowledge of appropriate dose titrations is lacking.

Methods

A pharmacokinetic modelling approach was applied to examine gestational changes in trough plasma concentrations for CYP 2D6 phenotypes, followed by necessary dose adjustment strategies to maintain paroxetine levels within a therapeutic range of 20–60 ng/ml.

Key findings

A decrease in trough plasma concentrations was simulated throughout gestation for all phenotypes. A significant number of ultrarapid (UM) phenotype subjects possessed trough levels below 20 ng/ml (73–76%) compared to extensive metabolisers (EM) (51–53%).

Conclusions

For all phenotypes studied, there was a requirement for daily doses in excess of the standard 20 mg dose throughout gestation. For EM, a dose of 30 mg daily in trimester 1 followed by 40 mg daily in trimesters 2 and 3 is suggested to be optimal. For poor metabolisers (PM), a 20 mg daily dose in trimester 1 followed by 30 mg daily in trimesters 2 and 3 is suggested to be optimal. For UM, a 40 mg daily dose throughout gestation is suggested to be optimal.

Simulation of the Pharmacokinetics of Oseltamivir and Its Active Metabolite in Normal Populations and Patients with Hepatic Cirrhosis Using Physiologically Based Pharmacokinetic Modeling

Oseltamivir is a neuraminidase inhibitor widely used to treat and prevent influenza A and B infections, although its safety and pharmacokinetics have not been evaluated in patients with severe hepatic impairment. A physiologically based pharmacokinetic (PBPK) model of the prodrug oseltamivir and its active metabolite, oseltamivir carboxylate (OC), was established and validated to simulate their disposition in adults and predict the exposure in patients with Child-Pugh C cirrhosis (CP-C). The simulated results from PBPK modeling and the observed data after oral administration of various oseltamivir regimens were consistent according to the fold error values of less than 2. Furthermore, the clinical observations published in the literature were comparable with our pharmacokinetic predictions. In patients with CP-C, the oseltamivir C_max was approximately 2-fold increased, and its AUC was approximately 6-fold higher compared with those in normal subjects. In contrast, the AUC of OC in CP-C patients did not differ significantly from that in normal subjects, whereas its C_max was reduced by approximately 30% in the patients. Examination of drug exposure in different health conditions indicated that the oseltamivir exposure was significantly increased in conditions with elevated cirrhosis severity, which might be associated with a higher risk of adverse drug effects, e.g., neuropsychiatric adverse events (NPAEs). In conclusion, the pharmacokinetics of oseltamivir and OC were correctly predicted by PBPK modeling. The model further predicted that the pharmacokinetics of oseltamivir might be altered in liver cirrhosis, depending on the degree of severity.

Quetiapine dose optimisation during gestation: a pharmacokinetic modelling study

Objectives

The second-generation antipsychotic quetiapine has been demonstrated to undergo gestation-related changes in pharmacokinetics. This study applied pharmacokinetic modelling principles to investigate the mechanism of these changes and to propose new dosing strategies to counteract these changes.

Methods

A pharmacokinetic modelling approach was implemented using virtual population groups. Changes in quetiapine trough plasma concentration during gestation were quantified across all trimesters, and dose adjustment strategies were applied to counteract these changes by targeting a therapeutic range of 50–500 ng/ml throughout gestation.

Key findings

The application of the model during gestation predicted a decrease in trough concentration. A maximum decrease of 58% was predicted during trimester 2, and being associated with a statistically significant decrease in oral clearance at gestation week 25, 204 l/h ± 100.8 l/h compared with non-pregnant subjects, 121.9 l/h ± 51.8 l/h. A dosing optimisation strategy identified that dose increases to 500–700 mg twice daily would result in 32–55% of subjects possessing trough concentration in excess of 50 ng/ml.

Conclusions

Quetiapine doses in pregnancy should be increased to 500–700 mg twice daily to counteract a concomitant increase in metabolic clearance, increase in volume of distribution and decrease in plasma protein binding.

Pharmacokinetics of oseltamivir phosphate and oseltamivir carboxylate in non-pregnant and pregnant rhesus monkeys

Oseltamivir is an antiviral drug approved to treat influenza in humans. Although the dosing regimen of this drug is well established for non-pregnant patients, it is not clear if the significant physiological alterations associated with pregnancy affect the pharmacokinetics of oseltamivir and, thus, warrant different dosing regimens to assure efficacy. In this study, we investigated the suitability of rhesus macaques as an animal model for studying oseltamivir pharmacokinetics during all trimesters of pregnancy in comparison to pre-pregnant conditions. Specifically, we compared the pharmacokinetics of oseltamivir and its pharmacologically active metabolite oseltamivir carboxylate in rhesus monkeys after intravenous and nasogastric administration of 2.5 mg oseltamivir phosphate/kg body weight given prior to and during the first, second, and third trimesters of pregnancy. Pregnancy had only a modest effect upon the pharmacokinetic parameters of oseltamivir and oseltamivir carboxylate. Monkeys treated intravenously in the third trimester had a reduction in Vd and CL, compared to non-pregnant monkeys. These changes did not occur in the other two trimesters. Pregnant monkeys treated intravenously had 20-25% decrease in AUC_0-∞ of oseltamivir carboxylate and a corresponding increase in Vd and CL. Pregnant monkeys treated nasogastrically with oseltamivir phosphate demonstrated a pattern that recapitulated intravenous dosing. Taken together these data indicate that rhesus monkeys are an acceptable model for studying drug-pregnancy interactions.

Physiologically-based pharmacokinetics of ziprasidone in pregnant women

AIMS

Pregnancy is associated with physiological changes that alter the pharmacokinetics (PK) of drugs. The aim of this study was to predict the PK of ziprasidone in pregnant women.

METHODS

A full physiologically-based pharmacokinetic (PBPK) model of ziprasidone was developed and validated for the non-pregnant population (healthy adults, paediatrics, geriatrics), and this was extended to the pregnant state to assess the change in PK profile of ziprasidone throughout pregnancy.

RESULTS

The PBPK model successfully predicted the ziprasidone disposition in healthy adult volunteers, wherein the predicted and observed AUC, C_max and t_max were within the fold-difference of 0.94-1.09, 0.89-1.40 and 0.80-1.08, respectively. The paediatric and geriatric population, also showed predicted AUC, C_max and t_max within a two-fold range of the observed values. The simulated exposure in pregnant women using a p-PBPK model showed no significant difference when compared to non-pregnant women.

CONCLUSIONS

The PBPK model predicted the impact of physiological changes during pregnancy on PK and exposure of ziprasidone, suggesting that dose adjustment is not necessary in this special population.

Physiologically Based Pharmacokinetic/Pharmacodynamic Model for Caffeine Disposition in Pregnancy

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

Gestational changes in buprenorphine exposure: A physiologically-based pharmacokinetic analysis

AIMS

Buprenorphine (BUP) is approved by the US Food and Drug Administration for the treatment of opioid addiction. The current dosing regimen of BUP in pregnant women is based on recommendations designed for nonpregnant adults. However, physiological changes during pregnancy may alter BUP exposure and efficacy. The objectives of this study were to develop a physiologically-based pharmacokinetic (PBPK) model for BUP in pregnant women, to predict changes in BUP exposure at different stages of pregnancy, and to demonstrate the utility of PBPK modelling in optimizing BUP pharmacotherapy during pregnancy.

METHODS

A full PBPK model for BUP was initially built and validated in healthy subjects. A fetoplacental compartment was included as a combined compartment in this model to simulate pregnancy induced anatomical and physiological changes. Further, gestational changes in physiological parameters were incorporated in this model. The PBPK model predictions of BUP exposure in pregnancy and during the postpartum period were compared to published data from a prospective clinical study.

RESULTS

The predicted BUP plasma concentration-time profiles in the virtual pregnant populations are consistent with the observed data in the 2nd and 3rd trimesters, and the postpartum period. The differences in the predicted means of dose normalized area under the plasma drug concentration-time curve up to 12 h, average concentration and maximum concentration were within ±25% of the corresponding observed means with the exception of average concentration in the 3rd trimester (-26.3%).

CONCLUSION

PBPK model-based simulation may be a useful tool to optimize BUP pharmacotherapy during pregnancy, obviating the need to perform pharmacokinetic studies in each trimester and the postpartum period that normally require intensive blood sampling.

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

During recent years there has been a surge in developing and applying physiologically based pharmacokinetic (PBPK) models in pregnant women to better understand and predict changes in drug pharmacokinetics throughout pregnancy. As a consequence, the number of publications focusing on pregnancy PBPK models has increased substantially. However, to date these models, especially across various platforms, have not been systematically evaluated. Hence, this review aims to assess published PBPK models in pregnancy used for therapeutic purposes.

Drug Dosing in Pregnant Women: Challenges and Opportunities in Using Physiologically Based Pharmacokinetic Modeling and Simulations

The unmet medical need of providing evidence‐based pharmacotherapy for pregnant women is recognized by the regulatory bodies. Physiologically based pharmacokinetic (PBPK) modeling offers an attractive platform to quantify anticipated changes in the pharmacokinetics (PKs) of drugs during pregnancy. Recent publications applying a pregnancy PBPK module to the prediction of maternal and fetal exposure of drugs are summarized. Future opportunities to use PBPK models to predict breast milk exposure and assess human fetotoxicity risks are presented.

Translational Systems Pharmacology Studies in Pregnant Women

Pregnancy involves rapid physiological adaptation and complex interplay between mother and fetus. New analytic technologies provide large amounts of genomic, proteomic, and metabolomics data. The integration of these data through bioinformatics, statistical, and systems pharmacology techniques can improve our understanding of the mechanisms of normal maternal physiologic changes and fetal development. New insights into the mechanisms of pregnancy‐related disorders, such as preterm birth (PTB), may lead to the development of new therapeutic interventions and novel biomarkers.