When special populations intersect with drug-drug interactions: Application of physiologically-based pharmacokinetic modeling in pregnant populations

A close examination of BCRP's role in lactation and methods for predicting drug distribution into milk

Breastfeeding is the most complete nutritional method of feeding infants, but several impediments affect the decision to breastfeed, including questions of drug safety for medications needed during lactation. Despite recent FDA guidance, few labels provide clear dosing advice during lactation. Physiologically based pharmacokinetic modeling (PBPK) is well suited to mechanistically explore pharmacokinetics and dosing paradigms to fill gaps in the absence of extensive clinical studies and complement existing real-world data. For lactation-focused PBPK (Lact-PBPK) models, information on system parameters (e.g., expression of drug transporters in mammary epithelial cells) is sparse. The breast cancer resistance protein (BCRP) is expressed on the apical side of mammary epithelial cells where it actively transports drugs/substrates into milk (reported milk: plasma ratios range from 2 to 20). A critical review of BCRP and its role in lactation was conducted. Longitudinal changes in BCRP mRNA expression have been identified in women with a maximum reached around 5 months postpartum. Limited data are available on the ontogeny of BCRP in infant intestine; however, data indicate lower BCRP abundance in infants compared to adults. Current status of incorporation of drug transporter information in Lact-PBPK models to predict active secretion of drugs into breast milk and consequential exposure of breast-fed infants is discussed. In addition, this review highlights novel clinical tools for evaluation of BCRP activity, namely a potential non-invasive BCRP biomarker (riboflavin) and liquid biopsy that could be used to quantitatively elucidate the role of this transporter without the need for administration of drugs and to inform Lact-PBPK models.

Placental Drug Delivery to Treat Pre-Eclampsia and Fetal Growth Restriction

Pre-eclampsia and fetal growth restriction (FGR) continue to cause unacceptably high levels of morbidity and mortality, despite significant pharmaceutical and technological advances in other disease areas. The recent pandemic has also impacted obstetric care, as COVID-19 infection increases the risk of poor pregnancy outcomes. This review explores the reasons why it lacks effective drug treatments for the placental dysfunction that underlies many common obstetric conditions and describes how nanomedicines and targeted drug delivery approaches may provide the solution to the current drug drought. The ever-increasing range of biocompatible nanoparticle formulations available is now making it possible to selectively deliver drugs to uterine and placental tissues and dramatically limit fetal drug transfer. Formulations that are refractory to placental uptake offer the possibility of retaining drugs within the maternal circulation, allowing pregnant individuals to take medicines previously considered too harmful to the developing baby. Liposomes, ionizable lipid nanoparticles, polymeric nanoparticles, and adenoviral vectors have all been used to create efficacious drug delivery systems for use in pregnancy, although each approach offers distinct advantages and limitations. It is imperative that recent advances continue to be built upon and that there is an overdue investment of intellectual and financial capital in this field.

Do birth outcomes mediate the association between drug use in pregnancy and neonatal metabolic bone disease? A prospective cohort study of 10,801 Chinese women

Background

Prenatal drug use may cause toxicity to bone health in newborns. We aimed to examine whether birth outcomes mediate the association between medication use and neonatal metabolic bone disease (MBD).

Methods

A prospective cohort of 10,801 pregnant women (17-49 years) and their infants followed at a single center from 1 January 2012 to 31 December 2021 were included. Based on four single drugs, comprehensive medication use was determined and categorized into three groups using latent-class analysis: group 1 included antibiotics and furosemide or less than two drugs except for MgSO4; group 2 included MgSO4 without antibiotics or furosemide; and group 3 encompassed dexamethasone and antibiotics. Mediation analysis was conducted to assess the mediating effects of prematurity, low birth weight (LBW), and small for gestational age (SGA).

Results

There were 138 (1.3%) infants with MBD; 2,701 (25%) were born preterm, 1717 (15.9%) had LBW, and 303 (2.8%) were SGA. Pregnant women in groups 2 and 3 were 2.52 to 14.66 times more likely to deliver an infant with MBD than those in group 1. Only LBW showed a significant mediating effect on the association between comprehensive medication use and MBD, with a mediation proportion of 51.8% (45.0-64.1%, p < 0.001).

Conclusion

Comprehensive medication use during pregnancy was associated with an increased risk of neonatal MBD, largely mediated by LBW. Early antepartum monitoring and prevention targeting adverse birth outcomes are necessary to mitigate the risk of MBD.

Safety and Efficacy of Antiviral Drugs and Vaccines in Pregnant Women: Insights from Physiologically Based Pharmacokinetic Modeling and Integration of Viral Infection Dynamics

Addressing the complexities of managing viral infections during pregnancy is essential for informed medical decision-making. This comprehensive review delves into the management of key viral infections impacting pregnant women, namely Human Immunodeficiency Virus (HIV), Hepatitis B Virus/Hepatitis C Virus (HBV/HCV), Influenza, Cytomegalovirus (CMV), and SARS-CoV-2 (COVID-19). We evaluate the safety and efficacy profiles of antiviral treatments for each infection, while also exploring innovative avenues such as gene vaccines and their potential in mitigating viral threats during pregnancy. Additionally, the review examines strategies to overcome challenges, encompassing prophylactic and therapeutic vaccine research, regulatory considerations, and safety protocols. Utilizing advanced methodologies, including PBPK modeling, machine learning, artificial intelligence, and causal inference, we can amplify our comprehension and decision-making capabilities in this intricate domain. This narrative review aims to shed light on diverse approaches and ongoing advancements, this review aims to foster progress in antiviral therapy for pregnant women, improving maternal and fetal health outcomes.

Mechanistic Modeling of the Drug-Drug Interaction Between Efavirenz and Dolutegravir: Is This Interaction Clinically Relevant When Switching From Efavirenz to Dolutegravir During Pregnancy?

Following the 2021 World Health Organization's updated recommendations on the management of HIV infection, millions of people living with HIV are currently switched from efavirenz-based antiretroviral therapy to dolutegravir-based antiretroviral therapy. Pregnant individuals transitioning from efavirenz to dolutegravir might be at increased risk of insufficient viral suppression in the immediate postswitch period because both efavirenz- and pregnancy-related increases in hormone levels induce enzymes involved in dolutegravir metabolism, namely, cytochrome P450 3A4 and uridine 5'-diphospho-glucuronosyltransferase 1A1. This study aimed at developing physiologically based pharmacokinetic models to simulate the switch from efavirenz to dolutegravir in the late second and third trimester. To this end, the drug-drug interaction between efavirenz and the uridine 5'-diphospho-glucuronosyltransferase 1A1 substrates dolutegravir and raltegravir was first simulated in nonpregnant subjects. After successful validation, the physiologically based pharmacokinetic models were translated to pregnancy and dolutegravir pharmacokinetics following efavirenz discontinuation were predicted. Modeling results indicated that, at the end of the second trimester, both efavirenz concentrations and dolutegravir trough concentrations fell below respective pharmacokinetic target thresholds (defined as reported thresholds producing 90%-95% of the maximum effect) during the time interval from 9.75 to 11 days after dolutegravir initiation. At the end of the third trimester, this time interval spanned from 10.3 days to >4 weeks after dolutegravir initiation. These findings suggest that dolutegravir exposure in the immediate post-efavirenz switch period during pregnancy may be suboptimal, leading to HIV viremia and, potentially, resistance. The clinical implications of these findings remain to be substantiated by future studies.

The investigation of the complex population-drug-drug interaction between ritonavir-boosted lopinavir and chloroquine or ivermectin using physiologically-based pharmacokinetic modeling

OBJECTIVES

Therapy failure caused by complex population-drug-drug (PDDI) interactions including CYP3A4 can be predicted using mechanistic physiologically-based pharmacokinetic (PBPK) modeling. A synergy between ritonavir-boosted lopinavir (LPVr), ivermectin, and chloroquine was suggested to improve COVID-19 treatment. This work aimed to study the PDDI of the two CYP3A4 substrates (ivermectin and chloroquine) with LPVr in mild-to-moderate COVID-19 adults, geriatrics, and pregnancy populations.

METHODS

The PDDI of LPVr with ivermectin or chloroquine was investigated. Pearson's correlations between plasma, saliva, and lung interstitial fluid (ISF) levels were evaluated. Target site (lung epithelial lining fluid [ELF]) levels of ivermectin and chloroquine were estimated.

RESULTS

Upon LPVr coadministration, while the chloroquine plasma levels were reduced by 30, 40, and 20%, the ivermectin plasma levels were increased by a minimum of 425, 234, and 453% in adults, geriatrics, and pregnancy populations, respectively. The established correlation equations can be useful in therapeutic drug monitoring (TDM) and dosing regimen optimization.

CONCLUSIONS

Neither chloroquine nor ivermectin reached therapeutic ELF levels in the presence of LPVr despite reaching toxic ivermectin plasma levels. PBPK modeling, guided with TDM in saliva, can be advantageous to evaluate the probability of reaching therapeutic ELF levels in the presence of PDDI, especially in home-treated patients.

Predicting transporter mediated drug-drug interactions via static and dynamic physiologically based pharmacokinetic modeling: A comprehensive insight on where we are now and the way forward

The greater utilization and acceptance of physiologically-based pharmacokinetic (PBPK) modeling to evaluate the potential metabolic drug-drug interactions is evident by the plethora of literature, guidance's, and regulatory dossiers available in the literature. In contrast, it is not widely used to predict transporter-mediated DDI (tDDI). This is attributed to the unavailability of accurate transporter tissue expression levels, the absence of accurate in vitro to in vivo extrapolations (IVIVE), enzyme-transporter interplay, and a lack of specific probe substrates. Additionally, poor understanding of the inhibition/induction mechanisms coupled with the inability to determine unbound concentrations at the interaction site made tDDI assessment challenging. Despite these challenges, continuous improvements in IVIVE approaches enabled accurate tDDI predictions. Furthermore, the necessity of extrapolating tDDI's to special (pediatrics, pregnant, geriatrics) and diseased (renal, hepatic impaired) populations is gaining impetus and is encouraged by regulatory authorities. This review aims to visit the current state-of-the-art and summarizes contemporary knowledge on tDDI predictions. The current understanding and ability of static and dynamic PBPK models to predict tDDI are portrayed in detail. Peer-reviewed transporter abundance data in special and diseased populations from recent publications were compiled, enabling direct input into modeling tools for accurate tDDI predictions. A compilation of regulatory guidance's for tDDI's assessment and success stories from regulatory submissions are presented. Future perspectives and challenges of predicting tDDI in terms of in vitro system considerations, endogenous biomarkers, the use of empirical scaling factors, enzyme-transporter interplay, and acceptance criteria for model validation to meet the regulatory expectations were discussed.

Developing New Treatments for COVID-19 through Dual-Action Antiviral/Anti-Inflammatory Small Molecules and Physiologically Based Pharmacokinetic Modeling

Broad-spectrum antiviral agents that are effective against many viruses are difficult to develop, as the key molecules, as well as the biochemical pathways by which they cause infection, differ largely from one virus to another. This was more strongly highlighted by the COVID-19 pandemic, which found health systems all over the world largely unprepared and proved that the existing armamentarium of antiviral agents is not sufficient to address viral threats with pandemic potential. The clinical protocols for the treatment of COVID-19 are currently based on the use of inhibitors of the inflammatory cascade (dexamethasone, baricitinib), or inhibitors of the cytopathic effect of the virus (monoclonal antibodies, molnupiravir or nirmatrelvir/ritonavir), using different agents. There is a critical need for an expanded armamentarium of orally bioavailable small-molecular medicinal agents, including those that possess dual antiviral and anti-inflammatory (AAI) activity that would be readily available for the early treatment of mild to moderate COVID-19 in high-risk patients. A multidisciplinary approach that involves the use of in silico screening tools to identify potential drug targets of an emerging pathogen, as well as in vitro and in vivo models for the determination of a candidate drug’s efficacy and safety, are necessary for the rapid and successful development of antiviral agents with potentially dual AAI activity. Characterization of candidate AAI molecules with physiologically based pharmacokinetics (PBPK) modeling would provide critical data for the accurate dosing of new therapeutic agents against COVID-19. This review analyzes the dual mechanisms of AAI agents with potential anti-SARS-CoV-2 activity and discusses the principles of PBPK modeling as a conceptual guide to develop new pharmacological modalities for the treatment of COVID-19.

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

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

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

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