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The article discusses the challenges of drug exposure to fetuses and infants during pregnancy and lactation, leading to the exclusion of pregnant and lactating women from clinical trials. Regulatory initiatives like the Diversity Action Plan and E21 Efficacy Guidelines aim to increase inclusion in clinical studies. Pharmacometrics and systems pharmacology play a crucial role in making studies more inclusive and optimizing drug therapy for pregnant and lactating women. The article highlights the importance of robust data on drug exposure, non-clinical safety data, and quantitative applications to inform drug therapy decisions for pregnant and lactating women. [Extracted from the article]

Optimal dosing in pregnant and lactating women requires an understanding of the pharmacokinetics in the mother, fetus, and breastfed infant. Physiologically‐based pharmacokinetic (PBPK) modeling can be used to simulate untested scenarios and hence supplement clinical data to support dosing decisions. A PBPK model for the antiretroviral dolutegravir (mainly metabolized by UGT1A1) was verified using reported exposures in non‐pregnant healthy volunteers, pregnant women, and the umbilical cord, lactating mothers, and breastfed neonates. The model was then applied to predict the impact of UGT1A1 phenotypes in extensive (EM), poor (PM), and ultra‐rapid metabolizers (UM). The predicted dolutegravir maternal plasma and umbilical cord AUC in UGT1A1 PMs was 1.6‐fold higher than in EMs. The predicted dolutegravir maternal plasma and umbilical cord AUC in UGT1A1 UMs mothers was 1.3‐fold lower than in EMs. The predicted mean systemic and umbilical vein concentrations were in excess of the dolutegravir IC90 at 17, 28, and 40 gestational weeks, regardless of UGT1A1 phenotype, indicating that the standard dose of dolutegravir (50 mg q.d., fed state) is generally appropriate in late pregnancy, across UGT1A1 phenotypes. Applying the model in breastfed infants, a 1.5‐, 1.7‐, and 2.2‐fold higher exposure in 2‐day‐old neonates, 10‐day‐old neonates, and infants who were UGT1A1 PMs, respectively, compared with EMs of the same age. However, it should be noted that the exposure in breastfed infants who were UGT1A1 PMs was still an order of magnitude lower than maternal exposure with a relative infant daily dose of <2%, suggesting safe use of dolutegravir in breastfeeding women. [ABSTRACT FROM AUTHOR]

The article discusses the challenges of using medicines during pregnancy due to limited clinical data and the need for a clinical pharmacology extrapolation framework to support pregnancy drug development strategies. It highlights the regulatory landscape, the impact of pregnancy-related physiological changes on drug exposure, and the importance of including pregnant women in clinical trials. The article emphasizes the need for an extrapolation approach to generate data in pregnancy, focusing on mother and fetal safety management, study design, and labeling updates. Additionally, it suggests using model-informed drug development (MIDD) approaches, such as physiologically-based pharmacokinetic (PBPK) modeling, to predict drug exposure and inform dosing decisions during pregnancy. [Extracted from the article]

In breastfeeding mothers, managing medical conditions presents unique challenges, particularly concerning medication use and breastfeeding practices. The transfer of drugs into breast milk and subsequent exposure to nursing infants raises important considerations for drug safety and efficacy. Modeling approaches are increasingly employed to predict infant exposure levels, crucial for assessing drug safety during breastfeeding. Physiologically‐based pharmacokinetic (PBPK) modeling provides a valuable tool for predicting drug exposure in lactating individuals and their infants. This tutorial offers an overview of PBPK modeling in lactation research, covering key concepts, prediction approaches, and best practices for model development and application. We delve into milk composition dynamics and its influence on drug transfer into breast milk, addressing modeling considerations, knowledge gaps, and future research directions. Practical examples and case studies illustrate PBPK modeling application in lactation studies. We demonstrate how prediction algorithms for Milk‐to‐Plasma (M/P) ratios within a PBPK framework can support scenarios lacking clinical lactation data or extend the utility of available lactation clinical data to support further untested clinical scenarios. This tutorial aims to assist researchers and clinicians in understanding and applying PBPK modeling to understand and support clinical scenarios in breastfeeding mothers. Advances in PBPK modeling techniques, along with ongoing research on lactation physiology and drug disposition, promise further insights into drug transfer during lactation. [ABSTRACT FROM AUTHOR]

Model‐informed drug development (MIDD) is a powerful quantitative approach that plays an integral role in drug development and regulatory review. While applied throughout the life cycle of the development of new drugs, a key application of MIDD is to inform clinical trial design including dose selection and optimization. To date, physiologically‐based pharmacokinetic (PBPK) modeling, an established component of the MIDD toolkit, has mainly been used for assessment of drug–drug interactions (DDIs) and consequential dose adjustments in regulatory submissions. As a result of recent scientific advances and growing confidence in the utility of the approach, PBPK models are being increasingly applied to provide dose recommendations for subjects with differing ages, genetics, and disease states. In this review, we present our perspective on the current landscape of regulatory acceptance of PBPK applications supported by relevant case studies. We also discuss the recent progress and future challenges associated with expanding the utility of PBPK models into emerging areas for regulatory decision making, especially dose optimization in highly vulnerable and understudied populations and facilitating diversity in clinical trials. [ABSTRACT FROM AUTHOR]

Moxidectin is approved by the US Food and Drug Administration (US FDA) for the treatment of onchocerciasis (river-blindness) due to Onchocerca volvulus in patients aged 12 years and older. In onchocerciasis-endemic areas, mass drug administration (MDA) programs with ivermectin, with or without vector control, aim to control the disease, reduce morbidity, interrupt transmission, and more recently, achieve elimination. Moxidectin has the potential to be used in MDA programs. In countries where onchocerciasis is endemic, infants are often breastfed up to the age of 2 years, suggesting that some women are likely to be lactating during such periodic MDA programs. Quantitative analyses of non-clinical and clinical data using non-compartmental analysis and population based pharmacokinetic (popPK) modeling as well as physiologically based pharmacokinetic modeling (PBPK) were performed to determine the amount of moxidectin excreted in breast milk and subsequent exposures in the infant. The results of the analyses were similar. Concentrations of moxidectin in breast milk followed a similar pattern to those in plasma, with maximum concentrations occurring approximately 4 hours after dosing followed by a rapid decline in both breast milk and plasma. As early as two days after dosing, concentrations of moxidectin in breast milk were below the threshold for acceptable daily intake levels established by the European Medicines Agency (EMA) and FDA for secondary exposures from veterinary use, and below the WHO recommended relative infant dose (RID) safety threshold. The analyses were conducted to support prescribers and policy makers on dosing recommendations for moxidectin in lactation. Author summary: Moxidectin is approved to treat onchocerciasis or "river-blindness". For years, mass drug administration programs (MDA) involving at least annual treatment of entire populations within a geographical area have been used as a strategy to control onchocerciasis. The potential treatment population therefore includes pregnant and breast-feeding women. Guidance on the safe and effective use of medicines in these populations is needed but is often insufficient. In this study, we describe two methods to determine the amount of moxidectin administered to breastfeeding infants via breastmilk. Both methods used data from a clinical study in which moxidectin levels were measured in the blood and breast milk of lactating women. In an empirical analysis, the amount of moxidectin in a breast-fed infant was inferred based on observed blood and breast milk levels in the clinical study. Using a physiologically based pharmacokinetic (PBPK) model approach, which considers all prior information on the drug and the physiological variability involved, direct assessments of the amount of drug in the infant were estimated. Both methods established the likely time-course and level of moxidectin exposure in infants via breast milk, highlighting the benefit of an integrated approach to generate dosing recommendations supporting the use of moxidectin in breastfeeding women. [ABSTRACT FROM AUTHOR]

Real‐world data (RWD) and real‐world evidence (RWE) are now being routinely used in epidemiology, clinical practice, and post‐approval regulatory decisions. Despite the increasing utility of the methodology and new regulatory guidelines in recent years, there remains a lack of awareness of how this approach can be applied in clinical pharmacology and translational research settings. Therefore, the American Society of Clinical Pharmacology & Therapeutics (ASCPT) held a workshop on March 21st, 2023 entitled "Advancing the Utilization of Real‐World Data (RWD) and Real‐World Evidence (RWE) in Clinical Pharmacology and Translational Research." The work described herein is a summary of the workshop proceedings. [ABSTRACT FROM AUTHOR]

A physiologically‐based pharmacokinetic (PBPK) model was developed to simulate plasma concentrations of tucatinib (TUKYSA®) after single‐dose or multiple‐dose administration of 300 mg b.i.d. orally. This PBPK model was subsequently applied to support evaluation of drug–drug interaction (DDI) risk as a perpetrator resulting from tucatinib inhibition of CYP3A4, CYP2C8, CYP2C9, P‐gp, or MATE1/2‐K. The PBPK model was also applied to support evaluation of DDI risk as a victim resulting from co‐administration with CYP3A4 or CYP2C8 inhibitors, or a CYP3A4 inducer. After refinement with clinical DDI data, the final PBPK model was able to recover the clinically observed single and multiple‐dose plasma concentrations for tucatinib when tucatinib was administered as a single agent in healthy subjects. In addition, the final model was able to recover clinically observed plasma concentrations of tucatinib when administered in combination with itraconazole, rifampin, or gemfibrozil as well as clinically observed plasma concentrations of probe substrates of CYP3A4, CYP2C8, CYP2C9, P‐gp, or MATE1/2‐K. The PBPK model was then applied to prospectively predict the potential perpetrator or victim DDIs with other substrates, inducers, or inhibitors. To simulate a potential interaction with a moderate CYP2C8 inhibitor, two novel PBPK models representing a moderate CYP2C8 inhibitor and a sensitive CYP2C8 substrate were developed based on the existing PBPK models for gemfibrozil and rosiglitazone, respectively. The simulated population geometric mean area under the curve ratio of tucatinib with a moderate CYP2C8 inhibitor ranged from 1.98‐ to 3.08‐fold, and based on these results, no dose modifications were proposed for moderate CYP2C8 inhibitors for the tucatinib label. [ABSTRACT FROM AUTHOR]

Imatinib is mainly metabolised by CYP3A4 and CYP2C8 and is extensively bound to α-acid glycoprotein (AAG). A physiologically based pharmacokinetic (PBPK) model for imatinib describing the CYP3A4-mediated autoinhibition during multiple dosing in gastrointestinal stromal tumor patients with normal renal function was previously reported. After performing additional verification, the PBPK model was applied to predict the exposure of imatinib after multiple dosing in cancer patients with varying degrees of renal impairment. In agreement with the clinical data, there was a positive correlation between AAG levels and imatinib exposure. A notable finding was that for recovery of the observed data in cancer patients with moderate RI (CrCL 20 to 39 mL/min), reductions of hepatic CYP3A4 and CYP2C8 abundances, which reflect the effects of RI, had to be included in the simulations. This was not the case for mild RI (CrCL 40 to 50 mL/min). The results support the finding of the clinical study, which demonstrated that both AAG levels and the degree of renal impairment are key components that contribute to the interpatient variability associated with imatinib exposure. As indicated in the 2020 FDA draft RI guidance, PBPK modelling could be used to support an expanded inclusion of patients with RI in clinical studies. [ABSTRACT FROM AUTHOR]

Robust prediction of pharmacokinetics (PKs) in pediatric subjects of diverse ages, ethnicities, and morbidities is critical. Qualification of pediatric physiologically‐based pharmacokinetic (P‐PBPK) models is an essential step toward enabling precision dosing of these vulnerable groups. Twenty‐two manuscripts involving P‐PBPK predictions and corresponding observed PK data (e.g., area under the curve and clearance) for 22 small‐molecule compounds metabolized by CYP (3A4, 1A2, and 2C9), UGT (1A9 and 2B7), FMO3, renal, non‐renal, and complex routes were identified; ratios of mean predicted/observed (P/O) PK parameters were calculated. Seventy‐eight of 115 mean predicted PK parameters were within 0.8 to 1.25‐fold of observed data, 98 within 0.67 to 1.5‐fold, 109 within 2‐fold, and only 6 P/O ratios were outside of these bounds. A set of 12 CYP3A4‐metabolized compounds and a set of 6 metabolized by other enzymes, CYP1A2 (1 compound), CYP2C9 (2 compounds), UGT1A9 (1 compound) and UGT2B7 (2 compounds) had 56 of 59 and 22 of 25 mean P/O ratios, respectively, that fell within the > 0.5 and < 2.0‐fold boundaries. For compounds covering renal, non‐renal, complex, and FM03 routes of elimination, 29 of 31 mean P/O ratios fell within the 0.67 to 1.5‐fold bounds, including 4 of 5 P/O ratios from newborns. P‐PBPK modeling and simulation is a strategic component of the complement of precision dosing methods and has a vital role to play in dose adjustment in vulnerable pediatric populations, such as those with disease or in different ethnic groups. Qualification of such models is an essential step toward acceptance of this methodology by regulators. [ABSTRACT FROM AUTHOR]

Abstract MDMA (3-4-methylenedioxymethamphetamine, commonly known as Ecstasy) is a potent mechanism-based inhibitor (MBI) of cytochrome P450 2D6 (CYP2D6), causing quasi-irreversible inhibition of the enzyme in vitro. An evaluation of the [...]