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As detailed information on the pharmacokinetics (PK) of labetalol in pregnant people are lacking, the aims of this study were: (1) to build a physiologically based PK (PBPK) model of labetalol in non-pregnant individuals that incorporates different CYP2C19 genotypes (specifically, *1/*1, *1/*2 or *3, *2/*2, and *17/*17); (2) to translate this model to the second and third trimester of pregnancy; and (3) to combine the model with a previously published direct pharmacodynamic (PD) model to predict the blood pressure lowering effect of labetalol in the third trimester. Clinical data for model evaluation was obtained from the scientific literature. In non-pregnant populations, the mean ratios of simulated versus observed peak concentration (Cmax), time to reach Cmax (Tmax), and exposure (area under the plasma concentration-time curve, AUC) were 0.94, 0.82, and 1.16, respectively. The pregnancy PBPK model captured the observed PK adequately, but clearance was slightly underestimated with mean ratios of simulated versus observed Cmax, Tmax, and AUC of 1.28, 1.30, and 1.39, respectively. The results suggested that pregnant people with CYP2C19 *2/*2 alleles have similar labetalol exposure and trough levels compared to non-pregnant controls, whereas those with other alleles were found to have increased exposure and trough concentrations. Importantly, the pregnancy PBPK/PD model predicted that, despite increased exposure in some genotypes, the blood pressure lowering effect was broadly comparable across all genotypes. In view of the large inter-individual variability and the potentially increasing blood pressure during pregnancy, patients may need to be closely monitored for achieving optimal therapeutic effects and avoiding adverse events.
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This Article shares the proceedings from the August 29th, 2023 (day 1) workshop "Physiologically Based Biopharmaceutics Modeling (PBBM) Best Practices for Drug Product Quality: Regulatory and Industry Perspectives". The focus of the day was on model parametrization; regulatory authorities from Canada, the USA, Sweden, Belgium, and Norway presented their views on PBBM case studies submitted by industry members of the IQ consortium. The presentations shared key questions raised by regulators during the mock exercise, regarding the PBBM input parameters and their justification. These presentations also shed light on the regulatory assessment processes, content, and format requirements for future PBBM regulatory submissions. In addition, the day 1 breakout presentations and discussions gave the opportunity to share best practices around key questions faced by scientists when parametrizing PBBMs. Key questions included measurement and integration of drug substance solubility for crystalline vs amorphous drugs; impact of excipients on apparent drug solubility/supersaturation; modeling of acid-base reactions at the surface of the dissolving drug; choice of dissolution methods according to the formulation and drug properties with a view to predict the in vivo performance; mechanistic modeling of in vitro product dissolution data to predict in vivo dissolution for various patient populations/species; best practices for characterization of drug precipitation from simple or complex formulations and integration of the data in PBBM; incorporation of drug permeability into PBBM for various routes of uptake and prediction of permeability along the GI tract.
Subject(s)
Biopharmaceutics , Models, Biological , Biopharmaceutics/methods , Humans , Solubility , Pharmaceutical Preparations/chemistry , Excipients/chemistry , Chemistry, Pharmaceutical/methodsABSTRACT
Since the Open Source Initiative laid the foundation for the open source software environment in 1998, the popularity of free and open source software has been steadily increasing. Model-informed drug discovery and development (MID3), a key component of pharmaceutical research and development, heavily makes use of computational models which can be developed using various software including the Open Systems Pharmacology (OSP) software (PK-Sim/MoBi), a free and open source software tool for physiologically based pharmacokinetic (PBPK) modeling. In this study, we aimed to investigate the impact, application areas, and reach of the OSP software as well as the relationships and collaboration patterns between organizations having published OSP-related articles between 2017 and 2023. Therefore, we conducted a bibliometric analysis of OSP-related publications and a social network analysis of the organizations with which authors of OSP-related publications were affiliated. On several levels, we found evidence for a significant growth in the size of the OSP community as well as its visibility in the MID3 community since OSP's establishment in 2017. Specifically, the annual publication rate of PubMed-indexed PBPK-related articles using the OSP software outpaced that of PBPK-related articles using any software. Our bibliometric analysis and network analysis demonstrated that the expansion of the OSP community was predominantly driven by new authors and organizations without prior connections to the community involving the generation of research clusters de novo and an overall diversification of the network. These findings suggest an ongoing evolution of the OSP community toward a more segmented, diverse, and inclusive network.
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Nickel carbonite complexes supported by alkaline earth metals have been accessed via salt-metathesis of the corresponding alkali metal precursors. The new complexes undergo Schlenk-like exchange reactions in solution which have been investigated by NMR spectroscopy. Also their reactivity towards epoxides and carbon monoxide was studied.
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Obstetric subjects represent a special population in pharmacology [...].
ABSTRACT
The concomitant administration of ritonavir and oxycodone may significantly increase the plasma concentrations of oxycodone. This study was aimed to simulate DDI between ritonavir and oxycodone, a widely used opioid, and to formulate dosing protocols for oxycodone by using physiologically based pharmacokinetic (PBPK) modeling. We developed a ritonavir PBPK model incorporating induction and competitive and time-dependent inhibition of CYP3A4 and competitive inhibition of CYP2D6. The ritonavir model was evaluated with observed clinical pharmacokinetic data and validated for its CYP3A4 inhibition potency. We then used the model to simulate drug interactions between oxycodone and ritonavir under various dosing scenarios. The developed model captured the pharmacokinetic characteristics of ritonavir from clinical studies. The model also accurately predicts exposure changes of midazolam, triazolam, and oxycodone in the presence of ritonavir. According to model simulations, the steady-state maximum, minimum and average concentrations of oxycodone increased by up to 166% after co-administration with ritonavir, and the total exposure increased by approximately 120%. To achieve similar steady-state concentrations, halving the dose with an unchanged dosing interval or doubling the dosing interval with an unaltered single dose should be practical for oxycodone, whether formulated in uncoated or controlled-release tablets during long-term co-medication with ritonavir. The results revealed exposure-related risks of oxycodone-ritonavir interactions that have not been studied clinically and emphasized PBPK as a workable method to direct judicious dosage.
Subject(s)
Oxycodone , Ritonavir , Ritonavir/pharmacokinetics , Oxycodone/pharmacokinetics , Cytochrome P-450 CYP3A , Midazolam/pharmacokinetics , Drug Interactions , Models, BiologicalABSTRACT
Nilotinib is a second-generation BCR-ABL tyrosine kinase inhibitor for the treatment of Philadelphia chromosome-positive chronic myeloid leukemia in both adult and pediatric patients. The pharmacokinetics (PK) of nilotinib in specific populations such as pregnant and lactating people remain poorly understood. Therefore, the objectives of the current study were to develop a physiologically based pharmacokinetic (PBPK) model to predict nilotinib PK in virtual drug-drug interaction (DDI) studies, as well as in pediatric, pregnant, and lactating populations. The nilotinib PBPK model was built in PK-Sim, which is part of the free and open-source software Open Systems Pharmacology. The observed clinical data for the validation of the nilotinib models were obtained from the literature. The model reasonably predicted nilotinib concentrations in the adult population; the DDIs between nilotinib and rifampin or ketoconazole in the adult population; and the PK in the pediatric, pregnant, and lactating populations, although in the latter 2 populations plasma concentrations were slightly underestimated. The ratio of predicted versus observed PK parameters for the adult model ranged from 0.71 to 1.11 for area under the concentration-time curve and 0.55 to 0.95 for maximum concentration. For the DDI, the predicted area under the concentration-time curve ratio and maximum concentration ratio fell within the Guest criterion. The current study demonstrated the utility of using PBPK modeling to understand the mechanistic basis of PK differences between adults and specific populations, such as pediatrics, and pregnant and lactating individuals, indicating that this technology can potentially inform or optimize dosing conditions in specific populations.
Subject(s)
Lactation , Models, Biological , Adult , Female , Pregnancy , Humans , Child , Computer Simulation , Drug Interactions , PyrimidinesABSTRACT
Vericiguat (Verquvo; US: Merck, other countries: Bayer) is a novel drug for the treatment of chronic heart failure. Preclinical studies have demonstrated that the primary route of metabolism for vericiguat is glucuronidation, mainly catalyzed by uridine diphosphate-glucuronosyltransferase (UGT)1A9 and to a lesser extent UGT1A1. Whereas a drug-drug interaction (DDI) study of the UGT1A9 inhibitor mefenamic acid showed a 20% exposure increase, the effect of UGT1A1 inhibitors has not been assessed clinically. This modeling study describes a physiologically-based pharmacokinetic (PBPK) approach to complement the clinical DDI liability assessment and support prescription labeling. A PBPK model of vericiguat was developed based on in vitro and clinical data, verified against data from the mefenamic acid DDI study, and applied to assess the UGT1A1 DDI liability by running an in silico DDI study with the UGT1A1 inhibitor atazanavir. A minor effect with an area under the plasma concentration-time curve (AUC) ratio of 1.12 and a peak plasma concentration ratio of 1.04 was predicted, which indicates that there is no clinically relevant DDI interaction anticipated. Additionally, the effect of potential genetic polymorphisms of UGT1A1 and UGT1A9 was evaluated, which showed that an average modest increase of up to 1.7-fold in AUC may be expected in the case of concomitantly reduced UGT1A1 and UGT1A9 activity for subpopulations expressing non-wild-type variants for both isoforms. This study is a first cornerstone to qualify the PK-Sim platform for use of UGT-mediated DDI predictions, including PBPK models of perpetrators, such as mefenamic acid and atazanavir, and sensitive UGT substrates, such as dapagliflozin and raltegravir.
Subject(s)
Glucuronosyltransferase , Heterocyclic Compounds, 2-Ring , Mefenamic Acid , Pyrimidines , Humans , Atazanavir Sulfate , Glucuronosyltransferase/metabolism , Drug InteractionsABSTRACT
BACKGROUND AND OBJECTIVE: Physiologically based pharmacokinetic (PBPK) models for pregnant women have recently been successfully used to predict maternal and umbilical cord pharmacokinetics (PK). Because there is very limited opportunity for conducting clinical and PK investigations for fetal drug exposure, PBPK models may provide further insights. The objectives of this study were to extend a whole-body pregnancy PBPK model by multiple compartments representing fetal organs, and to predict the PK of cefuroxime in the maternal and fetal plasma, the amniotic fluid, and several fetal organs. METHODS: To this end, a previously developed pregnancy PBPK model for cefuroxime was updated using the open-source software Open Systems Pharmacology (PK-Sim®/MoBi®). Multiple compartments were implemented to represent fetal organs including brain, heart, liver, lungs, kidneys, the gastrointestinal tract (GI), muscles, and fat tissue, as well as another compartment lumping organs and tissues not explicitly represented. RESULTS: This novel PBPK model successfully predicted cefuroxime concentrations in maternal blood, umbilical cord, amniotic fluid, and several fetal organs including heart, liver, and lungs. Further model validation with additional clinical PK data is needed to build confidence in the model. CONCLUSIONS: Being developed with an open-source software, the presented generic model can be freely re-used and tailored to address specific questions at hand, e.g., to assist the design of clinical studies in the context of drug research or to predict fetal organ concentrations of chemicals in the context of fetal health risk assessment.
Subject(s)
Cefuroxime , Models, Biological , Humans , Pregnancy , Female , Software , Amniotic Fluid , MusclesABSTRACT
In the past, rifampicin was well-established as strong index CYP3A inducer in clinical drug-drug interaction (DDI) studies. However, due to identified potentially genotoxic nitrosamine impurities, it should not any longer be used in healthy volunteer studies. Available clinical data suggest carbamazepine as an alternative to rifampicin as strong index CYP3A4 inducer in clinical DDI studies. Further, physiologically-based pharmacokinetic (PBPK) modeling is a tool with increasing importance to support the DDI risk assessment of drugs during drug development. CYP3A4 induction properties and the safety profile of carbamazepine were investigated in two open-label, fixed sequence, crossover clinical pharmacology studies in healthy volunteers using midazolam as a sensitive index CYP3A4 substrate. Carbamazepine was up-titrated from 100 mg twice daily (b.i.d.) to 200 mg b.i.d., and to a final dose of 300 mg b.i.d. for 10 consecutive days. Mean area under plasma concentration-time curve from zero to infinity (AUC(0-∞)) of midazolam consistently decreased by 71.8% (ratio: 0.282, 90% confidence interval (CI): 0.235-0.340) and 67.7% (ratio: 0.323, 90% CI: 0.256-0.407) in study 1 and study 2, respectively. The effect was adequately described by an internally developed PBPK model for carbamazepine which has been made freely available to the scientific community. Further, carbamazepine was safe and well-tolerated in the investigated dosing regimen in healthy participants. The results demonstrated that the presented design is appropriate for the use of carbamazepine as alternative inducer to rifampicin in DDI studies acknowledging its CYP3A4 inductive potency and safety profile.
Subject(s)
Midazolam , Rifampin , Humans , Rifampin/adverse effects , Midazolam/pharmacokinetics , Cytochrome P-450 CYP3A , Drug Interactions , Models, Biological , Carbamazepine/adverse effects , Cytochrome P-450 CYP3A Inhibitors/pharmacologyABSTRACT
Due to the strong tendency towards poorly soluble drugs in modern development pipelines, enabling drug formulations such as amorphous solid dispersions, cyclodextrins, co-crystals and lipid-based formulations are frequently applied to solubilize or generate supersaturation in gastrointestinal fluids, thus enhancing oral drug absorption. Although many innovative in vitro and in silico tools have been introduced in recent years to aid development of enabling formulations, significant knowledge gaps still exist with respect to how best to implement them. As a result, the development strategy for enabling formulations varies considerably within the industry and many elements of empiricism remain. The InPharma network aims to advance a mechanistic, animal-free approach to the assessment of drug developability. This commentary focuses current status and next steps that will be taken in InPharma to identify and fully utilize 'best practice' in vitro and in silico tools for use in physiologically based biopharmaceutic models.
Subject(s)
Body Fluids , Cyclodextrins , Biopharmaceutics , Solubility , Administration, OralABSTRACT
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.
Subject(s)
HIV Infections , Female , Pregnancy , Humans , HIV Infections/drug therapy , Benzoxazines , Drug Interactions , GlucuronosyltransferaseABSTRACT
Sickle cell anemia (SCA) is a life-threatening genetic condition contributing to high-risk pregnancies affecting both the mother and fetus. With improved management of children with SCA, this life-threatening hematological disorder has evolved into a chronic disease of adults, and consequently parenthood has now become a possible and important life goal for many patients. Providing continuous management with healthy red blood cell function and avoiding SCA-associated complications, such as pain crises, acute chest syndrome, and stroke, are crucial for a healthy pregnancy. Despite its excellent safety profile in non-pregnant adults and children, and based on theoretical concerns derived from data using animal models and supraphysiological dosing, hydroxyurea is currently contraindicated for pregnant and lactating women with SCA. Clinical experience of hydroxyurea use during pregnancy is increasingly reported, however, and has shown inconsistent results of fetal or infant adverse effects. How the hydroxyurea exposure level may correlate with pregnancy outcomes is still unclear. Accordingly, efforts should be made to systemically evaluate exposure and safety of hydroxyurea treatment during pregnancy and lactation. Novel approaches such as physiologically based pharmacokinetic (PBPK) modeling, coupled with the ex vivo human placental cotyledon perfusion assay, provide opportunities to understand hydroxyurea exposure not only in pregnant women but also in the developing fetus. Combined with animal data, research using these approaches might be able to define safe and effective hydroxyurea dosing regimens for pregnant and lactating women with SCA, when the benefits of continuing hydroxyurea treatment likely outweigh the risks of non-treatment, by avoiding substantial morbidity and even mortality for both mothers and infants.
Subject(s)
Anemia, Sickle Cell , Hydroxyurea , Child , Infant , Adult , Animals , Female , Humans , Pregnancy , Hydroxyurea/adverse effects , Antisickling Agents/adverse effects , Lactation , Placenta , Anemia, Sickle Cell/drug therapy , Anemia, Sickle Cell/complicationsABSTRACT
Developmental neurotoxicity (DNT) is a potential hazard of chemicals. Recently, an in vitro testing battery (DNT IVB) was established to complement existing rodent in vivo approaches. Deltamethrin (DLT), a pyrethroid with a well-characterized neurotoxic mode of action, has been selected as a reference chemical to evaluate the performance of the DNT IVB. The present study provides context for evaluating the relevance of these DNT IVB results for the human health risk assessment of DLT by estimating potential human fetal brain concentrations after maternal exposure to DLT. We developed a physiologically based kinetic (PBK) model for rats which was then translated to humans considering realistic in vivo exposure conditions (acceptable daily intake [ADI] for DLT). To address existing uncertainties, we designed case studies considering the most relevant drivers of DLT uptake and distribution. Calculated human fetal brain concentrations were then compared with the lowest benchmark concentration achieved in the DNT IVB. The developed rat PBK model was validated on in vivo rat toxicokinetic data of DLT over a broad range of doses. The uncertainty based case study evaluation confirmed that repeated exposure to DLT at an ADI level would likely result in human fetal brain concentrations far below the in vitro benchmark. The presented results indicate that DLT concentrations in the human fetal brain are highly unlikely to reach concentrations associated with in vitro findings under realistic exposure conditions. Therefore, the new in vitro DNT results are considered to have no impact on the current risk assessment approach.
Subject(s)
Neurotoxicity Syndromes , Pyrethrins , Female , Humans , Rats , Animals , Pyrethrins/toxicity , Neurotoxicity Syndromes/etiology , Nitriles/toxicity , Risk AssessmentABSTRACT
Pregnant individuals are at high risk for severe illness from COVID-19, and there is an urgent need to identify safe and effective therapeutics for this population. Remdesivir (RDV) is a SARS-CoV-2 nucleotide analog RNA polymerase inhibitor. Limited RDV pharmacokinetic (PK) and safety data are available for pregnant women receiving RDV. The aims of this study were to translate a previously published nonpregnant adult physiologically based PK (PBPK) model for RDV to pregnancy and evaluate model performance with emerging clinical PK data in pregnant women with COVID-19. The pregnancy model was built in the Open Systems Pharmacology software suite (Version 10) including PK-Sim® and MoBi® with pregnancy-related changes of relevant enzymes applied. PK were predicted in a virtual population of 1000 pregnant subjects, and prediction results were compared with in vivo PK data from the International Maternal, Pediatric, Adolescent AIDS Clinical Trials (IMPAACT) Network 2032 study. The developed PBPK model successfully captured RDV and its metabolites' plasma concentrations during pregnancy. The ratios of prediction versus observation for RDV area under the curve from time 0 to infinity (AUC0-∞ ) and maximum concentration (Cmax ) were 1.61 and 1.17, respectively. For GS-704277, the ratios of predicted versus observed were 0.94 for AUC0-∞ and 1.20 for Cmax . For GS-441524, the ratios of predicted versus observed were 1.03 for AUC0-24 , 1.05 for Cmax , and 1.07 for concentrations at 24 h. All predictions of AUC and Cmax for RDV and its metabolites were within a twofold error range, and about 60% of predictions were within a 10% error range. These findings demonstrate the feasibility of translating PBPK models to pregnant women to potentially guide trial design, clinical decision making, and drug development.
Subject(s)
COVID-19 , Pregnant Women , Adult , Adolescent , Pregnancy , Female , Child , Humans , SARS-CoV-2 , COVID-19 Drug Treatment , Models, BiologicalABSTRACT
Controlling the crystallization of perovskite in a thin film is essential in making solar cells. Processing tin-based perovskite films from solution is challenging because of the uncontrollable faster crystallization of tin than the most used lead perovskite. The best performing devices are prepared by depositing perovskite from dimethyl sulfoxide because it slows down the assembly of the tin-iodine network that forms perovskite. However, while dimethyl sulfoxide seems the best solution to control the crystallization, it oxidizes tin during processing. This work demonstrates that 4-(tert-butyl) pyridine can replace dimethyl sulfoxide to control the crystallization without oxidizing tin. We show that tin perovskite films deposited from pyridine have a 1 order of magnitude lower defect density, which promotes charge mobility and photovoltaic performance.
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Chemical risk assessment considers potentially susceptible populations including pregnant women and developing fetuses. Humans encounter thousands of chemicals in their environments, few of which have been fully characterized. Toxicokinetic (TK) information is needed to relate chemical exposure to potentially bioactive tissue concentrations. Observational data describing human gestational exposures are unavailable for most chemicals, but physiologically based TK (PBTK) models estimate such exposures. Development of chemical-specific PBTK models requires considerable time and resources. As an alternative, generic PBTK approaches describe a standardized physiology and characterize chemicals with a set of standard physical and TK descriptors - primarily plasma protein binding and hepatic clearance. Here we report and evaluate a generic PBTK model of a human mother and developing fetus. We used a published set of formulas describing the major anatomical and physiological changes that occur during pregnancy to augment the High-Throughput Toxicokinetics (httk) software package. We simulated the ratio of concentrations in maternal and fetal plasma and compared to literature in vivo measurements. We evaluated the model with literature in vivo time-course measurements of maternal plasma concentrations in pregnant and non-pregnant women. Finally, we prioritized chemicals measured in maternal serum based on predicted fetal brain concentrations. This new model can be used for TK simulations of 859 chemicals with existing human-specific in vitro TK data as well as any new chemicals for which such data become available. This gestational model may allow for in vitro to in vivo extrapolation of point of departure doses relevant to reproductive and developmental toxicity.
Subject(s)
Models, Biological , Female , Humans , Risk Assessment , ToxicokineticsABSTRACT
There is limited information about the transfer of antidepressants and antipsychotics across the human placenta. The objective of the current review was to systematically screen the scientific literature using relevant keywords to collect quantitative data on placental transfer of these drugs in humans and to give an overview of current modeling approaches used in this context. The collected data encompassed clinically measured fetal:maternal (F:M) concentration ratios (ie, the ratio between drug concentrations measured in the umbilical cord and drug concentrations measured in the mother) and transfer data obtained from ex vivo cotyledon perfusion experiments. These data were found for 18 antidepressants and some of their pharmacologically active metabolites, and for 10 antipsychotics and the metabolites thereof. Based on the collected data, similar maternal and fetal exposure could be observed for only a few compounds (eg, norfluoxetine and desvenlafaxine), whereas for most drugs (eg, paroxetine, sertraline, and quetiapine), fetal exposure appeared to be on average lower than maternal exposure. Venlafaxine appeared to be an exception in that the data indicated equivalent or higher concentrations in the umbilical cord than in the mother. Physiologically based pharmacokinetic (PBPK) models were sporadically used to investigate maternal pharmacokinetics of antidepressants or antipsychotics (eg, for sertraline, aripiprazole, and olanzapine), although without explicitly addressing fetal drug exposure. It is recommended that PBPK modeling is applied more frequently to these drugs. Although no substitute for clinical studies, these tools can help to better understand pregnancy-induced pharmacokinetic changes and ultimately contribute to a more evidence-based pharmacotherapy of depression and psychosis in pregnant subjects.