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The bioavailability of a monoclonal antibody (mAb) or another therapeutic protein after subcutaneous (SC) dosing is challenging to predict from first principles, even if the impact of injection site physiology and drug properties on mAb bioavailability is generally understood. We used a physiologically based pharmacokinetic model to predict pre-systemic clearance after SC administration mechanistically by incorporating the FcRn salvage pathway in antigen-presenting cells (APCs) in peripheral lymph nodes, draining the injection site. Clinically observed data of the removal rate of IgG from the arm as well as its plasma concentration after SC dosing were mostly predicted within the 95% confidence interval. The bioavailability of IgG was predicted to be 70%, which mechanistically relates to macropinocytosis in the draining lymph nodes and transient local dose-dependent partial saturation of the FcRn receptor in the APCs, resulting in higher catabolism and consequently less drug reaching the systemic circulation. The predicted free FcRn concentration was reduced to 40-45%, reaching the minimum 1-2 days after the SC administration of IgG, and returned to baseline after 8-12 days, depending on the site of injection. The model predicted the uptake into APCs, the binding affinity to FcRn, and the dose to be important factors impacting the bioavailability of a mAb.

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Introduction: The dose-response relationships of tacrolimus have been primarily assessed through trough concentrations during intermittent administrations. In scenarios where oral administration (PO) is unfeasible, continuous intravenous (IV) administration is advised. Under these circumstances, only steady-state (Css) plasma or blood concentrations are measured, with the absence of distinct trough levels (Cmin). Consequently, the measured concentrations are frequently misinterpreted as trough concentrations, potentially resulting in sub-therapeutic true tacrolimus blood levels. This study employs physiologically based pharmacokinetic modeling (PBPK) to establish the Css/Cmin ratio for tacrolimus across various clinical scenarios. Method: Using a validated PBPK model, the tacrolimus dose (both PO and IV) and the Css/Cmin ratios corresponding to matching area under the blood concentration-time curve during a dosage interval (AUCτ) values were estimated under different conditions, including healthy subjects and individuals exhibiting cytochrome P450 3A (CYP3A) interactions or CYP3A5 polymorphisms, along with a demonstration of a real-life clinical application. Result: In healthy volunteers, the oral/intravenous (PO/IV) dose ratio was found to be 4.25, and the Css/Cmin ratio was 1.40. A specific clinical case substantiated the practical applicability of the Css/Cmin ratio as simulated by PBPK, demonstrating no immediate clinical complications related to the transplant. When considering liver donors versus recipients expressing CYP3A5, the tacrolimus AUCτ was notably affected, yielding a PO/IV dose ratio of 4.00 and a Css/Cmin ratio of 1.75. Furthermore, the concomitant administration of the CYP3A inhibitor itraconazole given PO resulted in a PO/IV ratio of 1.75 with and a Css/Cmin ratio of 1.28. Notably, the inhibitory effect of itraconazole was diminished when administered IV. Conclusions: Through the application of PBPK methodologies, this study estimates the PO/IV dose ratios and Css/Cmin ratios that can enhance dose adjustment and therapeutic drug monitoring during the switch between IV and PO administration of tacrolimus in transplant patients, ultimately guiding clinicians in real-time decision-making. Further validation with in vivo data is recommended to support these findings.

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Enzyme-mediated pharmacokinetic drug-drug interactions can be caused by altered activity of drug metabolizing enzymes in the presence of a perpetrator drug, mostly via inhibition or induction. We identified a gap in the literature for a state-of-the art detailed overview assessing this type of DDI risk in the context of drug development. This manuscript discusses in vitro and in vivo methodologies employed during the drug discovery and development process to predict clinical enzyme-mediated DDIs, including the determination of clearance pathways, metabolic enzyme contribution, and the mechanisms and kinetics of enzyme inhibition and induction. We discuss regulatory guidance and highlight the utility of in silico physiologically-based pharmacokinetic modeling, an approach that continues to gain application and traction in support of regulatory filings. Looking to the future, we consider DDI risk assessment for targeted protein degraders, an emerging small molecule modality, which does not have recommended guidelines for DDI evaluation. Our goal in writing this report was to provide early-career researchers with a comprehensive view of the enzyme-mediated pharmacokinetic DDI landscape to aid their drug development efforts.

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Currently, Biopharmaceutics Classification System (BCS) classes I and III are the only biological exemptions of immediate-release solid oral dosage forms eligible for regulatory approval. However, through virtual bioequivalence (VBE) studies, BCS class II drugs may qualify for biological exemptions if reliable and validated modeling is used. Here, we sought to establish physiologically based pharmacokinetic (PBPK) models, in vitro-in vivo relationship (IVIVR), and VBE models for enteric-coated omeprazole capsules, to establish a clinically-relevant dissolution specification (CRDS) for screening BE and non-BE batches, and to ultimately develop evaluation criteria for generic omeprazole enteric-coated capsules. To establish omeprazole's IVIVR based on the PBPK model, we explored its in vitro dissolution conditions and then combined in vitro dissolution profile studies with in vivo clinical trials. The predicted omeprazole pharmacokinetics (PK) profiles and parameters closely matched the observed PK data. Based on the VBE results, the bioequivalence study of omeprazole enteric-coated capsules required at least 48 healthy Chinese subjects. Based on the CRDS, the capsules' in vitro dissolution should not be < 28%-54%, < 52%, or < 80% after two, three, and six hours, respectively. Failure to meet these dissolution criteria may result in non-bioequivalence. Here, PBPK modeling and IVIVR methods were used to bridge the in vitro dissolution of the drug with in vivo PK to establish the BE safety space of omeprazole enteric-coated capsules. The strategy used in this study can be applied in BE studies of other BCS II generics to obtain biological exemptions and accelerate drug development.

Asunto(s)

Cápsulas , Liberación de Fármacos , Modelos Biológicos , Omeprazol , Equivalencia Terapéutica , Omeprazol/farmacocinética , Omeprazol/administración & dosificación , Omeprazol/química , Humanos , Masculino , Adulto , Solubilidad , Adulto Joven , Administración Oral , Inhibidores de la Bomba de Protones/farmacocinética , Inhibidores de la Bomba de Protones/administración & dosificación , Inhibidores de la Bomba de Protones/química , Femenino , Medicamentos Genéricos/farmacocinética , Medicamentos Genéricos/administración & dosificación , Medicamentos Genéricos/normas , Medicamentos Genéricos/química , Estudios Cruzados

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Introduction: Critically ill patients show large variability in drug disposition due to e.g., age, size, disease and treatment modalities. Physiologically-based pharmacokinetic (PBPK) models can be used to design individualized dosing regimens taking this into account. Dexamethasone, prescribed for the prevention post-extubation stridor (PES), is metabolized by the drug metabolizing enzyme CYP3A. As CYP3A4 undergoes major changes during childhood, we aimed to develop age-appropriate dosing recommendations for children of dexamethasone for PES, as proof of concept for PBPK modeling to individualize dosing for critically ill patients. Methods: All simulations were conducted in Simcyp™ v21 (a population-based PBPK modeling platform), using an available dexamethasone compound model and pediatric population model in which CYP3A4 ontogeny is incorporated. Published pharmacokinetic (PK) data was used for model verification. Evidence for the dose to prevent post-extubation stridor was strongest for 2-6 year old children, hence simulated drug concentrations resulting from this dose from this age group were targeted when simulating age-appropriate doses for the whole pediatric age range. Results: Dexamethasone plasma concentrations upon single and multiple intravenous administration were predicted adequately across the pediatric age range. Exposure-matched predictions of dexamethasone PK indicated that doses (in mg/kg) for the 2-6 years olds can be applied in 3 month-2 year old children, whereas lower doses are needed in children of other age groups (60% lower for 0-2 weeks, 40% lower for 2-4 weeks, 20% lower for 1-3 months, 20% lower for 6-12 year olds, 40% lower for 12-18 years olds). Discussion: We show that PBPK modeling is a valuable tool that can be used to develop model-informed recommendations using dexamethasone to prevent PES in children. Based on exposure matching, the dose of dexamethasone should be reduced compared to commonly used doses, in infants <3 months and children ≥6 years, reflecting age-related variation in drug disposition. PBPK modeling is an promising tool to optimize dosing of critically ill patients.

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The interest in the development and therapeutic application of long-acting injectable products for chronic or long-term treatments has experienced exponential growth in recent decades. TV-46000 (Uzedy, Teva) is a long-acting subcutaneous (sc) injectable formulation of risperidone, approved for the treatment of schizophrenia in adults. Following sc injection, the copolymers together with risperidone precipitate to form a sc depot under the skin to deliver therapeutic levels of risperidone over a prolonged period of either 1 month or 2 months, depending upon the dose. This work presents the strategy and the results of the physiologically-based pharmacokinetic (PBPK) modeling and establishing of in vitro-in vivo correlation (IVIVC) for the prediction of TV-46000 pharmacokinetic profile in humans, using in vitro release, intravenous (iv), and sc single-dose pharmacokinetic data in beagle dogs. The resulting simulated TV-46000 PK profile in humans showed that the shape of the predicted risperidone and its active metabolite 9-OH-risperidone PK profiles was different from the observed one, thus suggesting that the TV-46000 release profile was species-dependent and cannot be directly extrapolated from dog to human. In conclusion, while level A IVIVC cannot be claimed, this work combining PBPK and IVIVC modeling represents an interesting alternative approach for complex injectable formulations where classical methods are not applicable.

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Utilization of in vitro (cellular) techniques, like Cell Painting and transcriptomics, could provide powerful tools for agrochemical candidate sorting and selection in the discovery process. However, using these models generates challenges translating in vitro concentrations to the corresponding in vivo exposures. Physiologically based pharmacokinetic (PBPK) modeling provides a framework for quantitative in vitro to in vivo extrapolation (IVIVE). We tested whether in vivo (rat liver) transcriptomic and apical points of departure (PODs) could be accurately predicted from in vitro (rat hepatocyte or human HepaRG) transcriptomic PODs or HepaRG Cell Painting PODs using PBPK modeling. We compared two PBPK models, the ADMET predictor and the httk R package, and found httk to predict the in vivo PODs more accurately. Our findings suggest that a rat liver apical and transcriptomic POD can be estimated utilizing a combination of in vitro transcriptome-based PODs coupled with PBPK modeling for IVIVE. Thus, high content in vitro data can be translated with modest accuracy to in vivo models of ultimate regulatory importance to help select agrochemical analogs in early stage discovery program.

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Agroquímicos , Animales , Ratas , Humanos , Agroquímicos/farmacocinética , Agroquímicos/toxicidad , Hepatocitos/metabolismo , Hígado/metabolismo , Modelos Biológicos , Masculino , Transcriptoma , Línea Celular , Medición de Riesgo

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Ischemia-reperfusion injury (IRI) is an intrinsic risk associated with liver transplantation. Ex vivo hepatic machine perfusion (MP) is an emerging organ preservation technique that can mitigate IRI, especially in livers subjected to prolonged warm ischemia time (WIT). However, a method to quantify the biological response to WIT during MP has not been established. Previous studies used physiologically based pharmacokinetic (PBPK) modeling to demonstrate that a decrease in hepatic transport and biliary excretion of the tracer molecule sodium fluorescein (SF) could correlate with increasing WIT in situ. Furthermore, these studies proposed intracellular sequestration of the hepatocyte canalicular membrane transporter multidrug resistance-associated protein 2 (MRP2) leading to decreased MRP2 activity (maximal transport velocity; Vmax) as the potential mechanism for decreased biliary SF excretion. We adapted an extant PBPK model to account for ex vivo hepatic MP and fit a six-parameter version of this model to control time-course measurements of SF in MP perfusate and bile. We then identified parameters whose values were likely insensitive to changes in WIT and fixed them to generate a reduced model with only three unknown parameters. Finally, we fit the reduced model to each individual biological replicate SF time course with differing WIT, found the mean estimated value for each parameter, and compared them using a one-way ANOVA. We demonstrated that there was a significant decrease in the estimated value of Vmax for MRP2 at the 30-min WIT. These studies provide the foundation for future studies investigating real-time assessment of liver viability during ex vivo MP.NEW & NOTEWORTHY We developed a computational model of sodium fluorescein (SF) biliary excretion in ex vivo machine perfusion and used this model to assess changes in model parameters associated with the activity of MRP2, a hepatocyte membrane transporter, in response to increasing warm ischemia time. We found a significant decrease in the parameter value describing MRP2 activity, consistent with a role of decreased MRP2 function in ischemia-reperfusion injury leading to decreased secretion of SF into bile.

Asunto(s)

Fluoresceína , Hígado , Modelos Biológicos , Daño por Reperfusión , Daño por Reperfusión/metabolismo , Hígado/metabolismo , Animales , Fluoresceína/farmacocinética , Fluoresceína/metabolismo , Perfusión , Isquemia Tibia , Bilis/metabolismo , Trasplante de Hígado , Proteína 2 Asociada a Resistencia a Múltiples Medicamentos , Preservación de Órganos/métodos , Eliminación Hepatobiliar , Transportadoras de Casetes de Unión a ATP

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Miltefosine (MTS) is the only approved oral drug for treating leishmaniasis caused by intracellular Leishmania parasites that localize in macrophages of the liver, spleen, skin, bone marrow, and lymph nodes. MTS is extensively distributed in tissues and has prolonged elimination half-lives due to its high plasma protein binding, slow metabolic clearance, and minimal urinary excretion. Thus, understanding and predicting the tissue distribution of MTS help assess therapeutic and toxicologic outcomes of MTS, especially in special populations, e.g., pediatrics. In this study, a whole-body physiologically-based pharmacokinetic (PBPK) model of MTS was built on mice and extrapolated to rats and humans. MTS plasma and tissue concentration data obtained by intravenous and oral administration to mice were fitted simultaneously to estimate model parameters. The resulting high tissue-to-plasma partition coefficient values corroborate extensive distribution in all major organs except the bone marrow. Sensitivity analysis suggests that plasma exposure is most susceptible to changes in fraction unbound in plasma. The murine oral-PBPK model was further validated by assessing overlay of simulations with plasma and tissue profiles obtained from an independent study. Subsequently, the murine PBPK model was extrapolated to rats and humans based on species-specific physiological and drug-related parameters, as well as allometrically scaled parameters. Fold errors for pharmacokinetic parameters were within acceptable range in both extrapolated models, except for a slight underprediction in the human plasma exposure. These animal and human PBPK models are expected to provide reliable estimates of MTS tissue distribution and assist dose regimen optimization in special populations.

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Antiprotozoarios , Fosforilcolina , Fosforilcolina/análogos & derivados , Fosforilcolina/farmacocinética , Animales , Antiprotozoarios/farmacocinética , Ratones , Humanos , Ratas , Distribución Tisular , Administración Oral , Masculino , Femenino

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The blood-brain-barrier (BBB) is made up of blood vessels whose permeability enables the passage of some compounds. A predictive model of BBB permeability is important in the early stages of drug development. The predicted BBB permeabilities of drugs have been confirmed using a variety of in vitro methods to reduce the quantities of drug candidates needed in preclinical and clinical trials. Most prior studies have relied on animal or cell-culture models, which do not fully recapitulate the human BBB. The development of microfluidic models of human-derived BBB cells could address this issue. We analyzed a model for predicting BBB permeability using the Emulate BBB-on-a-chip machine. Ten compounds were evaluated, and their permeabilities were estimated. Our study demonstrated that the permeability trends of ten compounds in our microfluidic-based system resembled those observed in previous animal and cell-based experiments. Furthermore, we established a general correlation between the partition coefficient (Kp) and the apparent permeability (Papp). In conclusion, we introduced a new paradigm for predicting BBB permeability using microfluidic-based systems.

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Small interfering RNA (siRNA) therapeutics represent an emerging class of pharmacotherapy with the potential to address previously hard-to-treat diseases. Currently approved siRNA therapeutics include LNP-encapsulated siRNA and triGalNAc-conjugated siRNA. These siRNA therapeutics exhibit distinct pharmacokinetic characteristics and unique absorption, distribution, metabolism, and elimination (ADME) properties. As a new drug modality, limited clinical data are available for siRNA therapeutics in specific populations, including pediatrics, geriatrics, individuals with renal or hepatic impairment, and pregnant women, making dosing challenging. In this review, a mechanistic overview of the ADME properties of the five currently approved siRNA therapeutics is presented. A concise overview of the clinical data available for therapeutic siRNAs in special populations, focusing on the potential impact of physiological changes during pregnancy on siRNA disposition is provided. The utility of physiologically based pharmacokinetic (PBPK) modeling as a tool to elucidate the characteristics and disposition of siRNA therapeutics in pregnant women is explored. Additionally, opportunities to integrate known physiological alterations induced by pregnancy into PBPK models that incorporate siRNA ADME mechanisms to predict the effects of pregnancy on siRNA disposition are discussed. Clinical data regarding the use of therapeutic siRNA in special populations remains limited. Data for precise parameterization of maternal-fetal siRNA PBPK models is lacking presently and underscores the need for further research in this area. Addressing this gap in knowledge will not only enhance our understanding of siRNA pharmacokinetics during pregnancy but also advance possible development of siRNA therapeutics to treat pregnancy related conditions. Significance Statement This review proposes a framework on how siRNA disposition can be predicted in pregnancy based on mechanistic ADME information using physiologically based pharmacokinetic (PBPK) modeling. The mechanistic ADME information and available clinical data in special populations of currently FDA approved siRNA therapeutics are summarized. A detailed discussion on how physiological changes during pregnancy may affect siRNA disposition in pregnant women and on the opportunities to project siRNA disposition in pregnant women using PBPK modeling is provided.

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Over the past 20 years, quantitative proteomics has contributed a wealth of protein expression data, which are currently used for a variety of systems pharmacology applications, as a complement or a surrogate for activity of the corresponding proteins. A symposium at the 25th North American ISSX meeting, in Boston, in September 2023, was held to explore current and emerging applications of quantitative proteomics in translational pharmacology and strategies for improved integration into model-informed drug development based on practical experience of each of the presenters. A summary of the talks and discussions is presented in this perspective alongside future outlooks that were outlined for future meetings. Significance Statement This perspective explores current and emerging applications of quantitative proteomics in translational pharmacology and precision medicine, and outlines outlooks for improved integration into model-informed drug development.

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Omeprazole, a gastric acid pump inhibitor, is repeatedly administered and is oxidatively metabolized mainly by polymorphic cytochrome P450 2C19. The prescribed dosage of omeprazole was discontinued or reduced in 47 of the 135 patients who received omeprazole alone in this survey, as recorded in the Japanese Adverse Drug Event Report database. The days to onset of omeprazole-related disorders were 3-4 d (median) and 16 d for intravenous 20-40 mg and oral 20 mg daily doses, respectively, in 34 patients for whom relevant data were available. The maximum plasma concentration of omeprazole was pharmacokinetically modeled after a single oral 40-mg dose in P450 2C19-defective poor metabolizers and was 2.4-fold higher than that in extensive metabolizers. The modeled area under the hepatic concentration curves of omeprazole in P450 2C19 poor metabolizers after virtual daily 40-mg doses for 7 d was 5.2-fold higher than that in the extensive metabolizers. Omeprazole-induced P450 2C19 (approx. 2-fold), resulting in increased hepatic intrinsic clearance in repeated doses, was considered after the second day. Virtual plasma/hepatic exposure estimated using pharmacokinetic modeling in subjects with P450 2C19 poor metabolizers indicated that these exposure levels virtually estimated could be one of causal factors for unexpected hepatic disorders induced by prescribed omeprazole, such as those resulting from drug interactions with repeatedly co-administered medicines.

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Citocromo P-450 CYP2C19 , Hígado , Omeprazol , Inhibidores de la Bomba de Protones , Humanos , Sistemas de Registro de Reacción Adversa a Medicamentos , Enfermedad Hepática Inducida por Sustancias y Drogas/etiología , Enfermedad Hepática Inducida por Sustancias y Drogas/sangre , Citocromo P-450 CYP2C19/genética , Citocromo P-450 CYP2C19/metabolismo , Bases de Datos Factuales , Pueblos del Este de Asia , Japón , Hígado/metabolismo , Hígado/efectos de los fármacos , Modelos Biológicos , Omeprazol/farmacocinética , Omeprazol/efectos adversos , Omeprazol/sangre , Omeprazol/administración & dosificación , Inhibidores de la Bomba de Protones/efectos adversos , Inhibidores de la Bomba de Protones/administración & dosificación , Inhibidores de la Bomba de Protones/farmacocinética , Inhibidores de la Bomba de Protones/sangre

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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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Bibliometría , Modelos Biológicos , Análisis de Redes Sociales , Humanos , Programas Informáticos , Farmacocinética , Descubrimiento de Drogas/métodos

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PURPOSE: Model-based methods can predict pediatric exposure and support initial dose selection. The aim of this study was to evaluate the performance of allometric scaling of population pharmacokinetic (popPK) versus physiologically based pharmacokinetic (PBPK) models in predicting the exposure of tyrosine kinase inhibitors (TKIs) for pediatric patients (≥ 2 years), based on adult data. The drugs imatinib, sunitinib and pazopanib were selected as case studies due to their complex PK profiles including high inter-patient variability, active metabolites, time-varying clearances and non-linear absorption. METHODS: Pediatric concentration measurements and adult popPK models were derived from the literature. Adult PBPK models were generated in PK-Sim® using available physicochemical properties, calibrated to adult data when needed. PBPK and popPK models for the pediatric populations were translated from the models for adults and were used to simulate concentration-time profiles that were compared to the observed values. RESULTS: Ten pediatric datasets were collected from the literature. While both types of models captured the concentration-time profiles of imatinib, its active metabolite, sunitinib and pazopanib, the PBPK models underestimated sunitinib metabolite concentrations. In contrast, allometrically scaled popPK simulations accurately predicted all concentration-time profiles. Trough concentration (Ctrough) predictions from the popPK model fell within a 2-fold range for all compounds, while 3 out of 5 PBPK predictions exceeded this range for the imatinib and sunitinib metabolite concentrations. CONCLUSION: Based on the identified case studies it appears that allometric scaling of popPK models is better suited to predict exposure of TKIs in pediatric patients ≥ 2 years. This advantage may be attributed to the stable enzyme expression patterns from 2 years old onwards, which can be easily related to adult levels through allometric scaling. In some instances, both methods performed comparably. Understanding where discrepancies between the model methods arise, can further inform model development and ultimately support pediatric dose selection.

Asunto(s)

Mesilato de Imatinib , Indazoles , Modelos Biológicos , Inhibidores de Proteínas Quinasas , Pirimidinas , Sulfonamidas , Sunitinib , Humanos , Niño , Inhibidores de Proteínas Quinasas/farmacocinética , Inhibidores de Proteínas Quinasas/administración & dosificación , Pirimidinas/farmacocinética , Sunitinib/farmacocinética , Sunitinib/administración & dosificación , Indazoles/farmacocinética , Indazoles/administración & dosificación , Adulto , Sulfonamidas/farmacocinética , Sulfonamidas/administración & dosificación , Mesilato de Imatinib/farmacocinética , Mesilato de Imatinib/administración & dosificación , Preescolar , Adolescente , Simulación por Computador , Masculino , Femenino , Antineoplásicos/farmacocinética , Antineoplásicos/administración & dosificación , Factores de Edad

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Electric arc furnace (EAF) slag is a coproduct of steel production used primarily for construction purposes. Some applications of EAF slag result in residential exposures by incidental ingestion and inhalation of airborne dust. To evaluate potential health risks, an EAF slag characterization program was conducted to measure concentrations of metals and leaching potential (including oral bioaccessibility) in 38 EAF slag samples. Arsenic, hexavalent chromium, iron, vanadium, and manganese (Mn) were identified as constituents of interest (COIs). Using a probabilistic risk assessment (PRA) approach, estimated distributions of dose for COIs were assessed, and increased cancer risks and noncancer hazard quotients (HQs) at the 50th and 95th percentiles were calculated. For the residents near slag-covered roads, cancer risk and noncancer HQs were <1E - 6 and 1, respectively. For residential driveway or landscape exposure, at the 95th percentile, cancer risks were 1E - 6 and 7E - 07 based on oral exposure to arsenic and hexavalent chromium, respectively. HQs ranged from 0.07 to 2 with the upper bound due to ingestion of Mn among children. To expand the analysis, a previously published physiologically based pharmacokinetic (PBPK) model was used to estimate Mn levels in the globus pallidus for both exposure scenarios and further evaluate the potential for Mn neurotoxicity. The PBPK model estimated slightly increased Mn in the globus pallidus at the 95th percentile of exposure, but concentrations did not exceed no-observed-adverse-effect levels for neurological effects. Overall, the assessment found that the application of EAF slag in residential areas is unlikely to pose a health hazard or increased cancer risk.

Asunto(s)

Teorema de Bayes , Manganeso , Acero , Medición de Riesgo/métodos , Humanos , Manganeso/farmacocinética , Exposición a Riesgos Ambientales , Disponibilidad Biológica , Adulto

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Buprenorphine readily crosses the placenta, and with greater prenatal exposure, neonatal opioid withdrawal syndrome (NOWS) likely grows more severe. Current dosing strategies can be further improved by tailoring doses to expected NOWS severity. To allow the conceptualization of fetal buprenorphine exposure, a maternal-fetal physiologically based pharmacokinetic (PBPK) model for sublingual buprenorphine was developed using Simcyp (v21.0). Buprenorphine transplacental passage was predicted from its physicochemical properties. The maternal-fetal PBPK model integrated reduced transmucosal absorption driven by lower salivary pH and induced metabolism observed during pregnancy. Maternal pharmacokinetics was adequately predicted in the second trimester, third trimester, and postpartum period, with the simulated area under the curve from 0 to 12 h, apparent clearance, and peak concentration falling within the 1.25-fold prediction error range. Following post hoc adjustment of the likely degree of individual maternal sublingual absorption, umbilical cord blood concentrations at delivery (n = 21) were adequately predicted, with a geometric mean ratio between predicted and observed fetal concentrations of 1.15 and with 95.2% falling within the 2-fold prediction error range. The maternal-fetal PBPK model developed in this study can be used to forecast fetal buprenorphine exposure and would be valuable to investigate its correlation to NOWS severity.

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We performed an ab initio next-generation risk assessment (NGRA) for a fragrance ingredient, benzyl salicylate (BSal), to demonstrate how cosmetic ingredients can be evaluated for systemic toxicity endpoints based on non-animal approaches. New approach methodologies (NAMs) used to predict the internal exposure included skin absorption assays, hepatocyte metabolism, and physiologically based pharmacokinetic (PBPK) modeling, and potential toxicodynamic effects were assessed using pharmacology profiling, ToxProfiler cell stress assay, transcriptomics in HepG2 and MCF-7 cells, ReproTracker developmental and reproductive toxicology (DART) assays, and cytotoxicity assays in human kidney cells. The outcome of the NGRA was compared to that of the traditional risk assessment approach based on animal data. The identification of the toxicologically critical entity was a critical step that directed the workflow and the selection of chemicals for PBPK modeling and testing in bioassays. The traditional risk assessment and NGRA identified salicylic acid (SA) as the "toxdriver." A deterministic PBPK model for a single-day application of 1.54 g face cream containing 0.5% BSal estimated the Cmax for BSal (1 nM) to be much lower than that of its major in vitro metabolite, SA (93.2 nM). Therefore, SA was tested using toxicodynamics bioassays. The lowest points of departure (PoDs) were obtained from the toxicogenomics assays. The interpretation of these results by two companies and methods were similar (SA only results in significant gene deregulation in HepG2 cells), but PoD differed (213 µM and 10.6 µM). A probabilistic PBPK model for repeated applications of the face cream estimated the highest Cmax of SA to be 630 nM. The resulting margins of internal exposure (MoIE) using the PoDs were 338 and 16, which were more conservative than those derived from external exposure and in vivo PoDs (margin of safety values were 9,705). In conclusion, both traditional and ab initio NGRA approaches concluded that the daily application of BSal in a cosmetic leave-on face cream at 0.5% is safe for humans. The processing and interpretation of toxicogenomics data can lead to different PoDs, which can subsequently affect the calculation of the MoIE. This case study supports the use of NAMs in a tiered NGRA ab initio approach.

RESUMEN

In this study, a physiologically based pharmacokinetic (PBPK) model of the cytochrome P450 3A (CYP3A) substrate azelnidipine was developed using in vitro and clinical data to predict the effects of azole antifungals on azelnidipine pharmacokinetics. Modeling and simulations were conducted using the Simcyp™ PBPK simulator. The azelnidipine model consisted of a full PBPK model and a first-order absorption model. CYP3A was assumed as the only azelnidipine elimination route, and CYP3A clearance was optimized using the pharmacokinetic profile of single-dose 5-mg azelnidipine in healthy participants. The model reproduced the results of a clinical drug-drug interaction study and met validation criteria. PBPK model simulations using azole antifungals (itraconazole, voriconazole, posaconazole, fluconazole, fosfluconazole) and azelnidipine or midazolam (CYP3A index substrate) were performed. Increases in the simulated area under the plasma concentration-time curve from time zero extrapolated to infinity with inhibitors were comparable between azelnidipine (range, 2.11-6.47) and midazolam (range, 2.26-9.22), demonstrating that azelnidipine is a sensitive CYP3A substrate. Increased azelnidipine plasma concentrations are expected when co-administered with azole antifungals, potentially affecting azelnidipine safety. These findings support the avoidance of azole antifungals in patients taking azelnidipine and demonstrate the utility of PBPK modeling to inform appropriate drug use.

Asunto(s)

Antifúngicos , Ácido Azetidinocarboxílico/análogos & derivados , Dihidropiridinas , Midazolam , Humanos , Midazolam/farmacocinética , Inhibidores del Citocromo P-450 CYP3A/farmacología , Citocromo P-450 CYP3A , Interacciones Farmacológicas , Itraconazol , Modelos Biológicos

RESUMEN

Physiologically based pharmacokinetic (PBPK) models of small molecules have become mainstream in drug development and academic research. The use of PBPK models is continuously expanding with the majority of work now focusing on predictions of drug-drug interactions, drug-disease interactions, and changes in drug disposition across lifespan. Recently, publications that use PBPK modeling to predict drug disposition during pregnancy and in organ impairment have increased reflecting the advances in incorporating diverse physiological changes into the models. Due to the expanding computational power and diversity of modeling platforms available, the complexity of PBPK models has also increased. Academic efforts have provided clear advances in better capturing human physiology in PBPK models and incorporating more complex mathematical concepts into PBPK models. Examples of such advances include the segregated gut model with a series gut compartments allowing modeling of physiological blood flow distribution within an organ and zonation of metabolic enzymes, and series compartment liver models allowing simulations of hepatic clearance for high extraction drugs. Despite these advances in academic research, the progress in assessing model quality and defining model acceptance criteria based on the intended use of the models has not kept pace. This review suggests that awareness of the need for predefined criteria for model acceptance has increased but many manuscripts still lack description of scientific justification and/or rationale for chosen acceptance criteria. As artificial intelligence and machine learning approaches become more broadly accepted, these tools offer promise for development of comprehensive assessment for existing observed data and analysis of model performance. Significance Statement PBPK modeling has become a mainstream application in academic literature and is broadly used for predictions, analysis and evaluation of pharmacokinetic data. Many significant advances have been made in developing advanced PBPK models that better capture human physiology but oftentimes sufficient justification for the chosen model acceptance criterion and model structure is still missing. This review provides a summary of the current landscape of PBPK applications used and highlights the needs for advancing PBPK modeling science and training in academia.