Assessment of Drug-Drug Interaction Risk Between Intravenous Fentanyl and the Glecaprevir/Pibrentasvir Combination Regimen in Hepatitis C Patients Using Physiologically Based Pharmacokinetic Modeling and Simulations.

INTRODUCTION: An unsafe injection practice is one of the major contributors to new hepatitis C virus (HCV) infections; thus, people who inject drugs are a key population to prioritize to achieve HCV elimination. The introduction of highly effective and well-tolerated pangenotypic direct-acting antivirals, including glecaprevir/pibrentasvir (GLE/PIB), has revolutionized the HCV treatment landscape. Glecaprevir is a weak cytochrome P450 3A4 (CYP3A4) inhibitor, so there is the potential for drug-drug interactions (DDIs) with some opioids metabolized by CYP3A4, such as fentanyl. This study estimated the impact of GLE/PIB on the pharmacokinetics of intravenous fentanyl by building a physiologically based pharmacokinetic (PBPK) model. METHODS: A PBPK model was developed for intravenous fentanyl by incorporating published information on fentanyl metabolism, distribution, and elimination in healthy individuals. Three clinical DDI studies were used to verify DDIs within the fentanyl PBPK model. This model was integrated with a previously developed GLE/PIB PBPK model. After model validation, DDI simulations were conducted by coadministering GLE 300 mg + PIB 120 mg with a single dose of intravenous fentanyl (0.5 µg/kg). RESULTS: The predicted maximum plasma concentration ratio between GLE/PIB + fentanyl and fentanyl alone was 1.00, and the predicted area under the curve ratio was 1.04, suggesting an increase of only 4% in fentanyl exposure. CONCLUSION: The administration of a therapeutic dose of GLE/PIB has very little effect on the pharmacokinetics of intravenous fentanyl. This negligible increase would not be expected to increase the risk of fentanyl overdose beyond the inherent risks related to the amount and purity of the fentanyl received during recreational use.

Virtual Bioequivalence Assessment of Elagolix Formulations Using Physiologically Based Pharmacokinetic Modeling.

In lieu of large bioequivalence studies and exposing healthy postmenopausal women to additional drug exposure for elagolix coadministered with hormonal add-back therapy, physiologically based pharmacokinetic (PBPK) modeling was used with in vitro dissolution data to test for virtual bioequivalence. For endometriosis, elagolix is approved at doses of 150 mg once daily and 200 mg twice daily as a tablet. As a combination therapy, two individual tablets, consisting of an elagolix tablet and an estradiol/norethindrone acetate 1/0.5 mg (E2/NETA) tablet, were utilized in Phase 3 endometriosis trials. However, the commercial combination drug products consist of a morning capsule (containing an elagolix tablet and E2/NETA tablet as a fixed-dose combination capsule, AM capsule) and an evening capsule (consisting of an elagolix tablet, PM capsule). In vitro dissolution profiles were dissimilar for the tablet and capsule formulations; thus, in vivo bioequivalence studies or a bioequivalence waiver would have been required. To simulate virtual cross-over, bioequivalence trials, in vitro dissolution data was incorporated into a previously verified PBPK model. The updated PBPK model was externally validated using relevant bioequivalence study data. Based on results of the virtual bioequivalence simulations, the commercial drug product capsules met the bioequivalence criteria of 0.80-1.25 when compared to the reference tablets. This was a novel example where PBPK modeling was utilized along with in vitro dissolution data to demonstrate virtual bioequivalence in support of a regulatory bioequivalence waiver.

Impact of Multiple Concomitant CYP3A Inhibitors on Venetoclax Pharmacokinetics: A PBPK and Population PK-Informed Analysis.

Venetoclax is an approved, orally bioavailable, B-cell lymphoma type 2 (BCL-2) inhibitor that is primarily metabolized by cytochrome P450 3A (CYP3A). Polypharmacy is common in patients undergoing treatment for hematological malignancies such as acute myeloid leukemia or chronic lymphocytic leukemia, and although venetoclax exposure has been well characterized with 1 concomitant CYP3A inhibitor, complex drug-drug interactions (DDIs) involving more than 1 inhibitor have not been systematically evaluated. Here, we aimed to describe the potential impact of multiple concomitant CYP3A inhibitors on venetoclax pharmacokinetics (PK) using physiologically based pharmacokinetic (PBPK) and population PK modeling. The modeling approaches were informed by clinical data in the presence of single or multiple CYP3A inhibitors, and the effects of 1 or more inhibitors were systematically considered within these modeling frameworks. The PBPK modeling approach was independently validated against clinical data involving more than 1 CYP3A inhibitor along with CYP3A substrates other than venetoclax. Both approaches indicated that combining a strong CYP3A inhibitor with another competitive CYP3A inhibitor does not seem to result in any additional increase in venetoclax exposure, beyond what would be expected with a strong inhibitor alone. This suggests that the current dose reductions recommended for venetoclax would be appropriate even when 2 or more CYP3A inhibitors are taken concomitantly. However, the results indicate that the involvement of time-dependent inhibition might lead to additional inhibitory effects over and above the effect of a single strong CYP3A inhibitor. Thus, the clinical management of such interactions must consider the underlying mechanism of the interactions.

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.

Physiologically based pharmacokinetic modeling and simulations to inform dissolution specifications and clinical relevance of release rates on elagolix exposure.

The aim of this analysis was to use a physiologically based pharmacokinetic (PBPK) model to predict the impact of changes in dissolution rates on elagolix exposures and define clinically relevant acceptance criteria for dissolution. Varying in vitro dissolution profiles were utilized in a PBPK model to describe the absorption profiles of elagolix formulations used in Phase 3 clinical trials and for the to be marketed commercial formulations. Single dose studies of 200 mg elagolix formulations were used for model verification under fasted conditions. Additional dissolution scenarios were evaluated to assess the impact of dissolution rates on elagolix exposures. Compared to the Phase 3 clinical trial formulation, sensitivity analysis on dissolution rates suggested that a hypothetical scenario of ∼75% slower dissolution rate would result in 14% lower predicted elagolix plasma exposures, however, the predicted exposures are still within the bioequivalence boundaries of 0.8-1.25 for both Cmax and AUC. A clinically verified PBPK model of elagolix was utilized to evaluate the impact of wider dissolution specifications on elagolix plasma exposures. The simulation results indicated that a slower in vitro dissolution profile, would not have a clinically significant impact on elagolix exposures. These model results informed the setting of wider dissolution specifications without requiring in vivo studies.

Finite-Time Heterogeneous Cyclic Pursuit With Application to Cooperative Target Interception.

This article presents a finite-time heterogeneous cyclic pursuit scheme that ensures consensus among agents modeled as integrators. It is shown that for the proposed consensus scheme, even when the gains are nonidentical, consensus results within a finite time, provided all the gains are positive or even if one gain is negative, subject to a lower bound. An algorithm is presented to compute the consensus value and consensus time for a given set of positive gains and initial states of the agents. The set of values, where consensus can occur, by varying the gains, has been derived and a second algorithm aids in determining the positive gains that enable consensus at any point in the aforementioned set, at a given finite time. As an application, the finite-time consensus in line-of-sight rates, over a cycle digraph, for a group of interceptors is shown to be effective in ensuring co-operative collision-free interception of a target, for both constant speed as well as realistic time-varying-speed models of the interceptors. Simulations the theoretical results.

Current Practices, Gap Analysis, and Proposed Workflows for PBPK Modeling of Cytochrome P450 Induction: An Industry Perspective.

The International Consortium for Innovation and Quality (IQ) Physiologically Based Pharmacokinetic (PBPK) Modeling Induction Working Group (IWG) conducted a survey across participating companies around general strategies for PBPK modeling of induction, including experience with its utility to address various questions, regulatory interactions, and regulatory acceptance. The results highlight areas where PBPK modeling is used with high confidence and identifies opportunities where confidence is lower and further evaluation is needed. To enhance the survey results, the PBPK-IWG also collected case studies and analyzed recent literature examples where PBPK models were applied to predict CYP3A induction-mediated drug-drug interactions. PBPK modeling of induction has evolved and progressed significantly, proving to have great potential to accelerate drug discovery and development. With the aim of enabling optimal use for new molecular entities that are either substrates and/or inducers of CYP3A, the PBPK-IWG proposes initial workflows for PBPK application, discusses future trends, and identifies gaps that need to be addressed.

Outcome of Sublingual Immunotherapy in Allergic Rhinitis.

Allergic rhinitis (AR) is one of the most common types of allergy worldwide. It has significant negative impact on the quality of life (QOL). One of the available causal treatments of AR is allergen specific immunotherapy which remains effective even after the end of treatment course, unlike symptomatic drugs. AR patients aged above five years, allergic to unavoidable allergen like house dust, mite etc., and refractory to maximal pharmacotherapy were included in present study. Patients allergic to avoidable allergen, taking beta-blocker medication, having other immunological disease, and who were pregnant, breast-feeding or lost to follow up, were excluded from the study. All patients included in the study underwent sublingual immunotherapy (SLIT). The impact of treatment is measured by calculating the difference between SNOT-20 score before and after treatment (which is 6 months interval). Total 30 patients were studied. Paired-t test calculated value of cumulative score and nasal symptom score are 7.853 and 6.85 respectively. Both are greater than table value of 2.46. So paired-t test shows that SLIT is very much effective in treatment of AR. The present study re-establish the fact that SLIT not only reduces AR symptoms, it also improves the QOL. It has very good patient compliance with minimal side effects.

Dose adjustment of venetoclax when co-administered with posaconazole: clinical drug-drug interaction predictions using a PBPK approach.

PURPOSE: Venetoclax, a targeted anticancer agent approved for the treatment of chronic lymphocytic leukemia and acute myeloid leukemia, is a substrate of cytochrome P450 (CYP) 3A enzyme (CYP3A4). Posaconazole, commonly used to prevent invasive fungal infections in neutropenic patients with hematological malignancies, potently inhibits CYP3A4. The purpose of this evaluation was to predict venetoclax exposures following co-administration of posaconazole at doses not previously studied clinically. METHODS: Two physiologically based pharmacokinetic (PBPK) models were developed for posaconazole based on published parameters, one for an oral suspension and another for delayed released tablets. Parameter optimization, guided by sensitivity analyses, was conducted such that the models could replicate clinical exposures of posaconazole and drug-drug interactions with sensitive CYP3A substrates including venetoclax. The clinically verified posaconazole PBPK models were then utilized to predict DDI with a previously published venetoclax PBPK model at clinically relevant dosing scenarios. RESULTS: The posaconazole PBPK models predicted posaconazole exposure and DDI related fold changes with acceptable prediction errors for both posaconazole formulations. The model predicted exposures of venetoclax, when co-administered with a 300 mg QD dose of delayed release tablets of posaconazole, were in concordance with observed data. Increasing the posaconazole dose to 500 mg QD increased venetoclax exposures by about 12% relative to 300 mg QD, which were still within the venetoclax safe exposure range. CONCLUSIONS: The posaconazole PBPK models were developed and clinically verified. Predictions using the robust PBPK model confirmed the venetoclax label recommendation of 70 mg in the presence of posaconazole at doses up to 500 mg QD.

Physiologically-Based Pharmacokinetic Models for Evaluating Membrane Transporter Mediated Drug-Drug Interactions: Current Capabilities, Case Studies, Future Opportunities, and Recommendations.

Physiologically-based pharmacokinetic (PBPK) modeling has been extensively used to quantitatively translate in vitro data and evaluate temporal effects from drug-drug interactions (DDIs), arising due to reversible enzyme and transporter inhibition, irreversible time-dependent inhibition, enzyme induction, and/or suppression. PBPK modeling has now gained reasonable acceptance with the regulatory authorities for the cytochrome-P450-mediated DDIs and is routinely used. However, the application of PBPK for transporter-mediated DDIs (tDDI) in drug development is relatively uncommon. Because the predictive performance of PBPK models for tDDI is not well established, here, we represent and discuss examples of PBPK analyses included in regulatory submission (the US Food and Drug Administration (FDA), the European Medicines Agency (EMA), and the Pharmaceuticals and Medical Devices Agency (PMDA)) across various tDDIs. The goal of this collaborative effort (involving scientists representing 17 pharmaceutical companies in the Consortium and from academia) is to reflect on the use of current databases and models to address tDDIs. This challenges the common perceptions on applications of PBPK for tDDIs and further delves into the requirements to improve such PBPK predictions. This review provides a reflection on the current trends in PBPK modeling for tDDIs and provides a framework to promote continuous use, verification, and improvement in industrialization of the transporter PBPK modeling.

In silico Tools at Early Stage of Pharmaceutical Development: Data Needs and Software Capabilities.

In early drug development, the selection of a formulation platform and decisions on formulation strategies have to be made within a short timeframe and often with minimal use of the active pharmaceutical ingredient (API). The current work evaluated the various physicochemical parameters required to improve the prediction accuracy of simulation software for immediate release tablets in early drug development. DDDPlus™ was used in simulating dissolution test profiles of immediate release tablets of ritonavir and all simulations were compared with experimental results. The minimum data requirements to make useful predictions were assessed using the ADMET predictor (part of DDDPlus) and Chemicalize (an online resource). A surfactant model was developed to estimate the solubility enhancement in media containing surfactant and the software's transfer model based on the USP two-tiered dissolution test was assessed. One measured data point was shown to be sufficient to make predictive simulations in DDDPlus. At pH 2.0, the software overestimated drug release while at pH 1.0 and 6.8, simulations were close to the measured values. A surfactant solubility model established with measured data gave good dissolution predictions. The transfer model uses a single-vessel model and was unable to predict the two in vivo environments separately. For weak bases like ritonavir, a minimum of three solubility data points is recommended for in silico predictions in buffered media. A surfactant solubility model is useful when predicting dissolution behavior in surfactant media and in silico predictions need measured solubility data to be predictive.

Guiding dose adjustment of amlodipine after co-administration with ritonavir containing regimens using a physiologically-based pharmacokinetic/pharmacodynamic model.

Amlodipine, a commonly prescribed anti-hypertensive drug, shows increased systemic exposure with cytochrome P450 (CYP) 3A inhibitors. Ritonavir (RTV) is a potent mechanism-based and reversible CYP3A inhibitor and moderate inducer that is used as a pharmacokinetic enhancer in several antiviral treatment regimens. Drug-drug interaction (DDI) between RTV and amlodipine is due to mixed inhibition and induction of CYP3A4, which is challenging to predict without a mechanistic model that accounts for the complexity of both mechanisms occurring simultaneously. A novel physiologically-based pharmacokinetic (PBPK) model was developed for amlodipine, and the model was verified using published clinical PK and DDI data. The verified amlodipine PBPK model was linked to a pharmacodynamics model that describes changes in systolic blood pressure (SBP) during and after co-administration with RTV. The magnitude and time course of RTV effects on amlodipine plasma exposures and SBP were evaluated, to provide guidance on dose adjustment of amlodipine during and after co-administration with RTV-containing regimens. Model simulations suggested that the increase in amlodipine's plasma exposure by RTV diminishes by approximately 80% within 5 days after the last dose of RTV. PBPK simulations suggested that resuming a full dose of amlodipine [5 mg once daily (QD)] immediately after RTV's last dose would decrease daily average SBP by a maximum of 3.3 mmHg, while continuing with the reduced dose (2.5 mg QD) for 5 days after the last dose of RTV would increase daily average SBP by a maximum of 5.8 mmHg. Based on these results, either approach of resuming amlodipine's full dose could be appropriate when combined with appropriate clinical monitoring.

Odontogenic Tumours of Jaw: A Prospective Study on Clinico-Pathological Profile and Their Management.

Odontogenic tumours are a group of heterogeneous diseases that range from hamartomatous or non-neoplastic tissue proliferations to benign neoplasms to malignant tumours with metastatic potential. They are rare, comprising about <2-3% of all oral and maxillofacial biopsy specimens. The aim of the present study was to determine the clinico-pathological presentation of this heterogeneous group of lesions and review of literature. The present study was conducted in the ENT department of a Government Medical College and Hospital, West Bengal, India, over the period of 5 years from January 2011 to December 2015. It included a total of 15 patients who were clinico-radiologically diagnosed as odontogenic tumours, and were given appropriate treatment. Their diagnostic and management approaches are discussed. Among 15 odontogenic tumours, 13 were benign and two were malignant. Male to female ratio was 2:3. Mandible to maxilla ratio was 1.8:1. The patients were in between 4 and 56 years of age with highest incidence in 3rd decade of life. All patients are doing well till date with a minimum follow-up of 1 year. Incisional biopsy is considered as gold standard for preoperative diagnosis but FNAC can offer clinicians a less invasive alternative. CT is the choice of investigation for study of lesion, analysis of its extension and surgical planning. The challenge to proper management lies in balancing between conservative and radical approach to reduce morbidity and recurrence both. Final diagnosis is made by post-operative histopathological examination.

Single-Stage Trans-mastoid Drainage of Otogenic Brain Abscess: A Single-Institution Experience.

Brain abscess is the ultimate otogenic complication, both in severity and difficulty of management. In developing countries with high incidence of cholesteatoma, brain abscess is not a rare complication. In India, brain abscesses constitute about 8 % of all intracranial lesions. The surgical treatment of brain abscess is very controversial. This prospective study was done in ENT department of a tertiary care hospital in Kolkata, during the period from May 2009 to April 2014. 22 such cases of otogenic brain abscess managed by single-stage trans-mastoid drainage along with meticulous mastoid clearance. On the basis of clinical, radiological and operative findings, data of all patients with otogenic brain abscess were analyzed. There was male predominance and 9 (40.91 %) of them were younger than 20 years. 15 (68.18 %) cases were of cerebellar abscess and in 7 (31.82 %) cases were of the temporal abscess. Lateral sinus thrombosis was the most common associated complication found (22.73 %) in our study. All the patients peri-operatively revealed cholesteatoma. All the patients recovered well and there was no recurrence of symptoms on a minimum 15 months follow-up. This approach suits the otologists in clearing the cause and effect of pathology, at the same sitting. This single-stage approach decreases the peri-operative morbidity and mortality of the two-stage procedure. It also decreases the hospital stay and financial burden.

Modeling In Vivo Interactions of Engineered Nanoparticles in the Pulmonary Alveolar Lining Fluid.

Increasing use of engineered nanomaterials (ENMs) in consumer products may result in widespread human inhalation exposures. Due to their high surface area per unit mass, inhaled ENMs interact with multiple components of the pulmonary system, and these interactions affect their ultimate fate in the body. Modeling of ENM transport and clearance in vivo has traditionally treated tissues as well-mixed compartments, without consideration of nanoscale interaction and transformation mechanisms. ENM agglomeration, dissolution and transport, along with adsorption of biomolecules, such as surfactant lipids and proteins, cause irreversible changes to ENM morphology and surface properties. The model presented in this article quantifies ENM transformation and transport in the alveolar air to liquid interface and estimates eventual alveolar cell dosimetry. This formulation brings together established concepts from colloidal and surface science, physics, and biochemistry to provide a stochastic framework capable of capturing essential in vivo processes in the pulmonary alveolar lining layer. The model has been implemented for in vitro solutions with parameters estimated from relevant published in vitro measurements and has been extended here to in vivo systems simulating human inhalation exposures. Applications are presented for four different ENMs, and relevant kinetic rates are estimated, demonstrating an approach for improving human in vivo pulmonary dosimetry.

Modeling in vitro cellular responses to silver nanoparticles.

Engineered nanoparticles (NPs) have been widely demonstrated to induce toxic effects to various cell types. In vitro cell exposure systems have high potential for reliable, high throughput screening of nanoparticle toxicity, allowing focusing on particular pathways while excluding unwanted effects due to other cells or tissue dosimetry. The work presented here involves a detailed biologically based computational model of cellular interactions with NPs; it utilizes measurements performed in human cell culture systems in vitro, to develop a mechanistic mathematical model that can support analysis and prediction of in vivo effects of NPs. The model considers basic cellular mechanisms including proliferation, apoptosis, and production of cytokines in response to NPs. This new model is implemented for macrophages and parameterized using in vitro measurements of changes in cellular viability and mRNA levels of cytokines: TNF, IL-1b, IL-6, IL-8, and IL-10. The model includes in vitro cellular dosimetry due to nanoparticle transport and transformation. Furthermore, the model developed here optimizes the essential cellular parameters based on in vitro measurements, and provides a "stepping stone" for the development of more advanced in vivo models that will incorporate additional cellular and NP interactions.

Physiologically-based toxicokinetic modeling of zearalenone and its metabolites: application to the Jersey girl study.

Zearalenone (ZEA), a fungal mycotoxin, and its metabolite zeranol (ZAL) are known estrogen agonists in mammals, and are found as contaminants in food. Zeranol, which is more potent than ZEA and comparable in potency to estradiol, is also added as a growth additive in beef in the US and Canada. This article presents the development and application of a Physiologically-Based Toxicokinetic (PBTK) model for ZEA and ZAL and their primary metabolites, zearalenol, zearalanone, and their conjugated glucuronides, for rats and for human subjects. The PBTK modeling study explicitly simulates critical metabolic pathways in the gastrointestinal and hepatic systems. Metabolic events such as dehydrogenation and glucuronidation of the chemicals, which have direct effects on the accumulation and elimination of the toxic compounds, have been quantified. The PBTK model considers urinary and fecal excretion and biliary recirculation and compares the predicted biomarkers of blood, urinary and fecal concentrations with published in vivo measurements in rats and human subjects. Additionally, the toxicokinetic model has been coupled with a novel probabilistic dietary exposure model and applied to the Jersey Girl Study (JGS), which involved measurement of mycoestrogens as urinary biomarkers, in a cohort of young girls in New Jersey, USA. A probabilistic exposure characterization for the study population has been conducted and the predicted urinary concentrations have been compared to measurements considering inter-individual physiological and dietary variability. The in vivo measurements from the JGS fall within the high and low predicted distributions of biomarker values corresponding to dietary exposure estimates calculated by the probabilistic modeling system. The work described here is the first of its kind to present a comprehensive framework developing estimates of potential exposures to mycotoxins and linking them with biologically relevant doses and biomarker measurements, including a systematic characterization of uncertainties in exposure and dose estimation for a vulnerable population.

Modeling Population Exposures to Silver Nanoparticles Present in Consumer Products.

Exposures of the general population to manufactured nanoparticles (MNPs) are expected to keep rising due to increasing use of MNPs in common consumer products (PEN 2014). The present study focuses on characterizing ambient and indoor population exposures to silver MNPs (nAg). For situations where detailed, case-specific exposure-related data are not available, as in the present study, a novel tiered modeling system, Prioritization/Ranking of Toxic Exposures with GIS (Geographic Information System) Extension (PRoTEGE), has been developed: it employs a product Life Cycle Analysis (LCA) approach coupled with basic human Life Stage Analysis (LSA) to characterize potential exposures to chemicals of current and emerging concern. The PRoTEGE system has been implemented for ambient and indoor environments, utilizing available MNP production, usage, and properties databases, along with laboratory measurements of potential personal exposures from consumer spray products containing nAg. Modeling of environmental and microenvironmental levels of MNPs employs Probabilistic Material Flow Analysis combined with product LCA to account for releases during manufacturing, transport, usage, disposal, etc. Human exposure and dose characterization further employs screening Microenvironmental Modeling and Intake Fraction methods combined with LSA for potentially exposed populations, to assess differences associated with gender, age, and demographics. Population distributions of intakes, estimated using the PRoTEGE framework, are consistent with published individual-based intake estimates, demonstrating that PRoTEGE is capable of capturing realistic exposure scenarios for the US population. Distributions of intakes are also used to calculate biologically-relevant population distributions of uptakes and target tissue doses through human airway dosimetry modeling that takes into account product MNP size distributions and age-relevant physiological parameters.

Modeling physicochemical interactions affecting in vitro cellular dosimetry of engineered nanomaterials: application to nanosilver.

Engineered nanomaterials (ENMs) possess unique characteristics affecting their interactions in biological media and biological tissues. Systematic investigation of the effects of particle properties on biological toxicity requires a comprehensive modeling framework which can be used to predict ENM particokinetics in a variety of media. The Agglomeration-diffusion-sedimentation-reaction model (ADSRM) described here is stochastic, using a direct simulation Monte Carlo method to study the evolution of nanoparticles in biological media, as they interact with each other and with the media over time. Nanoparticle diffusion, gravitational settling, agglomeration, and dissolution are treated in a mechanistic manner with focus on silver ENMs (AgNPs). The ADSRM model utilizes particle properties such as size, density, zeta potential, and coating material, along with medium properties like density, viscosity, ionic strength, and pH, to model evolving patterns in a population of ENMs along with their interaction with associated ions and molecules. The model predictions for agglomeration and dissolution are compared with in vitro measurements for various types of ENMs, coating materials, and incubation media, and are found to be overall consistent with measurements. The model has been implemented for an in vitro case in cell culture systems to inform in vitro dosimetry for toxicology studies, and can be directly extended to other biological systems, including in vivo tissue subsystems by suitably modifying system geometry.

Computational multiscale toxicodynamic modeling of silver and carbon nanoparticle effects on mouse lung function.

A computational, multiscale toxicodynamic model has been developed to quantify and predict pulmonary effects due to uptake of engineered nanomaterials (ENMs) in mice. The model consists of a collection of coupled toxicodynamic modules, that were independently developed and tested using information obtained from the literature. The modules were developed to describe the dynamics of tissue with explicit focus on the cells and the surfactant chemicals that regulate the process of breathing, as well as the response of the pulmonary system to xenobiotics. Alveolar type I and type II cells, and alveolar macrophages were included in the model, along with surfactant phospholipids and surfactant proteins, to account for processes occurring at multiple biological scales, coupling cellular and surfactant dynamics affected by nanoparticle exposure, and linking the effects to tissue-level lung function changes. Nanoparticle properties such as size, surface chemistry, and zeta potential were explicitly considered in modeling the interactions of these particles with biological media. The model predictions were compared with in vivo lung function response measurements in mice and analysis of mice lung lavage fluid following exposures to silver and carbon nanoparticles. The predictions were found to follow the trends of observed changes in mouse surfactant composition over 7 days post dosing, and are in good agreement with the observed changes in mouse lung function over the same period of time.