Determining tissue distribution of the oral antileishmanial agent miltefosine: a physiologically-based pharmacokinetic modeling approach.

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.

Assessing the degree of hepatic ischemia-reperfusion injury using physiologically based pharmacokinetic modeling of sodium fluorescein disposition in ex vivo machine-perfused livers.

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.

Enzyme-mediated drug-drug interactions: a review of in vivo and in vitro methodologies, regulatory guidance, and translation to the clinic.

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.

Absolute Membrane Protein Abundance of P-gp, BCRP and MRPs in Term Human Placenta Tissue and Commonly Used Cell Systems: Application in PBPK Modeling of Placental Drug Disposition.

The placenta acts as a barrier, excluding noxious substances whilst actively transferring nutrients to the fetus, mediated by various transporters. This study quantified the expression of key placental transporters in term human placenta (n=5) and BeWo, BeWo b30, and JEG-3 placenta cell lines. Combining these results with pregnancy physiologically-based pharmacokinetic (PBPK) modeling, we demonstrate the utility of proteomic analysis for predicting placental drug disposition and fetal exposure. Using targeted proteomics with QconCAT standards, we found significant expression of P-gp, BCRP, MRP2, MRP4, and MRP6 in the human placenta (0.05 - 0.25 pmol/mg membrane protein) with only regional differences observed for P-gp. Unexpectedly, both P-gp and BCRP were below the limit of quantification in the regularly used BeWo cells, indicating that this cell line may not be suitable for the study of placental P-gp and BCRP-mediated transport. In cellular and vesicular overexpression systems, P-gp and BCRP were detectable as expected. Vesicle batches showed consistent P-gp expression correlating with functional activity (N-methyl-quinidine (NMQ) transport). However, BCRP activity (Estrone 3-sulfate (E1S) transport) did not consistently align with expression levels. Incorporating in vitro transporter kinetic data, along with placental transporter abundance, into a PBPK model enabled the evaluation of fetal exposure. Simulation with a hypothetical drug indicated that estimating fetal exposure relies on the intrinsic clearances of relevant transporters. To minimize interlaboratory discrepancies, expression data was generated using consistent proteomic methodologies in the same lab. Integration of this data in pregnancy-PBPK modeling offers a promising tool to investigate maternal, placental and fetal drug exposure. Significance Statement This study quantified the expression of key transporters in human placenta and various placental cell lines, revealing significant expression variations. By integrating these data with PBPK modeling, the study highlights the importance of transporter abundance data in understanding and predicting placental drug disposition.

The ADME characteristics of siRNA therapeutics and the opportunity to predict disposition in pregnant women.

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.

Utility of PBPK Modeling in Predicting and Characterizing Clinical Drug Interactions.

Physiologically-based pharmacokinetic (PBPK) modeling is a mechanistic dynamic modeling approach that can be used to predict or retrospectively describe changes in drug exposure due to drug-drug interactions. With advancements in commercially available PBPK software, PBPK DDI modeling has become a mainstream approach from early drug discovery through to late stage drug development and is often utilized to support regulatory packages for new drug applications. This minireview will briefly describe the approaches to predicting DDI utilizing PBPK and static modeling approaches, the basic model structures and features inherent to PBPK DDI models and key examples where PBPK DDI models have been used to describe complex DDI mechanisms. Future directions aimed at using PBPK models to characterize transporter-mediated DDI, predict DDI in special populations and assess the DDI potential of protein therapeutics will be discussed. A summary of the 209 PBPK DDI examples published to date in 2023 will be provided. Overall, current data and trends suggest a continued role for PBPK models in the characterization and prediction of DDI for therapeutic molecules. Significance Statement PBPK models have been a key tool in the characterization of various pharmacokinetic phenomenon, including drug-drug interactions. This minireview will highlight recent advancements and publications around PBPK DDI modeling, an important area of drug discovery and development research in light of the increasing prevalence of polypharmacology in clinical settings.

Physiologically Based Pharmacokinetic (PBPK) Modeling of small molecules: How Much Progress Have We Made?

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.

Uncovering the Impact of COVID-19 Mediated Bidirectional Dysregulation of CYP3A4 on Systemic and Pulmonary Drug Concentrations Using Physiologically Based Pharmacokinetic Modeling.

Several clinical studies have shown that COVID-19 increases the systemic concentration of drugs in hospitalized COVID-19 patients. However, it is unclear how COVID-19-mediated bidirectional dysregulation of hepatic and pulmonary CYP3A4 impacts drug concentrations, especially in the lung tissue which is most affected by the disease. Herein, PBPK modeling was used to demonstrate the differences in systemic and pulmonary concentrations of four respiratory infectious disease drugs when CYP3A4 is concurrently downregulated in the liver and upregulated in the lung based on existing clinical data on COVID-19 - CYP3A4 interactions at varying severity levels including outpatients, non-ICU, and ICU patients. The study showed that hepatic metabolism is the primary determinant of both systemic and pulmonary drug concentrations despite the concurrent bidirectional dysregulation of liver and lung CYP3A4. ICU patients had the most systemic and pulmonary drug exposure with a percentage increase in AUCplasma of approximately 44%, 56%, 114%, and 196% for clarithromycin, nirmatrelvir, dexamethasone, and itraconazole, respectively, relative to the healthy group. Within the ICU cohort, clarithromycin exhibited its highest exposure in lung tissue mass with a fold change of 1189, while nirmatrelvir and dexamethasone showed their highest exposure in the plasma compartment, with fold changes of about 126 and 5, respectively, compared to the maximum therapeutic concentrations for their target pathogens. Itraconazole was significantly under-exposed in the lung fluid compartment potentially explaining its limited efficacy for the treatment of COVID-19. These findings underscore the importance of optimizing dosing regimens in at risk ICU patients to enhance both efficacy and safety profiles. Significance Statement This study investigated whether COVID-19-mediated concurrent hepatic downregulation and pulmonary upregulation of CYP3A4 leads to differences in the systemic and pulmonary concentrations of four respiratory medicines. The study demonstrated that intercompartmental differences in drug concentrations were driven by only hepatic CYP3A4 expression. This work suggests that ICU patients with significant COVID-19 - CYP3A4 interactions may be at risk of clinically relevant COVID-19-drug interactions, highlighting the need for optimizing dosing regimens in this patient group to improve safety and efficacy.

Heterotropic Allosteric Modulation of CYP3A4 In Vitro by Progesterone: Evidence for Improvement in Prediction of Time Dependent Inhibition for Macrolides.

Predictions of drug-drug interactions resulting from time-dependent inhibition (TDI) of CYP3A4 have consistently overestimated or mis-predicted (i.e. false positives) the interaction that is observed in vivo. Recent findings demonstrated that the presence of the allosteric modulator progesterone (PGS) in the in vitro assay could alter the in vitro kinetics of CYP3A4 TDI with inhibitors that interact with the heme moiety, such as metabolic-intermediate complex (MIC) forming inhibitors. The impact of the presence of 100 µM PGS on the TDI of molecules in the class of macrolides typically associated with MIC formation was investigated. Presence of PGS resulted in varied responses across the inhibitors tested. The TDI signal was eliminated for five inhibitors, and unaltered in the case of one, fidaxomicin. The remaining molecules erythromycin, clarithromycin, and troleandomycin, were observed to have a decrease in both potency and maximum inactivation rate ranging from 1.7-fold to 6.7-fold. These changes in TDI kinetics led to a >90% decrease in inactivation efficiency. In order to determine in vitro conditions that could reproduce in vivo inhibition, varied concentrations of PGS were incubated with clarithromycin and erythromycin. Resulting in vitro TDI kinetics were incorporated into dynamic physiologically-based pharmacokinetic (PBPK) models to predict clinically observed interactions. The results suggested that a concentration of ~45 µM PGS would result in TDI kinetic values that could reproduce in vivo observations and could potentially improve predictions for CYP3A4 TDI. Significance Statement The impact of the allosteric heterotropic modulator progesterone on the CYP3A4 time-dependent inhibition kinetics was quantified for a set of metabolic-intermediate complex forming mechanism-based inhibitors. We identify the in vitro conditions that optimally predict time-dependent inhibition for in vivo drug-drug interactions through dynamic physiologically-based pharmacokinetic modeling. The optimized assay conditions improve in vitro to in vivo translation and prediction of time-dependent inhibition.

Research Landscape of Physiologically Based Pharmacokinetic Model Utilization in Different Fields: A Bibliometric Analysis (1999-2023).

PURPOSE: The physiologically based pharmacokinetic (PBPK) modeling has received increasing attention owing to its excellent predictive abilities. However, there has been no bibliometric analysis about PBPK modeling. This research aimed to summarize the research development and hot points in PBPK model utilization overall through bibliometric analysis. METHODS: We searched for publications related to the PBPK modeling from 1999 to 2023 in the Web of Science Core Collection (WoSCC) database. The Microsoft Office Excel, CiteSpace and VOSviewers were used to perform the analyses. RESULTS: A total of 4,649 records from 1999 to 2023 were identified, and the largest number of publications focused in the period 2018-2023. The United States was the leading country, and the Environmental Protection Agency (EPA) was the leading institution. The journal Drug Metabolism and Disposition published and co-cited the most articles. Drug-drug interactions, special populations, and new drug development are the main topics in this research field. CONCLUSION: We first visualize the research landscape and hotspots of the PBPK modeling through bibliometric methods. Our study provides a better understanding for researchers, especially beginners about the dynamization of PBPK modeling and presents the relevant trend in the future.

Second-Order Effects of Chemotherapy Pharmacodynamics and Pharmacokinetics on Tumor Regression and Cachexia.

Drug dose response curves are ubiquitous in cancer biology, but these curves are often used to measure differential response in first-order effects: the effectiveness of increasing the cumulative dose delivered. In contrast, second-order effects (the variance of drug dose) are often ignored. Knowledge of second-order effects may improve the design of chemotherapy scheduling protocols, leading to improvements in tumor response without changing the total dose delivered. By considering treatment schedules with identical cumulative dose delivered, we characterize differential treatment outcomes resulting from high variance schedules (e.g. high dose, low dose) and low variance schedules (constant dose). We extend a previous framework used to quantify second-order effects, known as antifragility theory, to investigate the role of drug pharmacokinetics. Using a simple one-compartment model, we find that high variance schedules are effective for a wide range of cumulative dose values. Next, using a mouse-parameterized two-compartment model of 5-fluorouracil, we show that schedule viability depends on initial tumor volume. Finally, we illustrate the trade-off between tumor response and lean mass preservation. Mathematical modeling indicates that high variance dose schedules provide a potential path forward in mitigating the risk of chemotherapy-associated cachexia by preserving lean mass without sacrificing tumor response.

Modeled Hepatic/Plasma Exposures of Fluvastatin Prescribed Alone in Subjects with Impaired Cytochrome P450 2C9*3 as One of Possible Determinant Factors Likely Associated with Hepatic Toxicity Reported in a Japanese Adverse Event Database.

Fluvastatin is a 3-hydroxy-3-methylglutaryl CoA reductase inhibitor that competitively inhibits human cytochrome P450 (P450) 2C9 in vitro. Drug interactions between a variety of P450 2C9 substrates/inhibitors and fluvastatin can increase the incidence of fluvastatin-related hepatic or skeletal muscle toxicity in vivo. In this survey, the prescribed dosage of fluvastatin was reduced or discontinued in 133 of 164 patients receiving fluvastatin alone, as recorded in the Japanese Adverse Drug Event Report database of spontaneously reported events. The median days to onset of fluvastatin-related disorders were in the range 30-35 d in the 87 patients. Therefore, we aimed to focus on fluvastatin and, using the pharmacokinetic modeling technique, estimated the virtual plasma and hepatic exposures in subjects harboring the impaired CYP2C9*3 allele. The plasma concentrations of fluvastatin modeled after a virtual oral 20-mg dose increased in homozygotes with CYP2C9*3; the area under the plasma concentration curve was 4.9-fold higher than that in Japanese homozygotes for wild-type CYP2C9*1. The modeled hepatic concentrations of fluvastatin in patients with CYP2C9*3/*3 after virtual daily 20-mg doses for 7 d were 31-fold higher than those in subjects with CYP2C9*1/*1. However, heterozygous Chinese patients with CYP2C9*1/*3 reportedly have a limited elevation (1.2-fold) in plasma maximum concentrations. Virtual hepatic/plasma exposures in subjects harboring the impaired CYP2C9*3 allele estimated using pharmacokinetic modeling indicate that such exposure could be a causal factor for hepatic disorders induced by fluvastatin prescribed alone in a manner similar to that for interactions with a variety of co-administered drugs.

Modeled Hepatic/Plasma Exposures of Omeprazole Prescribed Alone in Cytochrome P450 2C19 Poor Metabolizers Are Likely Associated with Hepatic Toxicity Reported in a Japanese Adverse Event Database.

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.

Meropenem pharmacokinetic/pharmacodynamic target attainment and clinical response in ICU patients: A prospective observational study.

BACKGROUND: Several studies report lack of meropenem pharmacokinetic/pharmacodynamic (PK/PD) target attainment (TA) and risk of therapeutic failure with intermittent bolus infusions in intensive care unit (ICU) patients. The aim of this study was to describe meropenem TA in an ICU population and the clinical response in the first 72 h after therapy initiation. METHODS: A prospective observational study of ICU patients ≥18 years was conducted from 2014 to 2017. Patients with normal renal clearance (NRC) and augmented renal clearance (ARC) and patients on continuous renal replacement therapy (CRRT) were included. Meropenem was administered as intermittent bolus infusions, mainly at a dose of 1 g q6h. Peak, mid, and trough levels were sampled at 24, 48, and 72 h after therapy initiation. TA was defined as 100% T > 4× MIC or trough concentration above 4× MIC. Meropenem PK was estimated using traditional calculation methods and population pharmacokinetic modeling (P-metrics®). Clinical response was evaluated by change in C-reactive protein (CRP), Sequential Organ Failure Assessment (SOFA) score, leukocyte count, and defervescence. RESULTS: Eighty-seven patients were included, with a median Simplified Acute Physiology (SAPS) II score 37 and 90 days mortality rate of 32%. Median TA was 100% for all groups except for the ARC group with 45.5%. Median CRP fell from 175 (interquartile range [IQR], 88-257) to 70 (IQR, 30-114) (p < .001) in the total population. A reduction in SOFA score was observed only in the non-CRRT groups (p < .001). CONCLUSION: Intermittent meropenem bolus infusion q6h gives satisfactory TA in an ICU population with variable renal function and CRRT modality, except for ARC patients. No consistent relationship between TA and clinical endpoints were observed.

Pharmacokinetic modeling reveals parameters that govern tumor targeting and delivery by a pH-Low Insertion Peptide (pHLIP).

A pH-Low Insertion Peptide (pHLIP) is a pH-sensitive peptide that undergoes membrane insertion, resulting in transmembrane helix formation, on exposure to acidity at a tumor cell surface. As a result, pHLIPs preferentially accumulate within tumors and can be used for tumor-targeted imaging and drug delivery. Here we explore the determinants of pHLIP insertion, targeting, and delivery through a computational modeling approach. We generate a simple mathematical model to describe the transmembrane insertion process and then integrate it into a pharmacokinetic model, which predicts the tumor vs. normal tissue biodistribution of the most studied pHLIP, "wild-type pHLIP," over time after a single intravenous injection. From these models, we gain insight into the various mechanisms behind pHLIP tumor targeting and delivery, as well as the various biological parameters that influence it. Furthermore, we analyze how changing the properties of pHLIP can influence the efficacy of tumor targeting and delivery, and we predict the properties for optimal pHLIP phenotypes that have superior tumor targeting and delivery capabilities compared with wild-type pHLIP.

Probabilistic risk assessment of residential exposure to electric arc furnace steel slag using Bayesian model of relative bioavailability and PBPK modeling of manganese.

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.

Estimation of volatile organic compound exposure concentrations and time to reach a specific dermal absorption using physiologically based pharmacokinetic modeling.

A procedure was proposed to estimate dermal exposures based on a physiologically based pharmacokinetic (PBPK) model developed in rats. The study examined vapor concentrations ranging from 500 to 10,000 ppm for dibromomethane and 2,500 to 40,000 ppm for bromochloromethane. These concentrations were reconstructed based on chemical blood levels measured in 4 hr, with errors varying from 0.0% to 52.0%. The PBPK approach adequately predicted the blood concentrations and helped simulate contaminant transport through the stratum corneum and distribution in the body compartments. The proposed technique made it possible to estimate the skin absorption time (SAT) obtained from acute inhalation toxicity data. An inverse relationship exists between the SAT and exposure concentration. The method can be helpful in toxicology and risk assessment of hazardous volatile organic compounds.

A physiologically based pharmacokinetic model for the transdermal uptake of semivolatile organic compounds from the atmosphere and through clothing.

This study focuses on the semivolatile organic compound (SVOC) absorption through clothing and the skin. SVOCs are ubiquitous in daily life, in products like personal care items, plastics, and building materials. Understanding their permeation through the skin barrier is crucial for evaluating potential health risks of complete exposure. A PBPK model was developed to comprehend the dynamic interplay between SVOCs and human skin and to estimate tissue distribution throughout the body. The framework incorporated parameters such as skin permeability, physicochemical properties of the chemicals, and the impact of protective clothing and adsorbents. This model predicted the rate and extent of SVOC absorption under diverse scenarios. The PBPK predictions matched the experimental amount of mono-ethyl phthalate (MEP), a phthalate metabolite, when urine samples were collected for bare-skinned and clothed participants. Urine concentrations of MEP during a 6-hr exposure and for the next 48 hr show that clean clothing effectively decreased dermal uptake and the buildup of chemicals in the body. Additional removal of MEP was achieved through adsorption on activated carbon fabric. An increase in the maximum monolayer adsorption capacity or the Langmuir equilibrium constant further reduced the amount of MEP in the urine.

Optimizing anidulafungin exposure across a wide adult body size range.

Echinocandins like anidulafungin are first-line therapies for candidemia and invasive candidiasis, but their dosing may be suboptimal in obese patients. Our objective was to quantify anidulafungin exposure in a cohort of adults across a wide body size range to test if body size affects anidulafungin pharmacokinetics (PK). We enrolled 20 adults between the ages of 18 and 80 years, with an equal distribution of patients above and below a body mass index of 30 kg/m2. A single 100-mg dose of anidulafungin was administered, followed by intensive sampling over 72 h. Population PK analysis was used to identify and compare covariates of anidulafungin PK parameters. Monte Carlo simulations were performed to compute the probability of target attainment (PTA) based on alternative dosing regimens. Participants (45% males) had a median (range) age of 45 (21-78) years and a median (range) weight of 82.7 (42.4-208.3) kg. The observed median (range) of AUC0-∞ was 106.4 (51.9, 138.4) mg∙h/L. Lean body weight (LBW) and adjusted body weight (AdjBW) were more influential than weight as covariates of anidulafungin PK parameters. The conventional 100 mg daily maintenance is predicted to have a PTA below 90% in adults with an LBW > 55 kg or an AdjBW > 75 kg. A daily maintenance dose of 150-200 mg is predicted in these heavier adults. Anidulafungin AUC0-∞ declines with increasing body size. A higher maintenance dose will increase the PTA compared to the current approach in obese patients.

Effects of Body Mass and Age on the Pharmacokinetics of Subcutaneous or Hyaluronidase-facilitated Subcutaneous Immunoglobulin G in Primary Immunodeficiency Diseases.

PURPOSE: To assess the pharmacokinetics (PK) of subcutaneous immunoglobulin (SCIG) and hyaluronidase-facilitated SCIG (fSCIG) therapy across body mass index (BMI) and age categories in patients with primary immunodeficiency diseases (PIDD) previously treated with intravenous immunoglobulin (IVIG). METHODS: Using our previously published integrated population PK model based on data from eight clinical trials, simulations were conducted to examine the effects of BMI and age on serum immunoglobulin G (IgG) PK after administration of SCIG 0.15 g/kg weekly or fSCIG 0.6 g/kg every 4 weeks in patients switching from stable IVIG. Patients were assumed to have baseline IgG trough concentrations of 7 g/L (hypothetical protective threshold). RESULTS: Mean steady-state serum IgG trough values (Cmin,ss or trough) increased with BMI and age. Mean Cmin,ss was 18% (SCIG) and 16% (fSCIG) higher in the obese than the healthy BMI group. Pediatric patients aged < 18 years had 8-22% (SCIG) and 4-20% (fSCIG) lower mean Cmin,ss values than adults, with the youngest group (2- < 6 years) having the lowest Cmin,ss. All patients across populations maintained Cmin,ss IgG concentrations of ≥ 7 g/L after switching to SCIG or fSCIG. CONCLUSION: Both SCIG and fSCIG successfully maintained trough values at or above the hypothetical protective threshold after switching from stable IVIG, irrespective of BMI or age. Differences in trough values between BMI groups and age groups (≤ 22%) may not warrant SCIG or fSCIG dose adjustments based on BMI or age alone; instead, the dosing paradigm should be guided by prior IVIG dose, individual IgG monitoring, and clinical findings.