Pharmacokinetics and tumor delivery of nanoparticles.

Nanoparticles (NPs) have been widely used in different areas, including consumer products and medicine. In terms of biomedical applications, NPs or NP-based drug formulations have been extensively investigated for cancer diagnostics and therapy in preclinical studies, but the clinical translation rate is low. Therefore, a thorough and comprehensive understanding of the pharmacokinetics of NPs, especially in drug delivery efficiency to the target therapeutic tissue tumor, is important to design more effective nanomedicines and for proper assessment of the safety and risk of NPs. This review article focuses on the pharmacokinetics of both organic and inorganic NPs and their tumor delivery efficiencies, as well as the associated mechanisms involved. We discuss the absorption, distribution, metabolism, and excretion (ADME) processes following different routes of exposure and the mechanisms involved. Many physicochemical properties and experimental factors, including particle type, size, surface charge, zeta potential, surface coating, protein binding, dose, exposure route, species, cancer type, and tumor size can affect NP pharmacokinetics and tumor delivery efficiency. NPs can be absorbed with varying degrees following different exposure routes and mainly accumulate in liver and spleen, but also distribute to other tissues such as heart, lung, kidney and tumor tissues; and subsequently get metabolized and/or excreted mainly through hepatobiliary and renal elimination. Passive and active targeting strategies are the two major mechanisms of tumor delivery, while active targeting tends to have less toxicity and higher delivery efficiency through direct interaction between ligands and receptors. We also discuss challenges and perspectives remaining in the field of pharmacokinetics and tumor delivery efficiency of NPs.

Integration of Toxicogenomics and Physiologically Based Pharmacokinetic Modeling in Human Health Risk Assessment of Perfluorooctane Sulfonate.

Toxicogenomics and physiologically based pharmacokinetic (PBPK) models are useful approaches in chemical risk assessment, but the methodology to incorporate toxicogenomic data into a PBPK model to inform risk assessment remains to be developed. This study aimed to develop a probabilistic human health risk assessment approach by integrating toxicogenomic dose-response data and PBPK modeling using perfluorooctane sulfonate (PFOS) as a case study. Based on the available human in vitro and mouse in vivo toxicogenomic data, we identified the differentially expressed genes (DEGs) at each exposure paradigm/duration. Kyoto Encyclopedia of Genes and Genomes and disease ontology enrichment analyses were conducted on the DEGs to identify significantly enriched pathways and diseases. The dose-response data of DEGs were analyzed using the Bayesian benchmark dose (BMD) method. Using a previously published PBPK model, the gene BMDs were converted to human equivalent doses (HEDs), which were summarized to pathway and disease HEDs and then extrapolated to reference doses (RfDs) by considering an uncertainty factor of 30 for mouse in vivo data and 10 for human in vitro data. The results suggested that the median RfDs at different exposure paradigms were similar to the 2016 U.S. Environmental Protection Agency's recommended RfD, while the RfDs for the most sensitive pathways and diseases were closer to the recent European Food Safety Authority's guidance values. In conclusion, genomic dose-response data and PBPK modeling can be integrated to become a useful alternative approach in risk assessment of environmental chemicals. This approach considers multiple endpoints, provides toxicity mechanistic insights, and does not rely on apical toxicity endpoints.

Development of a multi-route physiologically based pharmacokinetic (PBPK) model for nanomaterials: a comparison between a traditional versus a new route-specific approach using gold nanoparticles in rats.

BACKGROUND: Physiologically based pharmacokinetic (PBPK) modeling is an important tool in predicting target organ dosimetry and risk assessment of nanoparticles (NPs). The methodology of building a multi-route PBPK model for NPs has not been established, nor systematically evaluated. In this study, we hypothesized that the traditional route-to-route extrapolation approach of PBPK modeling that is typically used for small molecules may not be appropriate for NPs. To test this hypothesis, the objective of this study was to develop a multi-route PBPK model for different sizes (1.4-200 nm) of gold nanoparticles (AuNPs) in adult rats following different routes of administration (i.e., intravenous (IV), oral gavage, intratracheal instillation, and endotracheal inhalation) using two approaches: a traditional route-to-route extrapolation approach for small molecules and a new approach that is based on route-specific data that we propose to be applied generally to NPs. RESULTS: We found that the PBPK model using this new approach had superior performance than the traditional approach. The final PBPK model was optimized rigorously using a Bayesian hierarchical approach with Markov chain Monte Carlo simulations, and then converted to a web-based interface using R Shiny. In addition, quantitative structure-activity relationships (QSAR) based multivariate linear regressions were established to predict the route-specific key biodistribution parameters (e.g., maximum uptake rate) based on the physicochemical properties of AuNPs (e.g., size, surface area, dose, Zeta potential, and NP numbers). These results showed the size and surface area of AuNPs were the main determinants for endocytic/phagocytic uptake rates regardless of the route of administration, while Zeta potential was an important parameter for the estimation of the exocytic release rates following IV administration. CONCLUSIONS: This study suggests that traditional route-to-route extrapolation approaches for PBPK modeling of small molecules are not applicable to NPs. Therefore, multi-route PBPK models for NPs should be developed using route-specific data. This novel PBPK-based web interface serves as a foundation for extrapolating to other NPs and to humans to facilitate biodistribution estimation, safety, and risk assessment of NPs.

Residue depletion profiles and withdrawal interval estimations of meloxicam in eggs and ovarian follicles following intravenous (Meloxicam solution for injection) and oral (Meloxidyl®) administration in domestic chickens (Gallus domesticus).

Meloxicam is a non-steroidal anti-inflammatory drug (NSAID) commonly prescribed in an extralabel manner for treating chickens in urbanized settings. The objectives of this study were to determine meloxicam depletion profiles in eggs and ovarian follicles and to estimate associated withdrawal intervals (WDI) in laying hens following a single intravenous or repeated oral administration. The observed peak concentration of meloxicam in ovarian follicles were consistently higher than in egg yolk and egg white samples. Terminal half-lives were 31-h, 113-h and 12-h in ovarian follicles, egg yolk and egg white samples, respectively, for repeated oral administrations at 1 mg/kg for 20 doses at 12-h intervals. The terminal half-life following a single intravenous administration at 1 mg/kg was 50-h for ovarian follicles. Meloxicam WDI estimations using ovarian follicle and egg yolk concentration data following 20 doses at 12-h intervals were 36 and 12 days, respectively. Meloxicam WDI estimation using egg yolk concentration data following 8 doses at 24-h intervals was 12 days. These results improve our understanding on the residue depletion of meloxicam from chickens' reproductive tracts and egg products and provide WDIs to help ensure food safety for humans consuming eggs from treated laying hens.

Physiological parameter values for physiologically based pharmacokinetic models in food-producing animals. Part III: Sheep and goat.

This report is the third in a series of studies that aimed to compile physiological parameters related to develop physiologically based pharmacokinetic (PBPK) models for drugs and environmental chemicals in food-producing animals including swine and cattle (Part I), chickens and turkeys (Part II), and finally sheep and goats (the focus of this manuscript). Literature searches were conducted in multiple databases (PubMed, Google Scholar, ScienceDirect, and ProQuest), with data on relevant parameters including body weight, relative organ weight (% of body weight), cardiac output, relative organ blood flow (% of cardiac output), residual blood volume (% of organ weight), and hematocrit reviewed and statistically summarized. The mean and standard deviation of each parameter are presented in tables. Equations describing the growth curves of sheep and goats are presented in figures. When data are sufficient, parameter values are reported for different ages or production classes of sheep, including fetal sheep, lambs, and market-age sheep (mature sheep). These data provide a reference database for developing standardized PBPK models to predict drug withdrawal intervals in sheep and goats, and also provide a basis for extrapolating PBPK models from major species such as cattle to minor species such as sheep and goats.

A study to assess the correlation between plasma, oral fluid and urine concentrations of flunixin meglumine with the tissue residue depletion profile in finishing-age swine.

BACKGROUND: Flunixin meglumine (FM) was investigated for the effectiveness of plasma, oral fluid, and urine concentrations to predict tissue residue depletion profiles in finishing-age swine, along with the potential for untreated pigs to acquire tissue residues following commingled housing with FM-treated pigs. Twenty pigs were housed in groups of three treated and one untreated control. Treated pigs received one 2.2 mg/kg dose of FM intramuscularly. Before treatment and at 1, 3, 6, 12, 24, 36, and 48 h (h) after treatment, plasma samples were taken. At 1, 4, 8, 12 and 16 days (d) post-treatment, necropsy and collection of plasma, urine, oral fluid, muscle, liver, kidney, and injection site samples took place. Analysis of flunixin concentrations using liquid chromatography/tandem mass spectrometry was done. A published physiologically based pharmacokinetic (PBPK) model for flunixin in cattle was extrapolated to swine to simulate the measured data. RESULTS: Plasma concentrations of flunixin were the highest at 1 h post-treatment, ranging from 1534 to 7040 ng/mL, and were less than limit of quantification (LOQ) of 5 ng/mL in all samples on Day 4. Flunixin was detected in the liver and kidney only on Day 1, but was not found 4-16 d post-treatment. Flunixin was either not seen or found less than LOQ in the muscle, with the exception of one sample on Day 16 at a level close to LOQ. Flunixin was found in the urine of untreated pigs after commingled housing with FM-treated pigs. The PBPK model adequately correlated plasma, oral fluid and urine concentrations of flunixin with residue depletion profiles in liver, kidney, and muscle of finishing-age pigs, especially within 24 h after dosing. CONCLUSIONS: Results indicate untreated pigs can be exposed to flunixin by shared housing with FM-treated pigs due to environmental contamination. Plasma and urine samples may serve as less invasive and more easily accessible biological matrices to predict tissue residue statuses of flunixin in pigs at earlier time points (≤24 h) by using a PBPK model.

Clinical pharmacokinetics and outcomes of oral fluconazole therapy in dogs and cats with naturally occurring fungal disease.

This multi-institutional study was designed to determine the clinical pharmacokinetics of fluconazole and outcomes in client-owned dogs (n = 37) and cats (n = 35) with fungal disease. Fluconazole serum concentrations were measured. Pharmacokinetic analysis was limited to animals at steady state (≥72 hr of treatment). The mean (range) body weight in 31 dogs was 25.6 (2.8-58.2) kg and in 31 cats was 3.9 (2.4-6.1) kg included in pharmacokinetic analyses. The dose, average steady-state serum concentrations (CSS ), and oral clearance in dogs were 14.2 (4.5-21.3) mg/kg/d, 26.8 (3.8-61.5) µg/mL, and 0.63 ml min-1  kg-1 , respectively, and in cats were 18.6 (8.2-40.0) mg/kg/d, 32.1 (1.9-103.5) µg/mL, and 0.61 ml min-1  kg-1 , respectively. Random inter-animal pharmacokinetic variability was high in both species. Two dogs had near twofold increases in serum fluconazole when generic formulations were changed, suggesting lack of bioequivalence. Median CSS for dogs and cats achieving clinical remission was 19.4 and 35.8 µg/ml, respectively. Starting oral doses of 10 mg/kg q12h in dogs and 50-100 mg total daily dose in cats are recommended to achieve median CSS associated with clinical remission. Due to the large pharmacokinetic variability, individualized dose adjustments based on CSS (therapeutic drug monitoring) and treatment failure should be considered.

Physiological parameter values for physiologically based pharmacokinetic models in food-producing animals. Part II: Chicken and turkey.

Physiologically based pharmacokinetic (PBPK) models are growing in popularity due to human food safety concerns and for estimating drug residue distribution and estimating withdrawal intervals for veterinary products originating from livestock species. This paper focuses on the physiological and anatomical data, including cardiac output, organ weight, and blood flow values, needed for PBPK modeling applications for avian species commonly consumed in the poultry market. Experimental and field studies from 1940 to 2019 for broiler chickens (1-70 days old, 40 g - 3.2 kg), laying hens (4-15 months old, 1.1-2.0 kg), and turkeys (1 day-14 months old, 60 g -12.7 kg) were searched systematically using PubMed, Google Scholar, ProQuest, and ScienceDirect for data collection in 2019 and 2020. Relevant data were extracted from the literature with mean and standard deviation (SD) being calculated and compiled in tables of relative organ weights (% of body weight) and relative blood flows (% of cardiac output). Trends of organ or tissue weight growth during different life stages were calculated when sufficient data were available. These compiled data sets facilitate future PBPK model development and applications, especially in estimating chemical residue concentrations in edible tissues to calculate food safety withdrawal intervals for poultry.

Physiological parameter values for physiologically based pharmacokinetic models in food-producing animals. Part I: Cattle and swine.

Physiologically based pharmacokinetic (PBPK) models for chemicals in food animals are a useful tool in estimating chemical tissue residues and withdrawal intervals. Physiological parameters such as organ weights and blood flows are an important component of a PBPK model. The objective of this study was to compile PBPK-related physiological parameter data in food animals, including cattle and swine. Comprehensive literature searches were performed in PubMed, Google Scholar, ScienceDirect, and ProQuest. Relevant literature was reviewed and tables of relevant parameters such as relative organ weights (% of body weight) and relative blood flows (% of cardiac output) were compiled for different production classes of cattle and swine. The mean and standard deviation of each parameter were calculated to characterize their variability and uncertainty and to allow investigators to conduct population PBPK analysis via Monte Carlo simulations. Regression equations using weight or age were created for parameters having sufficient data. These compiled data provide a comprehensive physiological parameter database for developing PBPK models of chemicals in cattle and swine to support animal-derived food safety assessment. This work also provides a basis to compile data in other food animal species, including goats, sheep, chickens, and turkeys.

Translating Nanomedicine to Comparative Oncology-the Case for Combining Zinc Oxide Nanomaterials with Nucleic Acid Therapeutic and Protein Delivery for Treating Metastatic Cancer.

The unique anticancer, biochemical, and immunologic properties of nanomaterials are becoming a new tool in biomedical research. Their translation into the clinic promises a new wave of targeted therapies. One nanomaterial of particular interest are zinc oxide (ZnO) nanoparticles (NPs), which has distinct mechanisms of anticancer activity including unique surface, induction of reactive oxygen species, lipid oxidation, pH, and also ionic gradients within cancer cells and the tumor microenvironment. It is recognized that ZnO NPs can serve as a direct enzyme inhibitor. Significantly, ZnO NPs inhibit extracellular signal-regulated kinase (ERK) and protein kinase B (AKT) associated with melanoma progression, drug resistance, and metastasis. Indeed, direct intratumoral injection of ZnO NPs or a complex of ZnO with RNA significantly suppresses ERK and AKT phosphorylation. These data suggest ZnO NPs and their complexes or conjugates with nucleic acid therapeutic or anticancer protein may represent a potential new strategy for the treatment of metastatic melanoma, and potentially other cancers. This review focuses on the anticancer mechanisms of ZnO NPs and what is currently known about its biochemical effects on melanoma, biologic activity, and pharmacokinetics in rodents and its potential for translation into large animal, spontaneously developing models of melanoma and other cancers, which represent models of comparative oncology.

Methamphetamine produces cardiac damage and apoptosis by decreasing melusin.

Methamphetamine (METH) is an amphetamine-type drug that is highly addictive and widely abused. Many studies have shown that METH exposure causes severe damage not only to the nervous system but also to the cardiovascular system. Melusin protein is a mechanotransducer that plays an important role in maintaining normal heart function. However, the role of melusin in METH-induced cardiotoxicity has not yet been reported. We hypothesized that methamphetamine can produce cardiac damage and apoptosis by decreasing the quantity of melusin. To test this hypothesis, we determined the protein expression of melusin and apoptosis markers in METH-treated rats and primary rat cardiomyocytes. We also established a melusin-overexpressing cell model to assess the importance of melusin in maintaining antiapoptotic pathways. To confirm our findings from the in vitro and animal models, we also evaluated the apoptotic index of cardiomyocytes and the protein expression of apoptotic markers in postmortem heart tissues from deceased METH abusers and age-matched control subjects. The results showed that the apoptosis of cardiomyocytes was increased significantly and that the protein expression of melusin was decreased after exposure to METH in primary rat cardiomyocytes, in rats and in humans. METH treatment also decreased the expression of the downstream proteins FAK, IQGAP1, p-AKT, p-GSK3ß, and p-ERK in primary rat cardiomyocytes and in vivo. After overexpression of melusin, the above effects were partially reversed in primary rat cardiomyocytes. We conclude that METH can produce cardiac damage and apoptosis by decreasing melusin, while melusin-activated signaling by phosphorylated AKT, phosphorylated GSK3ß, and ERK may be resistant to methamphetamine-induced myocardial apoptosis.

Methamphetamine exposure triggers apoptosis and autophagy in neuronal cells by activating the C/EBPß-related signaling pathway.

Methamphetamine (Meth) is a widely abused psychoactive drug that primarily damages the nervous system, notably causing dopaminergic neuronal apoptosis. CCAAT-enhancer binding protein (C/EBPß) is a transcription factor and an important regulator of cell apoptosis and autophagy. Insulin-like growth factor binding protein (IGFBP5) is a proapoptotic factor that mediates Meth-induced neuronal apoptosis, and Trib3 (tribbles pseudokinase 3) is an endoplasmic reticulum (ER) stress-inducible gene involved in autophagic cell death through the mammalian target of rapamycin (mTOR) signaling pathway. To test the hypothesis that C/EBPß is involved in Meth-induced IGFBP5-mediated neuronal apoptosis and Trib3-mediated neuronal autophagy, we measured the protein expression of C/EBPß after Meth exposure and evaluated the effects of silencing C/EBPß, IGFBP5, or Trib3 on Meth-induced apoptosis and autophagy in neuronal cells and in the rat striatum after intrastriatal Meth injection. We found that, at relatively high doses, Meth exposure increased C/EBPß protein expression, which was accompanied by increased neuronal apoptosis and autophagy; triggered the IGFBP5-mediated, p53-up-regulated modulator of apoptosis (PUMA)-related mitochondrial apoptotic signaling pathway; and stimulated the Trib3-mediated ER stress signaling pathway through the Akt-mTOR signaling axis. We also found that autophagy is an early response to Meth-induced stress upstream of apoptosis and plays a detrimental role in Meth-induced neuronal cell death. These results suggest that Meth exposure induces C/EBPß expression, which plays an essential role in the neuronal apoptosis and autophagy induced by relatively high doses of Meth; however, relatively low concentrations of Meth did not change the expression of C/EBPß in vitro. Further studies are needed to elucidate the role of C/EBPß in low-dose Meth-induced neurotoxicity.-Xu, X., Huang, E., Luo, B., Cai, D., Zhao, X., Luo, Q., Jin, Y., Chen, L., Wang, Q., Liu, C., Lin, Z., Xie, W.-B., Wang, H. Methamphetamine exposure triggers apoptosis and autophagy in neuronal cells by activating the C/EBPß-related signaling pathway.

Integration of Food Animal Residue Avoidance Databank (FARAD) empirical methods for drug withdrawal interval determination with a mechanistic population-based interactive physiologically based pharmacokinetic (iPBPK) modeling platform: example for flunixin meglumine administration.

Violative chemical residues in animal-derived food products affect food safety globally and have impact on the trade of international agricultural products. The Food Animal Residue Avoidance Databank program has been developing scientific tools to provide appropriate withdrawal interval (WDI) estimations after extralabel drug use in food animals for the past three decades. One of the tools is physiologically based pharmacokinetic (PBPK) modeling, which is a mechanistic-based approach that can be used to predict tissue residues and WDIs. However, PBPK models are complicated and difficult to use by non-modelers. Therefore, a user-friendly PBPK modeling framework is needed to move this field forward. Flunixin was one of the top five violative drug residues identified in the United States from 2010 to 2016. The objective of this study was to establish a web-based user-friendly framework for the development of new PBPK models for drugs administered to food animals. Specifically, a new PBPK model for both cattle and swine after administration of flunixin meglumine was developed. Population analysis using Monte Carlo simulations was incorporated into the model to predict WDIs following extralabel administration of flunixin meglumine. The population PBPK model was converted to a web-based interactive PBPK (iPBPK) framework to facilitate its application. This iPBPK framework serves as a proof-of-concept for further improvements in the future and it can be applied to develop new models for other drugs in other food animal species, thereby facilitating the application of PBPK modeling in WDI estimation and food safety assessment.

An integrated experimental and physiologically based pharmacokinetic modeling study of penicillin G in heavy sows.

Penicillin G is widely used in food-producing animals at extralabel doses and is one of the most frequently identified violative drug residues in animal-derived food products. In this study, the plasma pharmacokinetics and tissue residue depletion of penicillin G in heavy sows after repeated intramuscular administrations at label (6.5 mg/kg) and 5 × label (32.5 mg/kg) doses were determined. Plasma, urine, and environmental samples were tested as potential antemortem markers for penicillin G residues. The collected new data and other available data from the literature were used to develop a population physiologically based pharmacokinetic (PBPK) model for penicillin G in heavy sows. The results showed that antemortem testing of urine provided potential correlation with tissue residue levels. Based on the United States Department of Agriculture Food Safety and Inspection Service action limit of 25 ng/g, the model estimated a withdrawal interval of 38 days for penicillin G in heavy sows after 3 repeated intramuscular injections at 5 × label dose. This study improves our understanding of penicillin G pharmacokinetics and tissue residue depletion in heavy sows and provides a tool to predict proper withdrawal intervals after extralabel use of penicillin G in heavy sows, thereby helping safety assessment of sow-derived meat products.

The construction and application of a population physiologically based pharmacokinetic model for methadone in Beagles and Greyhounds.

Methadone is an opioid analgesic in veterinary and human medicine. To help develop appropriate pain management practices and to develop a quantitative model for predicting methadone dosimetry, a flow-limited multiroute physiologically based pharmacokinetic (PBPK) model for methadone in dogs constructed with Berkeley Madonna™ was developed. The model accounts for intravenous (IV), subcutaneous (SC), and oral administrations, and compartmentalizes the body into different components. This model was calibrated from plasma pharmacokinetic data after IV administration of methadone in Beagles and Greyhounds. The calibrated model was evaluated with independent data in both breeds of dogs. One advantage of this model is that most physiological parameter values for Greyhounds were taken directly from the original literature. The developed model simulates available pharmacokinetic data for plasma concentrations well for both breeds. After conducting regression analysis, all simulated datasets produced an R2  > 0.80 when compared to the measured plasma concentrations. Comparative analysis of the dosimetry of methadone between the breeds suggested that Greyhounds had ~50% lower 24-hr area under the curve (AUC) of plasma or brain concentrations than in Beagles. Furthermore, population analysis was conducted with this study. This model can be used to predict methadone concentrations in multiple dog breeds using breed-specific parameters.

DNA damage-inducible transcript 4 (DDIT4) mediates methamphetamine-induced autophagy and apoptosis through mTOR signaling pathway in cardiomyocytes.

Methamphetamine (METH) is an amphetamine-like psychostimulant that is commonly abused. Previous studies have shown that METH can induce damages to the nervous system and recent studies suggest that METH can also cause adverse and potentially lethal effects on the cardiovascular system. Recently, we demonstrated that DNA damage-inducible transcript 4 (DDIT4) regulates METH-induced neurotoxicity. However, the role of DDIT4 in METH-induced cardiotoxicity remains unknown. We hypothesized that DDIT4 may mediate METH-induced autophagy and apoptosis in cardiomyocytes. To test the hypothesis, we examined DDIT4 protein expression in cardiomyocytes and in heart tissues of rats exposed to METH with Western blotting. We also determined the effects on METH-induced autophagy and apoptosis after silencing DDIT4 expression with synthetic siRNA with or without pretreatment of a mTOR inhibitor rapamycin in cardiomyocytes using Western blot analysis, fluorescence microscopy and TUNEL staining. Our results showed that METH exposure increased DDIT4 expression and decreased phosphorylation of mTOR that was accompanied with increased autophagy and apoptosis both in vitro and in vivo. These effects were normalized after silencing DDIT4. On the other hand, rapamycin promoted METH-induced autophagy and apoptosis in DDIT4 knockdown cardiomyocytes. These results suggest that DDIT4 mediates METH-induced autophagy and apoptosis through mTOR signaling pathway in cardiomyocytes.

Estimation of tulathromycin depletion in plasma and milk after subcutaneous injection in lactating goats using a nonlinear mixed-effects pharmacokinetic modeling approach.

BACKGROUND: Extra-label use of tulathromycin in lactating goats is common and may cause violative residues in milk. The objective of this study was to develop a nonlinear mixed-effects pharmacokinetic (NLME-PK) model to estimate tulathromycin depletion in plasma and milk of lactating goats. Eight lactating goats received two subcutaneous injections of 2.5 mg/kg tulathromycin 7 days apart; blood and milk samples were analyzed for concentrations of tulathromycin and the common fragment of tulathromycin (i.e., the marker residue CP-60,300), respectively, using liquid chromatography mass spectrometry. Based on these new data and related literature data, a NLME-PK compartmental model with first-order absorption and elimination was used to model plasma concentrations and cumulative excreted amount in milk. Monte Carlo simulations with 100 replicates were performed to predict the time when the upper limit of the 95% confidence interval of milk concentrations was below the tolerance. RESULTS: All animals were healthy throughout the study with normal appetite and milk production levels, and with mild-moderate injection-site reactions that diminished by the end of the study. The measured data showed that milk concentrations of the marker residue of tulathromycin were below the limit of detection (LOD = 1.8 ng/ml) 39 days after the second injection. A 2-compartment model with milk as an excretory compartment best described tulathromycin plasma and CP-60,300 milk pharmacokinetic data. The model-predicted data correlated with the measured data very well. The NLME-PK model estimated that tulathromycin plasma concentrations were below LOD (1.2 ng/ml) 43 days after a single injection, and 62 days after the second injection with a 95% confidence. These estimated times are much longer than the current meat withdrawal time recommendation of 18 days for tulathromycin in non-lactating cattle. CONCLUSIONS: The results suggest that twice subcutaneous injections of 2.5 mg/kg tulathromycin are a clinically safe extra-label alternative approach for treating pulmonary infections in lactating goats, but a prolonged withdrawal time of at least 39 days after the second injection should be considered to prevent violative residues in milk and any dairy goat being used for meat should have an extended meat withdrawal time.

Exploring the potential and challenges of developing physiologically-based toxicokinetic models to support human health risk assessment of microplastic and nanoplastic particles.

Microplastics (MPs) and nanoplastics (NPs) pollution has emerged as a significant and widespread environmental issue. Humans are inevitably exposed to MPs and NPs via ingestion, inhalation, and dermal contacts from various sources. However, mechanistic knowledge of their distribution, interaction, and potency in the body is still lacking. To address this knowledge gap, we have undertaken the task of elucidating the toxicokinetic (TK) behaviors of MPs and NPs, aiming to provide mechanistic information for constructing a conceptual physiologically based toxicokinetic (PBTK) model to support in silico modeling approaches. Our effort involved a thorough examination of the existing literature and data collation on the presence of MPs in the human body and in vitro/ex vivo/in vivo biodistribution across various cells and tissues. By comprehending the absorption, distribution, metabolism, and excretion mechanisms of MPs and NPs in relation to their physicochemical attributes, we established a foundational understanding of the link between external exposure and internal tissue dosimetry. We observed that particle size and surface chemistry have been thoroughly explored in previous experimental studies. However, certain attributes, such as polymer type, shape, and biofilm/biocorona, warrant attention and further examination. We discussed the fundamental disparities in TK properties of MPs/NPs from those of engineered nanoparticles. We proposed a preliminary PBTK framework with several possible modeling approaches and discussed existing challenges for further investigation. Overall, this article provides a comprehensive compilation of existing TK data of MPs/NPs, a critical overview of TK processes and mechanisms, and proposes potential PBTK modeling approaches, particularly regarding their applicability to the human system, and outlines future perspectives for developing PBTK models and their integration into human health risk assessment of MPs and NPs.

Impact of protein coronas on nanoparticle interactions with tissues and targeted delivery.

A major challenge in advancing nanoparticle (NP)-based delivery systems stems from the intricate interactions between NPs and biological systems. These interactions are largely determined by the formation of the NP-protein corona (PC), in which proteins spontaneously adsorb to the surface of NPs. The PC endows the NPs with a new biological identity, capable of altering the interactions of NPs with targeting organs and subsequent biological fate. This review discusses the mechanisms behind PC-mediated effects on tissue distribution of NPs, aiming to provide insights into the role of PC and its potential applications in NP-based drug delivery.

Preface to the special issue of Food and Chemical Toxicology on "New approach methodologies and machine learning in food safety and chemical risk assessment: Development of reproducible, open-source, and user-friendly tools for exposure, toxicokinetic, and toxicity assessments in the 21st century".

This Special Issue contains articles on applications of various new approach methodologies (NAMs) in the field of toxicology and risk assessment. These NAMs include in vitro high-throughput screening, quantitative structure-activity relationship (QSAR) modeling, physiologically based pharmacokinetic (PBPK) modeling, network toxicology analysis, molecular docking simulation, omics, machine learning, deep learning, and "template-and-anchor" multiscale computational modeling. These in vitro and in silico approaches complement each other and can be integrated together to support different applications of toxicology, including food safety assessment, dietary exposure assessment, chemical toxicity potency screening and ranking, chemical toxicity prediction, chemical toxicokinetic simulation, and to investigate the potential mechanisms of toxicities, as introduced further in selected articles in this Special Issue.