Considerations for Improving Metabolism Predictions for In Vitro to In Vivo Extrapolation

Investigation of parenteral nutrition-induced hepatotoxicity using human liver spheroid co-cultures

Parenteral nutrition (PN) is typically administered to individuals with gastrointestinal dysfunction, a contraindication for enteral feeding, and a need for nutritional therapy. When PN is the only energy source in patients, it is defined as total parenteral nutrition (TPN). TPN is a life-saving approach for different patient populations, both in infants and adults. However, despite numerous benefits, TPN can cause adverse effects, including metabolic disorders and liver injury. TPN-associated liver injury, known as intestinal failure-associated liver disease (IFALD), represents a significant problem affecting up to 90% of individuals receiving TPN. IFALD pathogenesis is complex, depending on the TPN components as well as on the patient's medical conditions. Despite numerous animal studies and clinical observations, the molecular mechanisms driving IFALD remain largely unknown. The present study was set up to elucidate the mechanisms underlying IFALD. For this purpose, human liver spheroid co-cultures were treated with a TPN mixture, followed by RNA sequencing analysis. Subsequently, following exposure to TPN and its single nutritional components, several key events of liver injury, including mitochondrial dysfunction, endoplasmic reticulum stress, oxidative stress, apoptosis, and lipid accumulation (steatosis), were studied using various techniques. It was found that prolonged exposure to TPN substantially changes the transcriptome profile of liver spheroids and affects multiple metabolic and signaling pathways contributing to liver injury. Moreover, TPN and its main components, especially lipid emulsion, induce changes in all key events measured and trigger steatosis.

Ulgen K. Advances in Physiologically Based Pharmacokinetic (PBPK) Modeling of Nanomaterials

Nanoparticles (NPs) have been widely used to improve the pharmacokinetic properties and tissue distribution of small molecules such as targeting to a specific tissue of interest, enhancing their systemic circulation, and enlarging their therapeutic properties. NPs have unique and complicated in vivo disposition properties compared to small molecule drugs due to their complex multifunctionality. Physiologically based pharmacokinetic (PBPK) modeling has been a powerful tool in the simulation of the absorption, distribution, metabolism, and elimination (ADME) characteristics of the materials, and it can be used in the characterization and prediction of the systemic disposition, toxicity, efficacy, and target exposure of various types of nanoparticles. In this review, recent advances in PBPK model applications related to the nanoparticles with unique properties, and dispositional features in the biological systems, ADME characteristics, the description of transport processes of nanoparticles in the PBPK model, and the challenges in PBPK model development of nanoparticles are delineated and juxtaposed with those encountered in small molecule models. Nanoparticle related, non-nanoparticle-related, and interspecies-scaling methods applied in PBPK modeling are reviewed. In vitro to in vivo extrapolation (IVIVE) methods being a promising computational tool to provide in vivo predictions from the results of in vitro and in silico studies are discussed. Finally, as a recent advancement ML/AI-based approaches and challenges in PBPK modeling in the estimation of ADME parameters and pharmacokinetic (PK) analysis results are introduced.

Data set of fraction unbound values in the in vitro incubations for metabolic studies for better prediction of human clearance

In vitro-in vivo extrapolation is a commonly applied technique for liver clearance prediction. Various in vitro models are available such as hepatocytes, human liver microsomes, or recombinant cytochromes P450. According to the free drug theory, only the unbound fraction (fu) of a chemical can undergo metabolic changes. Therefore, to ensure the reliability of predictions, both specific and nonspecific binding in the model should be accounted. However, the fraction unbound in the experiment is often not reported. The study aimed to provide a detailed repository of the literature data on the compound's fu value in various in vitro systems used for drug metabolism evaluation and corresponding human plasma binding levels. Data on the free fraction in plasma and different in vitro models were supplemented with the following information: the experimental method used for the assessment of the degree of drug binding, protein or cell concentration in the incubation, and other experimental conditions, if different from the standard ones, species, reference to the source publication, and the author's name and date of publication. In total, we collected 129 literature studies on 1425 different compounds. The provided data set can be used as a reference for scientists involved in pharmacokinetic/physiologically based pharmacokinetic modelling as well as researchers interested in Quantitative Structure-Activity Relationship models for the prediction of fraction unbound based on compound structure. Database URL: https://data.mendeley.com/datasets/3bs5526htd/1.

Wildlife ecological risk assessment in the 21st century: Promising technologies to assess toxicological effects

Despite advances in toxicity testing and the development of new approach methodologies (NAMs) for hazard assessment, the ecological risk assessment (ERA) framework for terrestrial wildlife (i.e., air-breathing amphibians, reptiles, birds, and mammals) has remained unchanged for decades. While survival, growth, and reproductive endpoints derived from whole-animal toxicity tests are central to hazard assessment, nonstandard measures of biological effects at multiple levels of biological organization (e.g., molecular, cellular, tissue, organ, organism, population, community, ecosystem) have the potential to enhance the relevance of prospective and retrospective wildlife ERAs. Other factors (e.g., indirect effects of contaminants on food supplies and infectious disease processes) are influenced by toxicants at individual, population, and community levels, and need to be factored into chemically based risk assessments to enhance the "eco" component of ERAs. Regulatory and logistical challenges often relegate such nonstandard endpoints and indirect effects to postregistration evaluations of pesticides and industrial chemicals and contaminated site evaluations. While NAMs are being developed, to date, their applications in ERAs focused on wildlife have been limited. No single magic tool or model will address all uncertainties in hazard assessment. Modernizing wildlife ERAs will likely entail combinations of laboratory- and field-derived data at multiple levels of biological organization, knowledge collection solutions (e.g., systematic review, adverse outcome pathway frameworks), and inferential methods that facilitate integrations and risk estimations focused on species, populations, interspecific extrapolations, and ecosystem services modeling, with less dependence on whole-animal data and simple hazard ratios. Integr Environ Assess Manag 2024;20:725-748. © 2023 His Majesty the King in Right of Canada and The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC). Reproduced with the permission of the Minister of Environment and Climate Change Canada. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

Endoplasmic reticulum stress and pro-inflammatory responses induced by phthalate metabolites monoethylhexyl phthalate and monobutyl phthalate in 1.1B4 pancreatic beta cells

In recent years, phthalates and their metabolites have been associated with metabolic diseases such as diabetes mellitus. To investigate the effects of phthalate metabolites exposure on insulin production and release, 1.1B4 pancreatic beta cells were treated with different concentrations (0.001-1000 µM) of monoethylhexyl phthalate (MEHP) and monobutyl phthalate (MBP). For such purpose, the 1.1B4 cells were evaluated for their viability, apoptosis rate, lysosomal membrane permeabilization (LMP), mitochondrial membrane potential (ΔΨm), oxidative stress, ER stress status, in addition to their secretory functions. MEHP, not MBP, exhibited a notable reduction in metabolic viability, particularly at higher concentrations (500 and 1000 µM) following 24-hour exposure. Similarly, both MEHP and MBP induced decreased metabolic viability at high concentrations after 48- and 72-hour exposure. Notably, neither MEHP nor MBP demonstrated a significant impact on apoptosis rates after 24-hour exposure, and MBP induced mild necrosis at 1000 µM concentration. Cell proliferation rates, indicated by PCNA expression, decreased with 10 and 1000 µM MEHP and 0.1 and 10 µM MBP exposures. LMP analysis revealed an increase in 1000 µM MBP group. Exposure to 0.001 µM of both MEHP and MBP significantly reduced cellular glutathione (GSH) levels. No significant change in intracellular reactive oxygen species (ROS) levels and ΔΨm was observed, but MBP-exposed cells exhibited elevated levels of lipid peroxidation. Functional assessments of pancreatic beta cells unveiled reduced insulin secretion at low glucose concentrations following exposure to both MEHP and MBP, with concurrent alterations in the expression levels of key proteins associated with beta cell function, including GLUT1, GCK, PDX1, and MafA. Moreover, MEHP and MBP exposures were associated with alterations in ER stress-related pathways, including JNK, GADD153, and NF-κB expression, as well as PPARα and PPARγ levels. In conclusion, this study provides comprehensive insights into the diverse impacts of MEHP and MBP on 1.1B4 pancreatic beta cells, emphasizing their potential role in modulating cell survival, metabolic function, and stress response pathways.

Interpretation of in vitro concentration-response data for risk assessment and regulatory decision-making: Report from the 2022 IWGT quantitative analysis expert working group meeting

Quantitative risk assessments of chemicals are routinely performed using in vivo data from rodents; however, there is growing recognition that non-animal approaches can be human-relevant alternatives. There is an urgent need to build confidence in non-animal alternatives given the international support to reduce the use of animals in toxicity testing where possible. In order for scientists and risk assessors to prepare for this paradigm shift in toxicity assessment, standardization and consensus on in vitro testing strategies and data interpretation will need to be established. To address this issue, an Expert Working Group (EWG) of the 8th International Workshop on Genotoxicity Testing (IWGT) evaluated the utility of quantitative in vitro genotoxicity concentration-response data for risk assessment. The EWG first evaluated available in vitro methodologies and then examined the variability and maximal response of in vitro tests to estimate biologically relevant values for the critical effect sizes considered adverse or unacceptable. Next, the EWG reviewed the approaches and computational models employed to provide human-relevant dose context to in vitro data. Lastly, the EWG evaluated risk assessment applications for which in vitro data are ready for use and applications where further work is required. The EWG concluded that in vitro genotoxicity concentration-response data can be interpreted in a risk assessment context. However, prior to routine use in regulatory settings, further research will be required to address the remaining uncertainties and limitations.

A Pragmatic Framework for the Application of New Approach Methodologies in One Health Toxicological Risk Assessment

Globally, industries and regulatory authorities are faced with an urgent need to assess the potential adverse effects of chemicals more efficiently by embracing new approach methodologies (NAMs). NAMs include cell and tissue methods (in vitro), structure-based/toxicokinetic models (in silico), methods that assess toxicant interactions with biological macromolecules (in chemico), and alternative models. Increasing knowledge on chemical toxicokinetics (what the body does with chemicals) and toxicodynamics (what the chemicals do with the body) obtained from in silico and in vitro systems continues to provide opportunities for modernizing chemical risk assessments. However, directly leveraging in vitro and in silico data for derivation of human health-based reference values has not received regulatory acceptance due to uncertainties in extrapolating NAM results to human populations, including metabolism, complex biological pathways, multiple exposures, interindividual susceptibility and vulnerable populations. The objective of this article is to provide a standardized pragmatic framework that applies integrated approaches with a focus on quantitative in vitro to in vivo extrapolation (QIVIVE) to extrapolate in vitro cellular exposures to human equivalent doses from which human reference values can be derived. The proposed framework intends to systematically account for the complexities in extrapolation and data interpretation to support sound human health safety decisions in diverse industrial sectors (food systems, cosmetics, industrial chemicals, pharmaceuticals etc.). Case studies of chemical entities, using new and existing data, are presented to demonstrate the utility of the proposed framework while highlighting potential sources of human population bias and uncertainty, and the importance of Good Method and Reporting Practices.

Identifying xenobiotic metabolites with in silico prediction tools and LCMS suspect screening analysis

Understanding the metabolic fate of a xenobiotic substance can help inform its potential health risks and allow for the identification of signature metabolites associated with exposure. The need to characterize metabolites of poorly studied or novel substances has shifted exposure studies towards non-targeted analysis (NTA), which often aims to profile many compounds within a sample using high-resolution liquid-chromatography mass-spectrometry (LCMS). Here we evaluate the suitability of suspect screening analysis (SSA) liquid-chromatography mass-spectrometry to inform xenobiotic chemical metabolism. Given a lack of knowledge of true metabolites for most chemicals, predictive tools were used to generate potential metabolites as suspect screening lists to guide the identification of selected xenobiotic substances and their associated metabolites. Thirty-three substances were selected to represent a diverse array of pharmaceutical, agrochemical, and industrial chemicals from Environmental Protection Agency's ToxCast chemical library. The compounds were incubated in a metabolically-active in vitro assay using primary hepatocytes and the resulting supernatant and lysate fractions were analyzed with high-resolution LCMS. Metabolites were simulated for each compound structure using software and then combined to serve as the suspect screening list. The exact masses of the predicted metabolites were then used to select LCMS features for fragmentation via tandem mass spectrometry (MS/MS). Of the starting chemicals, 12 were measured in at least one sample in either positive or negative ion mode and a subset of these were used to develop the analysis workflow. We implemented a screening level workflow for background subtraction and the incorporation of time-varying kinetics into the identification of likely metabolites. We used haloperidol as a case study to perform an in-depth analysis, which resulted in identifying five known metabolites and five molecular features that represent potential novel metabolites, two of which were assigned discrete structures based on in silico predictions. This workflow was applied to five additional test chemicals, and 15 molecular features were selected as either reported metabolites, predicted metabolites, or potential metabolites without a structural assignment. This study demonstrates that in some-but not all-cases, suspect screening analysis methods provide a means to rapidly identify and characterize metabolites of xenobiotic chemicals.

A Physiologically Based Pharmacokinetic (PBPK) Modeling Framework for Mixtures of Dioxin-like Compounds

Humans are exposed to persistent organic pollutants, such as dioxin-like compounds (DLCs), as mixtures. Understanding and predicting the toxicokinetics and thus internal burden of major constituents of a DLC mixture is important for assessing their contributions to health risks. PBPK models, including dioxin models, traditionally focus on one or a small number of compounds; developing new or extending existing models for mixtures often requires tedious, error-prone coding work. This lack of efficiency to scale up for multi-compound exposures is a major technical barrier toward large-scale mixture PBPK simulations. Congeners in the DLC family, including 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), share similar albeit quantitatively different toxicokinetic and toxicodynamic properties. Taking advantage of these similarities, here we reported the development of a human PBPK modeling framework for DLC mixtures that can flexibly accommodate an arbitrary number of congeners. Adapted from existing TCDD models, our mixture model contains the blood and three diffusion-limited compartments-liver, fat, and rest of the body. Depending on the number of congeners in a mixture, varying-length vectors of ordinary differential equations (ODEs) are automatically generated to track the tissue concentrations of the congeners. Shared ODEs are used to account for common variables, including the aryl hydrocarbon receptor (AHR) and CYP1A2, to which the congeners compete for binding. Binary and multi-congener mixture simulations showed that the AHR-mediated cross-induction of CYP1A2 accelerates the sequestration and metabolism of DLC congeners, resulting in consistently lower tissue burdens than in single exposure, except for the liver. Using dietary intake data to simulate lifetime exposures to DLC mixtures, the model demonstrated that the relative contributions of individual congeners to blood or tissue toxic equivalency (TEQ) values are markedly different than those to intake TEQ. In summary, we developed a mixture PBPK modeling framework for DLCs that may be utilized upon further improvement as a quantitative tool to estimate tissue dosimetry and health risks of DLC mixtures.

Lights and Shadows on the Therapeutic Use of Antimicrobial Peptides

The emergence of antimicrobial-resistant infections is still a major concern for public health worldwide. The number of pathogenic microorganisms capable of resisting common therapeutic treatments are constantly increasing, highlighting the need of innovative and more effective drugs. This phenomenon is strictly connected to the rapid metabolism of microorganisms: due to the huge number of mutations that can occur in a relatively short time, a colony can “adapt” to the pharmacological treatment with the evolution of new resistant species. However, the shortage of available antimicrobial drugs in clinical use is also caused by the high costs involved in developing and marketing new drugs without an adequate guarantee of an economic return; therefore, the pharmaceutical companies have reduced their investments in this area. The use of antimicrobial peptides (AMPs) represents a promising strategy for the design of new therapeutic agents. AMPs act as immune defense mediators of the host organism and show a poor ability to induce antimicrobial resistance, coupled with other advantages such as a broad spectrum of activity, not excessive synthetic costs and low toxicity of both the peptide itself and its own metabolites. It is also important to underline that many antimicrobial peptides, due to their inclination to attack cell membranes, have additional biological activities, such as, for example, as anti-cancer drugs. Unfortunately, they usually undergo rapid degradation by proteolytic enzymes and are characterized by poor bioavailability, preventing their extensive clinical use and landing on the pharmaceutical market. This review is focused on the strength and weak points of antimicrobial peptides as therapeutic agents. We give an overview on the AMPs already employed in clinical practice, which are examples of successful strategies aimed at overcoming the main drawbacks of peptide-based drugs. The review deepens the most promising strategies to design modified antimicrobial peptides with higher proteolytic stability with the purpose of giving a comprehensive summary of the commonly employed approaches to evaluate and optimize the peptide potentialities.