Quantitative in vitro to in vivo extrapolation of tissues toxicity

Cytotoxicity and Thermal Characterization Assessment of Excipients for the Development of Innovative Lyophilized Formulations for Oncological Applications

Freeze-drying, also known as lyophilization, significantly improves the storage, stability, shelf life, and clinical translation of biopharmaceuticals. On the downside, this process faces complex challenges, i.e., the presence of freezing and drying stresses for the active compounds, the uniformity and consistency of the final products, and the efficiency and safety of the reconstituted lyophilized formulations. All these requirements can be addressed by adding specific excipients that can protect and stabilize the active ingredient during lyophilization, assisting in the formation of solid structures without interfering with the biological and/or pharmaceutical action of the reconstituted products. However, these excipients, generally considered safe and inert, could play an active role in the formulation interacting with the biological cellular machinery and promoting toxicity. Any side effects should be carefully identified and characterized to better tune any treatments in terms of concentrations and administration times. In this work, various concentrations in the range of 1 to 100 mg/mL of cellobiose, lactose, sucrose, trehalose, isoleucine, glycine, methionine, dextran, mannitol, and (2-hydroxypropyl)-β-cyclodextrin were evaluated in terms of their ability to create uniform and solid lyophilized structures. The freeze-dried products were then reconstituted in the appropriate cell culture media to assess their in vitro cytotoxicity on both a healthy cell line (B-lymphocytes) and their tumoral lymphoid counterpart (Daudi). Results showed that at 10 mg/mL, all the excipients demonstrated suitable lyophilized solid structures and high tolerability by both cell lines, while dextran was the only excipient well-tolerated also up to 100 mg/mL. An interesting result was shown for methionine, which even at 10 mg/mL, selectively affected the viability of the cancerous cell line only, opening future perspectives for antitumoral applications.

IVIVE: Facilitating the Use of In Vitro Toxicity Data in Risk Assessment and Decision Making

During the past few decades, the science of toxicology has been undergoing a transformation from observational to predictive science. New approach methodologies (NAMs), including in vitro assays, in silico models, read-across, and in vitro to in vivo extrapolation (IVIVE), are being developed to reduce, refine, or replace whole animal testing, encouraging the judicious use of time and resources. Some of these methods have advanced past the exploratory research stage and are beginning to gain acceptance for the risk assessment of chemicals. A review of the recent literature reveals a burst of IVIVE publications over the past decade. In this review, we propose operational definitions for IVIVE, present literature examples for several common toxicity endpoints, and highlight their implications in decision-making processes across various federal agencies, as well as international organizations, including those in the European Union (EU). The current challenges and future needs are also summarized for IVIVE. In addition to refining and reducing the number of animals in traditional toxicity testing protocols and being used for prioritizing chemical testing, the goal to use IVIVE to facilitate the replacement of animal models can be achieved through their continued evolution and development, including a strategic plan to qualify IVIVE methods for regulatory acceptance.

In Vitro and In Vivo Approaches for Screening the Potential of Anticancer Agents: A Review

BACKGROUND

Anticancer drug development is a tedious process, requiring several in vitro, in vivo, and clinical studies. In order to avoid chemical toxicity in animals during an experiment, it is necessary to envisage toxic doses of screened drugs in vivo at different concentrations. Several in vitro and in vivo studies have been reported to discover the management of cancer.

MATERIALS AND METHODS

This study focused on bringing together a wide range of in vivo and in vitro assay methods developed to evaluate each hallmark feature of cancer.

RESULT

This review provides detailed information on target-based and cell-based screening of new anticancer drugs in the molecular targeting period. This would help in inciting an alteration from the preclinical screening of pragmatic compound-orientated to target-orientated drug selection.

CONCLUSION

Selection methodologies for finding anticancer activity have importance for tumor- specific agents. In this study, advanced rationalization of the cell-based assay is explored along with broad applications of the cell-based methodologies considering other opportunities.

Application of physiologically based pharmacokinetic models to promote the development of veterinary drugs with high efficacy and safety

Physiologically based pharmacokinetic (PBPK) models have become important tools for the development of novel human drugs. Food-producing animals and pets comprise an important part of human life, and the development of veterinary drugs (VDs) has greatly impacted human health. Owing to increased affordability of and demand for drug development, VD manufacturing companies should have more PBPK models required to reduce drug production costs. So far, little attention has been paid on applying PBPK models for the development of VDs. This review begins with the development processes of VDs; then summarizes case studies of PBPK models in human or VD development; and analyzes the application, potential, and advantages of PBPK in VD development, including candidate screening, formulation optimization, food effects, target-species safety, and dosing optimization. Then, the challenges of applying the PBPK model to VD development are discussed. Finally, future opportunities of PBPK models in designing dosing regimens for intracellular pathogenic infections and for efficient oral absorption of VDs are further forecasted. This review will be relevant to readers who are interested in using a PBPK model to develop new VDs.

Assessment of long-term functional maintenance of primary human hepatocytes to predict drug-induced hepatoxicity in vitro

Hepatocytes are the main cell components of the liver and perform metabolic, detoxification, and endocrine functions. Functional hepatocytes are of great value in drug development, toxicity evaluation, and cell therapy for liver diseases. In recent years, an increasing number of in vitro models have been developed to screen drugs and test their toxicity. However, maintaining hepatocyte function in vitro for a long time is a serious challenge. Even freshly isolated liver cells cultured for a short time may lose function via spontaneous dedifferentiation. Thus, novel cell culture systems allowing extended hepatocyte maintenance and more predictive long-term in vitro studies are required. In this study, we developed a conditioned culture system composed of a small-molecule combination that can maintain hepatocyte morphology and functions over the long term. Two-month culture of primary human hepatocytes showed that the conditioned medium was able to stably preserve hepatic functions such as albumin and α-antitrypsin secretion, hepatic transport activity, urea synthesis, and ammonia elimination. Furthermore, this culture model can be used to assess drug-induced hepatotoxicity in vitro. In summary, our work suggests a feasible approach to maintain hepatocyte function in vitro and proposes a promising model for long-term toxicological studies and drug development.

Importance of in vitro conditions for modeling the in vivo dose in humans by in vitro-in vivo extrapolation (IVIVE)

In vitro studies are increasingly proposed to replace in vivo toxicity testing of substances. We set out to apply physiologically based pharmacokinetic (PBPK) modeling to predict the in vivo dose of amiodarone that leads to the same concentration-time profile in the supernatant and the cell lysate of cultured primary human hepatic cells (PHH). A PBPK human model was constructed based on the structure and tissue distribution of amiodarone in a rat model and using physiological human parameters. The predicted concentration-time profile in plasma was in agreement with human experimental data with the unbound fraction of amiodarone in plasma crucially affecting the goodness-of-fit. Using the validated kinetic model, we subsequently described the in vitro concentration-time data of amiodarone in PHH culture. However, this could be only appropriately modeled under conditions of zero protein binding and the very low clearance of the in vitro system in PHH culture. However, these represent unphysiological conditions and, thus, the main difference between the in vivo and the in vitro systems. Our results reveal that, for meaningful quantitative extrapolation from in vitro to in vivo conditions in PBPK studies, it is essential to avoid non-intended differences between these conditions. Specifically, clearance and protein binding, as demonstrated in our analysis of amiodarone modeling, are important parameters to consider.

Identification and quantification of blood-brain barrier transporters in isolated rat brain microvessels

The blood-brain barrier (BBB) maintains brain homeostasis by tightly regulating the exchange of molecules with systemic circulation. It consists primarily of microvascular endothelial cells surrounded by astrocytic endfeet, pericytes, and microglia. Understanding the make-up of transporters in rat BBB is essential to the translation of pharmacological and toxicological observations into humans. In this study, experimental workflows are presented in which the optimization of (a) isolation of rat brain microvessels (b) enrichment of endothelial cells, and (c) extraction and digestion of proteins were evaluated, followed by identification and quantification of BBB proteins. Optimization of microvessel isolation was indicated by 15-fold enrichment of endothelial cell marker Glut1 mRNA, whereas markers for other cell types were not enriched. Filter-aided sample preparation was shown to be superior to in-solution sample preparation (10251 peptides vs. 7533 peptides). Label-free proteomics was used to identify nearly 2000 proteins and quantify 1276 proteins in isolated microvessels. A combination of targeted and global proteomics was adopted to measure protein abundance of 6 ATP-binding cassette and 27 solute carrier transporters. Data analysis using proprietary Progenesis and open access MaxQuant software showed overall agreement; however, Abcb9 and Slc22a8 were quantified only by MaxQuant, whereas Abcc9 and Abcd3 were quantified only by Progenesis. Agreement between targeted and untargeted quantification was demonstrated for Abcb1 (19.7 ± 1.4 vs. 17.8 ± 2.3) and Abcc4 (2.2 ± 0.7 vs. 2.1 ± 0.4), respectively. Rigorous quantification of BBB proteins, as reported in this study, should assist with translational modeling efforts involving brain disposition of xenobiotics.

Early life exposure to air pollution particulate matter (PM) as risk factor for attention deficit/hyperactivity disorder (ADHD): Need for novel strategies for mechanisms and causalities

Epidemiological studies have demonstrated that air pollution particulate matter (PM) and adsorbed toxicants (organic compounds and trace metals) may affect child development already in utero. Recent studies have also indicated that PM may be a risk factor for neurodevelopmental disorders (NDDs). A pattern of increasing prevalence of attention deficit/hyperactivity disorder (ADHD) has been suggested to partly be linked to environmental pollutants exposure, including PM. Epidemiological studies suggest associations between pre- or postnatal exposure to air pollution components and ADHD symptoms. However, many studies are cross-sectional without possibility to reveal causality. Cohort studies are often small with poor exposure characterization, and confounded by traffic noise and socioeconomic factors, possibly overestimating the study associations. Furthermore, the mechanistic knowledge how exposure to PM during early brain development may contribute to increased risk of ADHD symptoms or cognitive deficits is limited. The closure of this knowledge gap requires the combined use of well-designed longitudinal cohort studies, supported by mechanistic in vitro studies. As ADHD has profound consequences for the children affected and their families, the identification of preventable risk factors such as air pollution exposure should be of high priority.

Automated workflows for modelling chemical fate, kinetics and toxicity

Automation is universal in today's society, from operating equipment such as machinery, in factory processes, to self-parking automobile systems. While these examples show the efficiency and effectiveness of automated mechanical processes, automated procedures that support the chemical risk assessment process are still in their infancy. Future human safety assessments will rely increasingly on the use of automated models, such as physiologically based kinetic (PBK) and dynamic models and the virtual cell based assay (VCBA). These biologically-based models will be coupled with chemistry-based prediction models that also automate the generation of key input parameters such as physicochemical properties. The development of automated software tools is an important step in harmonising and expediting the chemical safety assessment process. In this study, we illustrate how the KNIME Analytics Platform can be used to provide a user-friendly graphical interface for these biokinetic models, such as PBK models and VCBA, which simulates the fate of chemicals in vivo within the body and in vitro test systems respectively.

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The VCBA is a mathematical model that simulates in vitro fate of chemicals and the corresponding cellular effect.

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The VCBA has been implemented in an open access web-based KNIME platform for ease of use.

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KNIME Analytics Platform can be used to provide a user-friendly graphical interface for biokinetic models.

The virtual cell based assay: Current status and future perspectives

In order to replace the use of animals in toxicity testing, there is a need to predict in vivo toxic doses from concentrations that cause toxicological effects in relevant in vitro systems. The Virtual Cell Based Assay (VCBA) estimates time-dependent concentration of a test chemical in the cell and cell culture for a given in vitro system. The concentrations in the different compartments of the cell and test system are derived from ordinary differential equations, physicochemical parameters of the test chemical and properties of the cell line. The VCBA has been developed for a range of cell lines including BALB/c 3T3 cells, HepG2, HepaRG, lung A459 cells, and cardiomyocytes. The model can be used to design and refine in vitro experiments and extrapolate in vitro effective concentrations to in vivo doses that can be applied in risk assessment. In this paper, we first discuss potential applications of the VCBA: i) design of in vitro High Throughput Screening (HTS) experiments; ii) hazard identification (based on acute systemic toxicity); and iii) risk assessment. Further extension of the VCBA is discussed in the second part, exploring potential application to i) manufactured nanomaterials, ii) additional cell lines and endpoints, and considering iii) other opportunities.

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VCBA as an alternative approach can be applied in the domain of nanotoxicology.

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VCBA can support better testing strategies in acute toxicity.

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Refinement of the VCBA taking into account biological oscillators could improve toxicity prediction.

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Extensions of the VCBA can capture effects related to additional subcellular compartments.

Key to Opening Kidney for In Vitro-In Vivo Extrapolation Entrance in Health and Disease: Part II: Mechanistic Models and In Vitro-In Vivo Extrapolation

It is envisaged that application of mechanistic models will improve prediction of changes in renal disposition due to drug-drug interactions, genetic polymorphism in enzymes and transporters and/or renal impairment. However, developing and validating mechanistic kidney models is challenging due to the number of processes that may occur (filtration, secretion, reabsorption and metabolism) in this complex organ. Prediction of human renal drug disposition from preclinical species may be hampered by species differences in the expression and activity of drug metabolising enzymes and transporters. A proposed solution is bottom-up prediction of pharmacokinetic parameters based on in vitro-in vivo extrapolation (IVIVE), mediated by recent advances in in vitro experimental techniques and application of relevant scaling factors. This review is a follow-up to the Part I of the report from the 2015 AAPS Annual Meeting and Exhibition (Orlando, FL; 25th-29th October 2015) which focuses on IVIVE and mechanistic prediction of renal drug disposition. It describes the various mechanistic kidney models that may be used to investigate renal drug disposition. Particular attention is given to efforts that have attempted to incorporate elements of IVIVE. In addition, the use of mechanistic models in prediction of renal drug-drug interactions and potential for application in determining suitable adjustment of dose in kidney disease are discussed. The need for suitable clinical pharmacokinetics data for the purposes of delineating mechanistic aspects of kidney models in various scenarios is highlighted.

Multiscale modelling approaches for assessing cosmetic ingredients safety

The European Union's ban on animal testing for cosmetic ingredients and products has generated a strong momentum for the development of in silico and in vitro alternative methods. One of the focus of the COSMOS project was ab initio prediction of kinetics and toxic effects through multiscale pharmacokinetic modeling and in vitro data integration. In our experience, mathematical or computer modeling and in vitro experiments are complementary. We present here a summary of the main models and results obtained within the framework of the project on these topics. A first section presents our work at the organelle and cellular level. We then go toward modeling cell levels effects (monitored continuously), multiscale physiologically based pharmacokinetic and effect models, and route to route extrapolation. We follow with a short presentation of the automated KNIME workflows developed for dissemination and easy use of the models. We end with a discussion of two challenges to the field: our limited ability to deal with massive data and complex computations.

In Silico Modeling for the Prediction of Dose and Pathway-Related Adverse Effects in Humans From In Vitro Repeated-Dose Studies

Long-term repeated-dose toxicity is mainly assessed in animals despite poor concordance of animal data with human toxicity. Nowadays advanced human in vitro systems, eg, metabolically competent HepaRG cells, are used for toxicity screening. Extrapolation of in vitro toxicity to in vivo effects is possible by reverse dosimetry using pharmacokinetic modeling. We assessed long-term repeated-dose toxicity of bosentan and valproic acid (VPA) in HepaRG cells under serum-free conditions. Upon 28-day exposure, the EC50 values for bosentan and VPA decreased by 21- and 33-fold, respectively. Using EC(10) as lowest threshold of toxicity in vitro, we estimated the oral equivalent doses for both test compounds using a simplified pharmacokinetic model for the extrapolation of in vitro toxicity to in vivo effect. The model predicts that bosentan is safe at the considered dose under the assumed conditions upon 4 weeks exposure. For VPA, hepatotoxicity is predicted for 4% and 47% of the virtual population at the maximum recommended daily dose after 3 and 4 weeks of exposure, respectively. We also investigated the changes in the central carbon metabolism of HepaRG cells exposed to orally bioavailable concentrations of both drugs. These concentrations are below the 28-day EC(10) and induce significant changes especially in glucose metabolism and urea production. These metabolic changes may have a pronounced impact in susceptible patients such as those with compromised liver function and urea cycle deficiency leading to idiosyncratic toxicity. We show that the combination of modeling based on in vitro repeated-dose data and metabolic changes allows the prediction of human relevant in vivo toxicity with mechanistic insights.

Biokinetics in repeated-dosing in vitro drug toxicity studies

The aim of the EU FP7 Predict-IV project was to improve the predictivity of in vitro assays for unwanted effects of drugs after repeated dosing. The project assessed the added benefit of integrating long-lived in vitro organotypic cell systems with 'omics' technologies and in silico modelling, including systems biology and pharmacokinetic assessments. RPTEC/TERT1 kidney cells, primary rat and human hepatocytes, HepaRG liver cells and 2D and 3D primary brain cultures were dosed daily or every other day for 14 days to a selection of drugs varying in their mechanism of pharmacological action. Since concentration-effect relationships not only depend on the activity of the drug or the sensitivity of the target, but also on the distribution of compounds in the in vitro system, the concentration of a selection of drugs in cells, microtitre plate plastic and medium was measured over time. Results, reviewed in this paper, indicate that lipophilic drugs bind significantly to plastic labware. A few drugs, including less lipophilic drugs, bind to cell-attachment matrices. Chemicals that reach high concentrations in cells, including cyclosporin A and amiodarone, significantly accumulate over time after repeated dosing, partly explaining their increased toxicity after repeated dosing, compared to a single dose.