Thoroughly Calibrated Modular Agent-Based Model of the Human Cardiovascular and Renal Systems for Blood Pressure Regulation in Health and Disease

Here we present a modular agent-based mathematical model of the human cardiovascular and renal systems. It integrates the previous models primarily developed by A. C. Guyton, F. Karaaslan, K. M. Hallow, and Y. V. Solodyannikov. We performed the model calibration to find an equilibrium state within the normal vital sign ranges for a healthy adult. We verified the model's abilities to reproduce equilibrium states with abnormal physiological values related to different combinations of cardiovascular diseases (such as systemic hypertension, chronic heart failure, pulmonary hypertension, etc.). For the model creation and validation, we involved over 200 scientific studies covering known models of the human cardiovascular and renal functions, biosimulation platforms, and clinical measurements of physiological quantities in normal and pathological conditions. We compiled detailed documentation describing all equations, parameters and variables of the model with justification of all formulas and values. The model is implemented in BioUML and available in the web-version of the software.

The clonal structure and dynamics of the human T cell response to an organic chemical hapten

Diphenylcyclopropenone (DPC) is an organic chemical hapten which induces allergic contact dermatitis and is used in the treatment of warts, melanoma, and alopecia areata. This therapeutic setting therefore provided an opportunity to study T cell receptor (TCR) repertoire changes in response to hapten sensitization in humans. Repeated exposure to DPC induced highly dynamic transient expansions of a polyclonal diverse T cell population. The number of TCRs expanded early after sensitization varies between individuals and predicts the magnitude of the allergic reaction. The expanded TCRs show preferential TCR V and J gene usage and consist of clusters of TCRs with similar sequences, two characteristic features of antigen-driven responses. The expanded TCRs share subtle sequence motifs that can be captured using a dynamic Bayesian network. These observations suggest the response to DPC is mediated by a polyclonal population of T cells recognizing a small number of dominant antigens.

Determination of Protein Haptenation by Chemical Sensitizers Within the Complexity of the Human Skin Proteome

Skin sensitization associated with the development of allergic contact dermatitis occurs via a number of specific key events at the cellular level. The molecular initiating event (MIE), the first in the sequence of these events, occurs after exposure of the skin to an electrophilic chemical, causing the irreversible haptenation of proteins within skin. Characterization of this MIE is a key step in elucidating the skin sensitization adverse outcome pathway and is essential to providing parameters for mathematical models to predict the capacity of a chemical to cause sensitization. As a first step to addressing this challenge, we have exposed complex protein lysates from a keratinocyte cell line and human skin tissue with a range of well characterized sensitizers, including dinitrochlorobenzene, 5-chloro-2-methylisothiazol-3-one, cinnamaldehyde, and the non (or weak) sensitizer 6-methyl coumarin. Using a novel stable isotope labeling approach combined with ion mobility-assisted data independent mass spectrometry (HDMSE), we have characterized the haptenome for these sensitizers. Although a significant proportion of highly abundant proteins were haptenated, we also observed the haptenation of low abundant proteins by all 3 of the chemical sensitizers tested, indicating that within a complex protein background, protein abundance is not the sole determinant driving haptenation, highlighting a relationship to tertiary protein structure and the amino acid specificity of these chemical sensitizers and sensitizer potency.

A model qualification method for mechanistic physiological QSP models to support model-informed drug development

Mechanistic physiological modeling is a scientific method that combines available data with scientific knowledge and engineering approaches to facilitate better understanding of biological systems, improve decision‐making, reduce risk, and increase efficiency in drug discovery and development. It is a type of quantitative systems pharmacology (QSP) approach that places drug‐specific properties in the context of disease biology. This tutorial provides a broadly applicable model qualification method (MQM) to ensure that mechanistic physiological models are fit for their intended purposes.

Bayesian integrated testing strategy (ITS) for skin sensitization potency assessment: a decision support system for quantitative weight of evidence and adaptive testing strategy

The presented Bayesian network Integrated Testing Strategy (ITS-3) for skin sensitization potency assessment is a decision support system for a risk assessor that provides quantitative weight of evidence, leading to a mechanistically interpretable potency hypothesis, and formulates adaptive testing strategy for a chemical. The system was constructed with an aim to improve precision and accuracy for predicting LLNA potency beyond ITS-2 (Jaworska et al., J Appl Toxicol 33(11):1353-1364, 2013) by improving representation of chemistry and biology. Among novel elements are corrections for bioavailability both in vivo and in vitro as well as consideration of the individual assays' applicability domains in the prediction process. In ITS-3 structure, three validated alternative assays, DPRA, KeratinoSens and h-CLAT, represent first three key events of the adverse outcome pathway for skin sensitization. The skin sensitization potency prediction is provided as a probability distribution over four potency classes. The probability distribution is converted to Bayes factors to: 1) remove prediction bias introduced by the training set potency distribution and 2) express uncertainty in a quantitative manner, allowing transparent and consistent criteria to accept a prediction. The novel ITS-3 database includes 207 chemicals with a full set of in vivo and in vitro data. The accuracy for predicting LLNA outcomes on the external test set (n = 60) was as follows: hazard (two classes)-100 %, GHS potency classification (three classes)-96 %, potency (four classes)-89 %. This work demonstrates that skin sensitization potency prediction based on data from three key events, and often less, is possible, reliable over broad chemical classes and ready for practical applications.

Systems toxicology: from basic research to risk assessment

Systems Toxicology is the integration of classical toxicology with quantitative analysis of large networks of molecular and functional changes occurring across multiple levels of biological organization. Society demands increasingly close scrutiny of the potential health risks associated with exposure to chemicals present in our everyday life, leading to an increasing need for more predictive and accurate risk-assessment approaches. Developing such approaches requires a detailed mechanistic understanding of the ways in which xenobiotic substances perturb biological systems and lead to adverse outcomes. Thus, Systems Toxicology approaches offer modern strategies for gaining such mechanistic knowledge by combining advanced analytical and computational tools. Furthermore, Systems Toxicology is a means for the identification and application of biomarkers for improved safety assessments. In Systems Toxicology, quantitative systems-wide molecular changes in the context of an exposure are measured, and a causal chain of molecular events linking exposures with adverse outcomes (i.e., functional and apical end points) is deciphered. Mathematical models are then built to describe these processes in a quantitative manner. The integrated data analysis leads to the identification of how biological networks are perturbed by the exposure and enables the development of predictive mathematical models of toxicological processes. This perspective integrates current knowledge regarding bioanalytical approaches, computational analysis, and the potential for improved risk assessment.

Applying the skin sensitisation adverse outcome pathway (AOP) to quantitative risk assessment

As documented in the recent OECD report 'the adverse outcome pathway for skin sensitisation initiated by covalent binding to proteins' (OECD, 2012), the chemical and biological events driving the induction of human skin sensitisation have been investigated for many years and are now well understood. Several non-animal test methods have been developed to predict sensitiser potential by measuring the impact of chemical sensitisers on these key events (Adler et al., 2011; Maxwell et al., 2011); however our ability to use these non-animal datasets for risk assessment decision-making (i.e. to establish a safe level of human exposure for a sensitising chemical) remains limited and a more mechanistic approach to data integration is required to address this challenge. Informed by our previous efforts to model the induction of skin sensitisation (Maxwell and MacKay, 2008) we are now developing two mathematical models ('total haptenated protein' model and 'CD8(+) T cell response' model) that will be linked to provide predictions of the human CD8(+) T cell response for a defined skin exposure to a sensitising chemical. Mathematical model development is underpinned by focussed clinical or human-relevant research activities designed to inform/challenge model predictions whilst also increasing our fundamental understanding of human skin sensitisation. With this approach, we aim to quantify the relationship between the dose of sensitiser applied to the skin and the extent of the hapten-specific T cell response that would result. Furthermore, by benchmarking our mathematical model predictions against clinical datasets (e.g. human diagnostic patch test data), instead of animal test data, we propose that this approach could represent a new paradigm for mechanistic toxicology.

Assuring consumer safety without animals: Applications for tissue engineering

Humans are exposed to a variety of chemicals in their everyday lives through interactions with the environment and through the use of consumer products. It is a basic requirement that these products are tested to assure they are safe under normal and reasonably foreseeable conditions of use. Within the European Union, the majority of tests used for generating toxicological data rely on animals. However recent changes in legislation (e.g., 7(th) amendment of the Cosmetics Directive and REACH) are driving researchers to develop and adopt non-animal alternative methods with which to assure human safety. Great strides have been made to this effect, but what other opportunities/technologies exist that could expedite this? Tissue engineering has increasing scope to contribute to replacing animals with scientifically robust alternatives in basic research and safety testing, but is this application of the technology being fully exploited? This review highlights how the consumer products industry is applying tissue engineering to ensure chemicals are safe for human use without using animals, and identifies areas for future development and application of the technology.

Non-animal test methods for predicting skin sensitization potentials

Contact allergies are complex diseases, and it is estimated that 15-20 % of the general population suffers from contact allergy, with increasing prevalence. Evaluation of the sensitization potential of a substance is usually carried out in animal models. Nowadays, there is much interest in reducing and ultimately replacing current animal tests. Furthermore, as of 2013, the EU has posed a ban on animal testing of cosmetic ingredients that includes skin sensitization. Therefore, predictive and robust in vitro tests are urgently needed. In order to establish alternatives to animal testing, the in vitro tests must mimic the very complex interactions between the sensitizing chemical and the different parts of the immune system. This review article summarizes recent efforts to develop in vitro tests for predicting skin sensitizers. Cell-based assays, in chemico methods and, to a lesser extent, in silico methods are presented together with a discussion of their current status. With considerable progress having been achieved during the last years, the rationale today is that data from different non-animal test methods will have to be combined in order to obtain reliable hazard and potency information on potential skin sensitizers.

Chemical sensitization and allergotoxicology

Chemical sensitization remains an important environmental and occupational health issue. A wide range of substances have been shown to possess the ability to induce skin sensitization or respiratory sensitization. As a consequence, there is a need to have appropriate methods to identify sensitizing agents. Although a considerable investment has been made in exploring opportunities to develop methods for hazard identification and characterization, there are, as yet, no validated nonanimal methods available. A state of the art of the different in vitro approaches to identify contact and respiratory capacity of chemicals is covered in this chapter.

Alternative (non-animal) methods for cosmetics testing: current status and future prospects-2010

The 7th amendment to the EU Cosmetics Directive prohibits to put animal-tested cosmetics on the market in Europe after 2013. In that context, the European Commission invited stakeholder bodies (industry, non-governmental organisations, EU Member States, and the Commission's Scientific Committee on Consumer Safety) to identify scientific experts in five toxicological areas, i.e. toxicokinetics, repeated dose toxicity, carcinogenicity, skin sensitisation, and reproductive toxicity for which the Directive foresees that the 2013 deadline could be further extended in case alternative and validated methods would not be available in time. The selected experts were asked to analyse the status and prospects of alternative methods and to provide a scientifically sound estimate of the time necessary to achieve full replacement of animal testing. In summary, the experts confirmed that it will take at least another 7-9 years for the replacement of the current in vivo animal tests used for the safety assessment of cosmetic ingredients for skin sensitisation. However, the experts were also of the opinion that alternative methods may be able to give hazard information, i.e. to differentiate between sensitisers and non-sensitisers, ahead of 2017. This would, however, not provide the complete picture of what is a safe exposure because the relative potency of a sensitiser would not be known. For toxicokinetics, the timeframe was 5-7 years to develop the models still lacking to predict lung absorption and renal/biliary excretion, and even longer to integrate the methods to fully replace the animal toxicokinetic models. For the systemic toxicological endpoints of repeated dose toxicity, carcinogenicity and reproductive toxicity, the time horizon for full replacement could not be estimated.