(54c) Integra 2.0: Bridging the Gap from Global-Scale Contamination to Tissue-Specific Dose Assessment, Integration of a Computational Systems Biology Approach.

The assessment of aggregate exposure is a complex procedure that demands comprehensive data at every stage of the methodological pipeline. Addressing these requirements is the core focus of the INTEGRA platform (Sarigiannis et al., 2014; Sarigiannis et al., 2016) which encapsulates the life cycle of a compound within a modeling framework, consolidating all available information essential for assessing the source-to-dose continuum.

INTEGRA is an online integrative computational software that effectively navigates the calculation route from environmental release to internal dose, considering time-dependent processes and incorporating a Markov chain Monte Carlo (MCMC) probabilistic analysis framework. With this abstract, we are pleased to introduce the INTEGRA 2.0 platform, featuring significant enhancements. The updated version which is to be released in the upcoming days includes a detailed level four multimedia model, models for microenvironments assessment, an updated and more comprehensive version of the PBPK/TK model, integration with the Next Generation Systems Biology models that will be linked to toxicokinetic models by incorporating dose-response curves, and advanced 3D QSARs models to address data gaps.

The multimedia framework within INTEGRA is a sophisticated design that comprehensively considers a wide array of interactions occurring at significant distances, profoundly influencing the fate and transport of environmental and industrial chemicals. INTEGRA aligns itself with the rigorous guidelines set forth by the European Chemicals Agency ECHA (2012), which lays the foundation for a methodological pipeline ensuring the safety assessment of chemicals. What sets INTEGRA apart is its versatility, operating across various spatial scales, spanning from local to regional, continental, and even global domains. It adeptly manages the intricate exchange of chemicals across multiple environmental media, encompassing air, soil, water, sediment, and their subsequent transfer into food items such as crops, meat, milk, and fish. In the updated version, we've elevated the INTEGRA multimedia model to a level four by incorporating considerations for the time required for a chemical to circulate within environmental components. This enhancement yields several benefits, including heightened precision, advanced multiscale modeling capabilities, detailed cross-media mass transfer analysis, increased customization and predictability, and improved integration with other models through real-time monitoring. These improvements collectively contribute to the platform's enhanced capabilities for comprehensive environmental and human health assessments. The framework presented considers emissions, advection, diffusion, and degradation, principles as well. It is worth mentioning that a variety of plant tissues have been included in the model as well, increasing even more the complexity of the mechanistic model as well as its accuracy and precision.

The modeling of indoor microenvironments and the comprehensive assessment of individual exposure in close proximity, often referred to as near-field exposure, have been significantly enhanced through the improvement of the two-zone model by Sarigiannis et al. (2012) that was used. This innovative model offers a comprehensive understanding of indoor microenvironments by accounting for the partitioning of substances among gaseous, particulate, and settled dust phases (Sarigiannis et al., 2012). The key strength of this exposure model lies in its holistic approach, considering all potential means and routes of exposure. Moreover, it factors in a multitude of variables that can influence exposure levels, such as age and gender, by incorporating activity-based inhalation rates, dietary patterns, food item intake rates, the quantity of soil and dust ingested, and children's hand-to-mouth behavior. This approach ensures a more accurate and nuanced evaluation of exposure, reflecting the complex interplay of environmental and behavioral factors on individual health risks.

The PBPK model has undergone significant expansion, featuring additional compartments such as the intestine, spleen, feces, hair, and a generic blood-brain barrier mechanism with six sub-compartments including red blood cells, central plasma, cells, cerebrospinal fluid, intracellular, and extracellular fluid. This expansion has necessitated the update of our dynamic mass balance equations. Importantly, all these included organs are now equipped with specific metabolism mechanisms tailored to individual chemicals. Furthermore, a comprehensive system of equations has been developed to account for age-related metabolism alterations, adding a layer of detail and precision to the model. In addition, the generic PBPK model is not only geared with a Michaelis – Menten approach but also with the Brigs-Haldane equation.

In the updated kinetic model, the direction of metabolism has evolved from a linear pathway with three metabolites to a multi-dimensional framework with an infinite number of metabolites. Users now have the flexibility to either select from the pre-existing toxicokinetic models with predefined metabolite compositions or design their custom metabolism pathways, with the option to incorporate an infinite number of branches as needed. The source code is implemented in R computing environment, enabling the use of text processing techniques to generate an infinite set of differential mass balance equations, which can be seamlessly integrated with the parent compound. Furthermore, the model introduces a mechanism tailored for particularly lipophilic chemicals, which allows them to penetrate cell membranes, and includes protein binding mechanisms to account for a broader spectrum of chemical behaviors and interactions within biological systems.

For the parameterization of pharmacokinetic models, high-precision 3D QSARs (Quantitative Structure-Activity Relationships) have been developed using deep learning architectures such as TensorFlow and Keras. These models encompass numerous parameters, including Blood: Tissue partition coefficients, enzyme kinetics, plasma protein fraction bound, and more. These models are made accessible to the user, offering an alternative when data necessary for running the PBPK model is not readily available. As a result, to execute only the pharmacokinetic model in Tier 1, users need the chemical's structural information (InChI identifier or SMILES) and details about the quantity of chemical in the three exposure routes. This approach ensures flexibility and precision in pharmacokinetic modeling, even in cases where comprehensive data may be limited.

To apply this model at the molecular level, the integration of Next Generation Systems Biology (NGSB) models, as presented in the work by Karakoltzidis et al. (2023), has been seamlessly incorporated into the INTEGRA methodological pipeline. These NGSB models represent extensive mathematical models consisting of hundreds of equations that intricately describe the functioning of biological systems in depth and precision. The successful connection of PBPK outputs with NGSB models includes the integration of chemical-specific dose-response curves for multiple biomarkers (genes, enzymes, proteins, endogenous metabolites), ensuring a comprehensive approach. The collection of dose-response curves in the INTEGRA database is facilitated by employing Natural Language Processing (NLP) and token classification techniques. These curves help establish links between specific biomarkers and adverse outcomes, allowing for tailored assessments based on available data and user preferences. The utility of INTEGRA extends across a multitude of applications in industry, not only at the risk assessment level but also within the realm of toxicology. It is a valuable tool for evaluating occupational exposure and assessing the potential consequences of accidents, providing a versatile and comprehensive platform for various industrial risk assessment needs.

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Sarigiannis, D., Karakitsios, S., Antonakopoulou, M., & Gotti, A. (2012). Exposure analysis of accidental release of mercury from compact fluorescent lamps (CFLs). Science of the Total Environment, 435–436(0), 306-315. https://doi.org/10.1016/j.scitotenv.2012.07.026

Sarigiannis, D., Karaktitsios, S., Gotti, A., Loizou, G., Cherrie, J., Smolders, R., De Brouwere, K., Galea, K., Jones, K., Handakas, E., Papadaki, K., & Sleeuwenhoek, A. (2014). Integra: From global scale contamination to tissue dose. Proceedings - 7th International Congress on Environmental Modelling and Software: Bold Visions for Environmental Modeling, iEMSs,

Sarigiannis, D. A., Karakitsios, S. P., Handakas, E., Simou, K., Solomou, E., & Gotti, A. (2016). Integrated exposure and risk characterization of bisphenol-A in Europe. Food and Chemical Toxicology, 98, 134-147. https://doi.org/10.1016/j.fct.2016.10.017