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Translational quantitative systems toxicology to improve the understanding of the safety of medicines - Sofia: 116030

Periodic Reporting for period 3 - TransQST (Translational quantitative systems toxicology to improve the understanding of the safety of medicines - Sofia: 116030)

Reporting period: 2019-01-01 to 2019-12-31

The TransQST project gathers existing data and will generate new data under the project goals to support the development of tools that should make it easier to assess the safety profile of drug candidates before undergoing clinical testing. This will be achieved by an increased understanding of when results in nonclinical testing can be reliably extrapolated to humans, and by developing models to predict exposure-based biological responses in human tissues, which is an important element of safety assessment for new drug candidates. Liver, kidney, cardiovascular and gastrointestinal-immune systems are common target organs when safety signals are encountered during clinical testing.

The philosophy underlying TransQST is that improved translation from nonclinical to human safety during clinical trials can be achieved with novel Quantitative Systems Toxicology models.

To achieve this ambitious goal, the TransQST partnership will focus on liver, kidney, cardiovascular and gastrointestinal-immune systems, common target organs for drug-induced injury to:

• Build on existing physiologically-based pharmacokinetic/pharmacodynamic (PB-PK/PD) models to define systemic as well as specific organ/cell exposure to drugs and metabolites in a holistic fashion.
• Develop SYSTEMS models for drug-induced organ damage across the four target organs.
• Integrate PB-PK/PD models and output from SYSTEMS models into quantitative systems toxicology models.
• Test the models using selected compounds with nonclinical and human data.
• Form a unique public-private partnership that leverages industry data and practical experience with public expertise in mechanistic work as well as modelling across scales of complexity.
Overall, the project is on track and most of the deliverables and milestones have been submitted as scheduled. The scientific strategy has been led by the Executive Committee with continuous support of the Steering Committee members and the Scientific Leadership Team. The consortium has actively promoted the project, as shown by our internal and external communication and dissemination track. TransQST counts with 18 peer-reviewed publications, and with a high number of oral and poster presentations given at first line scientific events, showing results stemming from the project activities.

In terms of science, TransQST has finished the third year with several achievements that will facilitate tackling the overall project goals. Some examples of our achievements are as follows:

• Development of TransQST Data Management Platform
- Second major release of data management platform
- KNIME data integration workflows upgrade
- BioModels parameter search enhancements
- Extended curation of Black Box Warnings
- Creation of a standardized nomenclature and ontology for histopathology
- Internal data collaboration

• Development of several bioinformatic tools tailored to the toxicology area that have been described in detail in previous reports, and that are constantly being updated to address users’ needs and the needs of the project:
- CARNIVAL is a network contextualization tool which identifies subnetworks of upstream regulatory signaling networks based on downstream gene expression data and has been developed within the
TransQST Consortium in collaboration with the H2020 Symbiosys ITN Training Network. The tool is available as an open source tool to the whole scientific community at
https://github.com/saezlab/CARNIVAL.
- TXG-MAPr tool was developed to visualize and analyse gene expression data using the weight gene co-expression analysis (WGCNA) approach. The model and tool were built upon the TG-GATEs
dataset, a large-scale toxicogenomics database which contains data up to
160 compounds at 3 dose levels and 3-8 time points tested in human primary hepatocytes, rat in vivo liver and kidney. The tool has been specifically developed by the TransQST consortium in
collaboration with the IMI projects EUToxRisk and eTRANSAFE and is available for the use of the consortia members at https://txg-mapr.eu.
- OmniPath is a comprehensive collection of molecular biology prior knowledge from 103 databases, with focus on literature-curated human and rodent signalling pathways. It has been updated and
improved by the TransQST consortium and is publicly available at: http://omnipathdb.org/
- iPath is a modelling approach aimed at identifying cellular pathways involved in drug toxicity. iPath can leverage information from diverse omics datasets, namely protein interaction networks,
toxicogenomics data, gene and protein expression data, genotype-phenotype associations, and chemical biology information. iPath has been specifically developed by the TransQST consortium in
collaboration with the eTRANSAFE project and it is publicly available at http://sbi.imim.es/data/ipath.tgz & http://sbi.imim.es/data/ipath.zip
- DisGeNET is a knowledge management platform that contains a comprehensive collection of genes and variants associated with human diseases and phenotypes, including drug adverse events.
DisGeNET is an Elixir-Recommended Interoperability Resource which has been updated and improved by the TransQST consortium and is publicly available at https://www.disgenet.org/

• Development of different mechanistic, multi-scale models in the four organ work packages, that describe specific toxicity mechanisms relevant for each organ: liver, kidney, heart and gastro-intestinal system.
The TransQST actions aim to generate significant impact in different dimensions by a deep understanding of the physiological, pharmacological and toxicological relevance of data and models for predicting clinical Adverse Drug Reactions (ADRs).

During the project’s lifetime, participants are working toward improved methods to visualise and analyse large and complex datasets covering different types of available information (ie. drug metabolism, transcriptomics, proteomics, metabolomics, toxicology, pathological phenotype, biomarkers) to aid decision-making on drug safety.

In this third year of the TransQST Consortium, different mechanistic, multi-scale models are being deployed in the organ work packages that describe specific toxicity mechanisms relevant for each organ.
These models cover different scales of biological organization and integrate different modelling approaches. In particular, the integration of PBPK (physiologically-based pharmacokinetic) models with QST (quantitative systems toxicology) models, such as those for cardiac cell injury in WP7, GI (gastrointestinal) epithelium in WP8 and kidney cell injury in WP6, provides predictions of organ injury and recovery over time. These predictions are instrumental to support decision‐making, trial optimization and dose schedule guidance in early stages of drug development. Pending the validation of drug-induced liver injury models in WP5, it is expected that such models can be used to supplement regulatory submissions to provide additional evidence of predicted human safety response.
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