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

Periodic Reporting for period 5 - TransQST (Translational quantitative systems toxicology to improve the understanding of the safety of medicines - Sofia: 116030)

Período documentado: 2021-01-01 hasta 2022-08-31

The aim of TransQST project is to gather existing data and generate new data under the project goals to support the development of tools for the assessment of drug candidates´ safety profile before undergoing clinical testing. These goals have been 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.

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 has focused on liver, kidney, cardiovascular and gastrointestinal-immune systems as 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.
In the 68 months of project duration, TransQST project has worked towards better drug assessment and safety. To progress drug safety predictions in liver, kidney, heart and gastro-intestinal immune system, the consortium has both developed new TransQST models and enhanced pre-existing models aimed at assessing different organ toxicities. Among these we can find novel systems models, using ordinary differential equation (ODE) and agent-based (ABM) approaches, coupled with more established modelling approaches such as physiologically-based pharmacokinetic (PBPK) models. Project partners have also developed and enhanced a broad panel of tools used to identify and quantify toxic mechanisms, and have completed key activities in data curation, integration, and annotation.

As a result of these activities, the project has produced the following outcomes:
- 22 models. Some of these are available to the wider scientific community at: https://www.ebi.ac.uk/biomodels/search?query=submitter_keywords%3ATransQST&domain=biomodels_all
- 11 tools. Available through bio.tools website: https://bio.tools/t?page=1&q=%27TransQST%27&sort=score
- ~100 GB of curated/generated data
- 70 scientific peer-reviewed articles

In the final period of the project, all project models, tools and data have been made openly accessible through public repositories as far as possible, following the project´s open access philosophy. We hope these results will therefore serve to provide insights to other projects and the wider scientific community beyond TransQST. All project results are easily accessible through our website: https://transqst.org/results/.
In this final period of the TransQST Consortium, different mechanistic, multi-scale models have been deployed in the organ work packages that describe specific toxicity mechanisms relevant for each organ. The 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 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 and it is expected that such models can be used to supplement regulatory submissions to provide additional evidence of predicted human safety response.

Models from the four organ systems studied in the project, liver, kidney, heart and gastro-intestinal immune system, are currently being tested by the TransQST pharma partners for their intake as part of their internal decision-making processes, advancing towards the acceptance of model-based predictions as industry standard and a precursor for regulatory acceptance. Some of these successes include:

- Toxicogenomics mapping in the liver and kidney that can help to understand mechanisms of toxicity and compare new compounds to those with known toxicity profiles: https://txg-mapr.eu/ and https://bio.tools/TXG-MAPr.
- A quantitative systems toxicology (QST) model for drug-induced kidney injury, one of the novel QST models developed by TransQST consortium: www.ebi.ac.uk/biomodels/MODEL2204290001.
- An agent-based model of the intestinal epithelium, presenting a novel modelling technology in the field of pharmacolog: www.ebi.ac.uk/biomodels/MODEL2212120002.
- Gastrointestinal toxicology models, being used in clinical stages to support combination strategies in cancer treatments (yet to be published).
- Virtual Assay tool combining several heart models, being used to perform in silico drug trials in populations of human cardiac cell models: https://bio.tools/virtual_assay and https://www.cs.ox.ac.uk/ccs/virtual-assay/.
- A Haemodynamic Model, important at present as global regulatory authorities start to produce guidance around haemodynamic testing for chronic use medications: github.com/vanhasseltlab/hemodynamic-simulator and hemosim.lacdr.leidenuniv.nl/.

Additionally, a BioModels resource, a major dissemination platform for the open access models developed in TransQST, has also been released: https://bio.tools/t?page=1&q=%27TransQST%27&sort=score.

The project members also engaged in the common fight against the COVID-19 pandemic. A drug study developed and published from the Heart workpackage demonstrated how QST models can be used to make real-life risk assessments: https://pubmed.ncbi.nlm.nih.gov/33620150/.

As part of a larger effort to improve model reproducibility, TransQST partners have reproduced an eight-point scorecard that modellers, reviewers and journals can use when publishing or reviewing a model: https://www.embopress.org/doi/epdf/10.15252/msb.20209982