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 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.
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/.
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