Report

Teaser, summary, work performed and final results

Periodic Reporting for period 2 - TransQST (Translational quantitative systems toxicology to improve the understanding of the safety of medicines - Sofia: 116030)

Teaser

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...

Summary

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.

Work performed

Overall the project is on track, all deliverables and milestones were submitted according to the plans.The first year involved a lot of logistics. WP1-2 worked to set up a series of tools to facilitate collaborative work across the Consortium and to stablish the administrative workflows to support the production of high quality project results (Project Handbook,D1.1(M4)). The scientific strategy was leaded by the Executive Committee with continuous support of the Steering Committee members and the Scientific Leadership Team. The internal and external communication and dissemination objectives and key audiences were determined (Communication Plan,D2.1(M6)).
In terms of science, TransQST has finished the first year with several initial achievements that will facilitate tackling the overall project goals.
Two key work packages (WP3-4) delivered the foundation to support the technical activities and also provided a decision-making framework to the organ-specific WPs. Briefly, the major achievements in these enabling work packages can be summarized as follows:
• Based on existing data, a first list of model compounds for modelling challenges in regard to the target 4 organs was defined. To cover the lack of data in some cases, a gap analysis was carried out to define an experimental plan, and new data will be generated accordingly.
• The first release of the data management platform was launched, and this tool will give support for the integration of the data and the management of the knowledge related to the 4 target systems.
• The Data Management Plan has been defined based on all data types and their representation employed in toxicity modelling, with attention to the data standards and data/knowledge representation for their integration and use as input in the different modelling approaches.
• The model selection process and the criteria for continuation or cessation of specific model development among the project life were defined.
• A tool has been developed in the R-Shiny package to visualize and analyse toxicogenomic WGCNA module data. The tool is available to the broad scientific community (https://wgcna-lacdr-dds.nl) and dissemination activities are underway to raise awareness.
There has been encouraging progress across the organ work packages (WP5-8) with tangible scientific outputs.
• The WGCNA tool has already been used for the TG-GATEs cryopreserved primary human hepatocyte dataset (WP5) and will be expanded to include human and rat liver networks. Enabling translation is critical for TransQST and efforts have begun with a statistical analysis of the preservation of WGCNA networks in rat liver, primary rat and human hepatocytes and HepG2 cells.These components form three corners of a parallelogram with human liver being the missing corner. Understanding the relationship between the three corners will facilitate prediction for human liver (see Figure, schema of relationship between liver related information available).
• Work is also underway to create a demonstration model integrating a Genome Scale Metabolic Network liver, PBPK and an ODE model of cytochrome P450 enzyme gene regulation under the influence of the nuclear receptors, PXR and GR. This will be coupled to the WGCNA module perturbation and compound exposure predictions. A similar process involving WGCNA module analysis and network modelling is underway for kidney (WP6).
• In the case of cardiac safety (WP7), the first work in predicting arrhythmogenic potential for specific compounds and linking antiarrhythmic drugs (which can also be proarrhythmic in some circumstances) to QTc prolongation and sudden death was reported to the consortium partners and published (arrhythmia prediction) in manuscript format. As the project matures the scope of these efforts will go beyond QTc-related arrhythmias into cardiotoxicity and haemodynamic mechanisms. The initial data needs, key compounds and models for this extension of the cardiovascular work p

Final results

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.
During the project’s life participants envisage 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 first year of the TransQST Consortium, two main foundations to support more accurate and predictive decision-making tools for quantitative human drug safety assessment were put in place (a data management platform to centralize the modelling data, and the advanced development of the R-Shiny package to visualize/analyse toxicogenomic WGCNA module data).
The improved modelling approaches planned in the scope of the project will ultimately lead to reduced attrition, accelerated development and the approval of safer and more effective therapeutics. At this stage of the project activity, it is difficult to quantify the benefits (in terms of reduction in R&D time, reduction in attrition). We envisage first modest gains, more visible in the near future, as outcomes from the collaborative research addressed in the consortium.

Website & more info

More info: http://transqst.org/.