tristan-rat-analysis
Analysis of the TRISTAN rat data
Science Score: 46.0%
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Low similarity (12.9%) to scientific vocabulary
Repository
Analysis of the TRISTAN rat data
Basic Info
- Host: GitHub
- Owner: openmiblab
- License: apache-2.0
- Language: Python
- Default Branch: main
- Size: 526 KB
Statistics
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
- Releases: 2
Metadata Files
README.md
Measuring drug-mediated inhibition of liver transporters: analysis of TRISTAN rat data
📚 Context
The liver is responsible for filtering waste products from the blood, and evacuating these by excreting them to bile. Drugs commonly affect these procesesses, potentially leading to toxic side effects.
If a drug inhibits excretion into the bile, then harmful material can get stuck in liver cells and cause damage to the liver. This is commonly referred to as drug-induced liver injury (DILI). If a drug on the other hand blocks the uptake of these materials into the liver, they will circulate in the blood for too long and may cause harm elsewehere.
When dealing with novel drugs, either in basic research or drug development, it is often unknown to what extent a drug affects the uptake or excretion into the liver. This can expose trial participants to significant risk, or even patients in clinical practice if the risk is not identified during development.
In order to mitigate these risks, the TRISTAN project developed an MRI-based method to measure the effect of drugs in liver transporters directly. An analysis pipeline was developed which generates measurements from signal-time curves in liver and aorta.
The pipeline in this repository derives some key results from previous studies in rats published by the TRISTAN consortium. The analysis was done post-hoc as an illustration and replication excercise with new code, but does not aim to replicate the exact figures and tables from the manuscript.
🛠️ Methodology
The inputs to the pipeline are metrics produced by the assay for primary and secondary objectives, saved in a persistent data archive.
The output is the a number of figures summarising key findings from the rat studies.
💻 Usage
The pipeline can be run after installing the requirements:
console
pip install -r requirements.txt
The folder build contains the output of the analysis. To reproduce it, delete the build folder and run the script src/run.py. This takes less than a minute on a standard laptop computer and should recreate all results in the build folder.
📄 Code structure
The src folder contains all the source code, with the top level entry scripts run.py. This call functions in the subfolder stages.
The build folder contains the output of the top level scripts. It can be deleted and will be fully rebuilt when running the script. The build folder has the following contents:
- Data: contains the downloaded data.
- Tables: tables and numerical results produced by src/methods/analysis.py.
- Figs: Figures produced by src/methods/plot.py.
❤️ Citation
Thazin Min, Marta Tibiletti, Paul Hockings, Aleksandra Galetin, Ebony Gunwhy, Gerry Kenna, Nicola Melillo, Geoff JM Parker, Gunnar Schuetz, Daniel Scotcher, John Waterton, Ian Rowe, and Steven Sourbron. Measurement of liver function with dynamic gadoxetate-enhanced MRI: a validation study in healthy volunteers. Proc Intl Soc Mag Reson Med, Singapore 2024, 4015.
💰 Funding
The work was performed as part of the TRISTAN project on imaging biomarkers for drug toxicity. The project was EU-funded through the Innovative Health Initiative.
👥 Contributors
 Ebony Gunwhy |
 Steven Sourbron |
Owner
- Name: openmiblab
- Login: openmiblab
- Kind: organization
- Repositories: 1
- Profile: https://github.com/openmiblab
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| Name | Commits | |
|---|---|---|
| Steven Sourbron | s****n@s****k | 4 |
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Dependencies
- matplotlib ==3.10.3
- miblab ==0.0.15
- numpy ==2.3.0
- pandas ==2.3.0
- pydmr ==0.0.4