RevK – Reverse dosimetry and PBPK prediction
In this case study the Open Systems Pharmacology physiologically based pharmacokinetic (PBPK) model will be made accessible and used for risk assessment-relevant scenarios.
- Reverse dosimetry (finding the exposure dose of a chemical leading to a prescribed blood plasma concentration);
- Forward predictions of plasma and tissue concentrations following a prescribed exposure dose or concentration. In this case, Monte Carlo simulations of inter-individual variability will also be performed.
Risk assessment framework
This case study is particularly associated with Tier 2, step 7B (biokinetic refinements). PBPK models tend to be information hungry and are typically reserved to higher tier problems. However, there is a current push toward their use in lower prioritization tiers. This typically requires integration of databases and in silico models to inform PBPK parameter values.
Use Cases Associated
To be defined.
Databases and tools
JaqPot Quattro (NTUA), PK-SIM Open Systems Pharmacology.
A predictive pharmacokinetic model will be integrated.
Currently available services:
Generate, store and share predictive statistical and machine learning modelsService type: Service, Data mining tool, Model, Model generation tool, Trained model, Processing tool, Analysis tool
Interactive computing and workflows sharingService type: Helper tool, Visualisation tool, Processing tool, Analysis tool, Software, Workflow
Computation research made simple and reproducibleService type: Database / data source, Service, Workflow
Aim: understanding the use, form, inputs and outputs of physiologically based (PBPK) pharmacokinetic models. Presentation of software applications for developing PBPK models. Customising PBPK to individual time-drug concentration data. Creating optimal drug dosage regimens