Case Study
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.

Service integration

A predictive pharmacokinetic model will be integrated.

Currently available services:

  • Generate, store and share predictive statistical and machine learning models
    Service type: Service, Data mining tool, Model, Model generation tool, Trained model, Processing tool, Analysis tool
  • Interactive computing and workflows sharing
    Service type: Helper tool, Visualisation tool, Processing tool, Analysis tool, Software, Workflow
  • Computation research made simple and reproducible
    Service type: Database / data source, Service, Workflow

Related resources

RevK Pharmacokinetics OpenRiskNet Case study using Jaqpot web modelling platform
Philip Doganis
15 Oct 2018
Related services:
Jaqpot API
Jaqpot GUI

Target audience: Risk assessors, Researchers, OpenRiskNet stakeholders, Data modellers
Open access: yes
Licence: Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
Organisations involved: NTUA
Biokinetics Modelling: use, form, inputs and outputs of PBPK models
Harry Sarimveis, Aris Dokoumetzidis, Pantelis Karatzas, Philip Doganis, Periklis Tsiros, Nikolas-Marios Katritsis, Georgia Tsiliki
9 Oct 2018
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

Target audience: Risk assessors, Researchers, Developers, Data owners, Nanosafety community, OpenRiskNet stakeholders, Regulators, Data modellers
Open access: yes
Licence: Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
Organisations involved: NTUA