Case Study
RevK – Reverse dosimetry and PBPK prediction

Summary

This case-study demonstrates and document the use of a web interface to physiologically-based pharmacokinetic models for forward and reverse dosimetry calculations. Forward calculations compute internal concentrations from given exposure doses. Reverse calculations compute exposure doses from internal concentrations or measured biomarker levels (e.g., urine concentration data). The result of those calculations can be used in risk assessments to help with in vitro to in vivo extrapolations or interspecies extrapolations. The tools used for this case-study will be developed at NTUA and accessible as user-friendly web services for simulations with the httk PBPK model (httk is a R package) or with the PKSim model, or with a user-defined model. For each of these three models, forward and reverse simulations will be performed for a referenced chemical: Imazalil for the httk model, Theophylline for the PKSim model, and Diazepam for the user-defined model. The exposure scenarios chosen will be in the range of corresponding environmental or therapeutic levels. The conduct of the simulations and their results will be documented in the format of a User’s Manual which will be accessible to future users.

Objectives

The objective of this case study is to demonstrate and document the capabilities of the OpenRisNet-developed web-services for PBPK modeling. Both forward and reverse dosimetry predictions will be illustrated.

Risk assessment framework

The application frameworks are, for example: REACH risk assessments; SEVESO II directive on safety around industrial plants; Internal chemical, cosmetic, or pharmaceutical company assessments of workers’ safety, or consumer’s safety. All those require integration and extrapolation of in vitro and/or in vivo data on animals to assess human risks.

Use Cases Associated

In the future, web-services for QSAR predictions of partition coefficients for chemicals or other PBPK parameters could be used for input in the service’s PBPK models.

Databases and tools

We will use open source software able to implement PBPK models: R (with package httk), PKSim, GNU MCSim. The Jaqpot biokinetic services will be used to publish the PBPK models as web services. Service clients will be developed in Python or as Jupyter notebooks.

Databases of parameter values will be provided by the httk R package, and the PKSim model.

Technical implementation

Implementation of the chosen PBPK model as web services:

PBPK models for a specific class of chemicals and animal species will be selected by the user from a particular PBPK modelling environment (e.g., httk in R, PKSim, GNU MCSim).

The chosen PBPK model will be exposed as a web service using the Jaqpot modelling platform. This is possible through the Jaqpot Protocol of Data Interchange (JPDI) which allows to dynamically and seamlessly incorporate practically any algorithmic implementation into Jaqpot. The protocol specifies the form of data exchange between Jaqpot services and third party algorithm web service implementations. The Jaqpot framework already provides wrappers for the R language and the Python language. Integration with R is made possible through the OpenCPU system, which defines an HTTP API for embedded scientific computing based on R, although this approach could easily be generalized to other computational back-ends (Ooms, 2014). OpenCPU acts as a wrapper to R that is readily able to expose R functions as RESTful HTTP resources. The OpenCPU server takes advantage of multi-processing in the Apache2 web server to handle concurrency. This implementation uses forks of the R process to serve concurrent requests immediately with little performance overhead. By doing so it enables access to those functions on simple HTTP calls converting R from a standalone application to a web service.

User-friendly clients will be developed in Python or as Jupyter notebooks.

Demonstration of PBPK models that have been exposed as web services:

The three models (httk, PKSim and user-specified) will be exercised with Imazalil, Theophylline, and Diazepam, respectively.

For each chemical, we will start by identifying relevant human exposures (e.g. from ExpoCast, or published literature) to be used in forward dosimetry. For reverse dosimetry, we will identify (e.g. from the US NHANES database, or the scientific literature) typical blood or urine concentrations found in humans to be used as input to the exposure dose reconstruction.

The model will be parameterized using user-specified or pre-programmed tabulated physiological data.

For forward dosimetry predictions, each model will be run with the given exposure scenario to predict internal concentrations after 24 hours. Plots of the concentration time-courses will be generated and compared to reference simulations (generated with the stand-alone versions of the same packages).

For reverse dosimetry the model will be run forward iteratively with user set exposures so as to match the input biomarkers (that is: manually invert the model). The external exposure level leading to data-matching biomarker level will be recorded as final estimate.

Outcomes

In the Appendix, two tutorials provide descriptions of preliminary implementations of this case study: the first tutorial uses PKSim with theophylline as the chemical of interest. The second tutorial uses httk and Imazalil. Those were demonstrated and received positive feedback during the biokinetics workshop of the OpenTox Euro conference in Basel, 2017, where we had the opportunity to interact with potential users.

The preliminary results of this case-study demonstrates that the OpenRiskNet framework can be used as a central e-platform for the biokinetics community, where the users can publish, share, search and use PBPK models. Additional biokinetic models will be integrated in the future and will be tested in terms of producing successful results (time-concentration profiles). The case study will deliver a User’s Manual including a tutorial for this service.

Currently available services:

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

Related resources

Report
Case Study description - Reverse dosimetry and PBPK prediction [RevK]
10 May 2019
Abstract:
This case-study demonstrates and document the use of a web interface to physiologically-based pharmacokinetic models for forward and reverse dosimetry calculations. Forward calculations compute internal concentrations from given exposure doses. Reverse calculations compute exposure doses from internal concentrations or measured biomarker levels (e.g., urine concentration data). The result of those calculations can be used in risk assessments to help with in vitro to in vivo extrapolations or interspecies extrapolations. The tools used for this case-study will be developed at NTUA and accessible as user-friendly web services for simulations with the httk PBPK model (httk is a R package) or with the PKSim model, or with a user-defined model. For each of these three models, forward and reverse simulations will be performed for a referenced chemical: Imazalil for the httk model, Theophylline for the PKSim model, and Diazepam for the user-defined model. The exposure scenarios chosen will be in the range of corresponding environmental or therapeutic levels. The conduct of the simulations and their results will be documented in the format of a User’s Manual which will be accessible to future users.
Additional materials:
Case Study report

Target audience: Risk assessors, Researchers, OpenRiskNet stakeholders, Bioinformaticians
Open access: yes
Licence: Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
Organisations involved: NTUA, INERIS
Report
Tutorial
RevK Pharmacokinetics OpenRiskNet Case study using Jaqpot web modelling platform
Philip Doganis
15 Oct 2018
Related services:
Jaqpot GUI
Jaqpot API

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
Tutorial
Tutorial
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
Abstract:
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
Tutorial