CardiacPBPK: An Open-Source software for PBPK modelling of heart tissue

Posted on: 18/02/2020

Researchers from the Jagiellonian University Medical College in Poland have developed a software  that predicts and allows the user to visualize the time-concentration profiles of a parent compound (and its main metabolite) in the venous plasma and heart tissue after oral or intravenous administration of a drug (Tylutki Z. et al). Users can compare the generated predictions with clinically observed data in order to verify their model performance. However, the use of the software requires a lot of data and the output of the simulation does specify whether a compound is cardiologically safe or not.

The software can be freely accessed via the following links: and (or installed on local computers). The source code is publicly available, therefore allowing the users to improve the efficiency of the software and enabling them to customize it to their individual need. The application of CardiacPBPK was demonstrated on the study of amitriptyline intoxication in the case of CYP2D6 genetic polymorphism.

The authors believe that the generated predictions are valuable in terms of drug safety and efficacy assessment, which could be further used in the establishment of drug concentration-effect which could potentially reduce the risk of drug development failure due to cardiotoxicity. This argument is congruent with a recent publication from an OECD expert on PBK modelling (Sachana M., 2019), which indicates the need for guidance on characterising, validating and reporting new generation PBK models. Researchers invest significant time, effort and resources into generating and optimising novel methodologies and test systems that could be used to generate ADME data. However, the potentials and benefits using such data are not clearly communicated.

Therefore, OECD has decided to develop a guidance document that would inform model developers, reviewers, and risk assessors on the current state of science regarding the:

  1. characterisation of PBK models using non-animal ADME data (e.g. model elements and construction, underlying principles and assumptions, model parameters and their estimation) ;
  2. assessment of the model performance (e.g. model verification, sensitivity analysis, uncertainty assessment, applicability domain, limitations) ;
  3. reporting and documentation of model characterisation, validation, and intended applications.


Read the full article:

Tylutki Z. et al, CardiacPBPK: A tool for the prediction and visualization of time-concentration profiles of drugs in heart tissue. Computers in Biology and Medicine 115 (2019) 103484

Sachana M., An international effort to promote the regulatory use of PBK models based on non-animal data. Computational Toxicology 11 (2019) 23–24

Overall workflow of CardiacPBPK