Yu Fu (1), N. Snelder (2), M.M. Said (1), P.H. van der Graaf (1,3), J.G.C. van Hasselt(1)
(1) System Biomedicine and Pharmacology, LACDR, Leiden University, the Netherlands; (2) LAP&P Consultants BV, Leiden, the Netherlands (3) Certara QSP, Canterbury, UK
Objectives: Characterization of hemodynamic drug effects and mode of action (MOA) is a crucial part of cardiovascular translational safety assessment. Hemodynamic regulation is complex and mediated by multiple feedback mechanisms. Mathematical modelling of the hemodynamic system can be helpful to quantitatively assess mode of action and to study the effect of different dose schedules on hemodynamic endpoints. To this end, Snelder et al [1,2] previously developed a hemodynamic systems model consisting of five biomarkers and their interactions, including heart rate (HR), stroke volume (SV), total peripheral resistance (TPR), cardiac output (CO) and mean atrial pressure (MAP). This modelling framework can be of relevance to support preclinical safety pharmacologists, but cannot be easily used by non-modelling safety pharmacology scientists. In the current project we aimed to develop a user-friendly web application to perform model-based predictions of drug effect on hemodynamic endpoints based on the Snelder model. Specifically we aimed to tool can support identification of expected hemodynamic mode of action, and to support the design of cardiovascular safety studies.
Methods: A web application was implemented using the R package Shiny. The RxODE R package was used to perform using the ordinary differential equation model by Snelder et al [1,2]. The packages shinydashboard, shinyalert and shinyWidgets were used to further enhance the user interface. Typical values of species-specific parameters in rat and drug-specific parameters for seven reference drugs are available according to estimates in Snelder model and were included in the web application [1,2]. The application allows simulation of PK, HR, CO and MAP for reference drugs and investigational drugs. The user can also upload datasets and manually define user-defined models.
Results: The shiny web app can be accessed at http://hemodynamic-simulator.eu/. The source code is posted to Github. Model-based prediction can be obtained by following the following steps:
1. select species for simulation, select strains ;
2. select reference drug and define dosage for simulation (optional);
3. perform simulation for the investigational drug by define drug-specific PK and PD parameters and dose regimen. A circadian rhythm can be described with a cosine function can be include or exclude in the simulations. Three types of MOA can be simulated by selecting different drug effects on HR, SV or TPR;
4. upload of an input data file including observations of PK, HR, CO or MAP using a predefined dataset template (optional)
5. generation of a PDF report detailing all the information for the! simulation and including the plots (optional).
Conclusion: This application with a user-friendly interface can help safety evaluation, study design and decision making in drug development. We plan to expand this app with additional reference drugs and species in the future, and will investigate the possibility of performing model-fitting.
References:
[1] Snelder, N. et al. Br J Pharmacol 169, 1510-1524, doi:10.1111/bph.12190 (2013).
[2] Snelder, N. et al. Br J Pharmacol 171, 5076-5092, doi:10.1111/bph.12824 (2014).
Reference: PAGE () Abstr 9484 [www.page-meeting.org/?abstract=9484]
Poster: Drug/Disease Modelling - Safety