PhysPK: Interactive simulation software for physiological systems
Compliant with PBPK, PK and PD methodological standards
Cutting edge technology for population simulation and parameter estimation
Powerful objects devoted to allometric scaling, parameters conversion algorithms, IVIVE
Very rich physiological human and animals’ models, open to users for reuse and experimentation
Multidomain approach with true reusability and multiscale modelling and simulation
Seamless connection among physiological systems and artificial devices models
Open modelling based on three layer architecture: processes (dynamics), PK and Physiological elements, and signal layer (PD, control, indices, …)
An intuitive and graphical modelling interface seamlessly connected to a powerful object-based modeling language
Simulation scenarios guided through Wizard-based experiments: steady, transient, parametric types of studies
Healthcare and e-health industry
Chemical risk analysis
For today’s, using simulation tools to improve the design process of medical products has become an absolute necessity. Systems simulations allow companies to reduce design and manufacturing costs while shortening development times.
Use Case: Developing a PBPK model with oral administration of MTX and 6-MP under PhysPK
PBPK model for the prediction of 6-MP and MTX kinetics and interactions in patients with acute lymphoblastic leukaemia (ALL), taken the earlier work of Ogungbenro et al (2014) as a reference. A previous PBPK model for MTX was the starting point. Simplified building process:
Building of a PBPK base model with stomach, gut lumen, enterocyte, gut tissue, spleen, liver vascular, liver tissue, kidney vascular, kidney tissue, skin, bone marrow, thymus, muscle, rest of body and RBC. Strong quasi-static MTX binding is considered in near all tissues. Gut enterocyte and liver includes metabolism of 6-MP through Xanthine oxidase (XO), which is reversibly inhibited by MTX. RBC includes polymerization of MTX. Kidney is described through the nephron dynamics.
Environment and population (application) models are built using the PBPK based model. The parameters used by this application model are processed by allometric or other types of algorithms, to customize the model to requirements.
The PBPK application model is executed through the associated experiments, making population-optimization fitting, parametric analysis, transient studies, etc. Results are obtained in a rich monitor environment and in different format output files.
It is presented a simple transient experiment which simulates the evolution of the system physiology during 20 hours, after the oral drug administration. The transient experiment structure is created by PhysPK in EL code if it is demanded by the users. There are also graphic wizards, that can manage external parameter data sets in a friendly an powerful way. The experiment can be compiled and run internally (PhysPK IDE) or exported for external execution.
Reference works Ogungbenro, K., & Aarons, L. (2014). Physiologically based pharmacokinetic modelling of methotrexate and 6-mercaptopurine in adults and children. Part 1: Methotrexate. Journal of Pharmacokinetics and Pharmacodynamics, 41(2), 159–171. Ogungbenro, K., & Aarons, L. (2014). Physiologically based pharmacokinetic modelling of methotrexate and 6-mercaptopurine in adults and children. Part 2: 6-mercaptopurine and its interaction with methotrexate. Journal of Pharmacokinetics and Pharmacodynamics, 41(2), 173–185.
Prado-Velasco, M., Borobia, A., & Carcas-Sansuan, A. (2020). Predictive engines based on pharmacokinetics modelling for tacrolimus personalized dosage in paediatric renal transplant patients. Scientific reports, 10(1), 1-18.
Reig-Lopez, J., Merino-Sanjuan, M., Mangas-Sanjuan, V., & Prado-Velasco, M. (2020). A Multilevel Object- Oriented Modelling Methodology for Physiologically-Based Pharmacokinetics (PBPK): Evaluation with a Semi-Mechanistic Pharmacokinetic Model. Computer Methods and Programs in Biomedicine, 105322.
Prado-Velasco, Manuel. (2018). New approach based on mathematical modelling to compute drug bioavailability using the PhysPK™ biosimulation system. 10.13140/RG.2.2.17896.16648.
Ignacio Gonzalez-Garcia, Manuel Prado-Velasco, Diego Garcia-Alvarez, Carlos Fernández-Teruel, Salvador Fudio (2017 – Budapest, Hungary). Comparison of FO – FOCE population parameter estimation methods in PhysPK 2.0 against NONMEM 7.3.
Prado-Velasco, Manuel. (2017). Brief analysis and approaches to compute the bioavailability using the PhysPK platform.
Prado-Velasco, Manuel & Rueda, Almudena & Borobia, Alberto & Carcas Sansuán, Antonio & García-Álvarez, Diego & Serna, Jenifer. (2017). PBPK versus PK modeling of Tacrolimus drug in patients with renal transplant as knowledge engines for personalized posology software: PhysPK® development and preliminary results.
Prado-Velasco, Manuel & Rueda, Almudena & Borobia, Alberto & Carcas Sansuán, Antonio & García, Diego & Serna, Jenifer. (2016). Computing the personalized optimal posology for drugs with PhysPK: development of PBPK/PK/PD models and automatic generation of software for clinical use.
Prado-Velasco, Manuel. (2016). Bridging the gap between open and specialized modelling tools in PBPK/PK/PD with PhysPK/EcosimPro modelling system: PBPK model of methotrexate and 6-mercaptopurine in humans with focus in reusability and multilevel modelling features.
Prado-Velasco, Manuel. (2015). PhysPK/EcosimPro: Sistema de modelado y simulación de sistemas fisiológicos. Metodología, arquitectura y aplicación a problemas PBPK/PK/PD.
Matos, Tome & Prado-Velasco, Manuel & Navarro Ruiz, Juan & Vallez, Cristina. (2013). On a reusable and multilevel methodology for modeling and simulation of pharmacokinetic-physiological systems: A preliminary study. Computers in biology and medicine. 43. 1512-22. 10.1016/j.compbiomed.2013.07.025.
Prado-Velasco, Manuel. (2013). Flow Modeling of Hollow Fiber Dialyzers. Studies in Computational Intelligence. 404. 519-562. 10.1007/978-3-642-27458-9-11.