J Reig-Lopez1, M Merino-Sanjuan1, V Mangas-Sanjuan2, M Prado-Velasco3. 1. Department of Pharmacy and Pharmaceutical Technology and Parasitology, School of Pharmacy, University of Valencia, Av Vicent Andres Estelles, s/n. 46100, Valencia, Spain; Interuniversity Research Institute for Molecular Recognition and Technological Development, Polytechnic University of Valencia-University of Valencia, Valencia, Spain. 2. Department of Pharmacy and Pharmaceutical Technology and Parasitology, School of Pharmacy, University of Valencia, Av Vicent Andres Estelles, s/n. 46100, Valencia, Spain; Interuniversity Research Institute for Molecular Recognition and Technological Development, Polytechnic University of Valencia-University of Valencia, Valencia, Spain. Electronic address: victor.mangas@uv.es. 3. Multiscale Modeling in Bioengineering Research Group and Department of Graphic Engineering. University of Seville, Seville, Spain.
Abstract
BACKGROUND AND OBJECTIVE: The aims of this study are (i) to assess the predictive reliability of the physiologically based software PhysPK versus the well-known population approach software NONMEM for the cited semi-mechanistic PK model, (ii) to determine whether these modelling approaches are interchangeable and (iii) to compare acausal with causal modelling approaches in the framework of semi-mechanistic PK models. METHODS: A semi-mechanistic model was proposed, which assumed oral administration of a solid dosage form with a peripheral compartment and two active metabolites. The model incorporates intestinal transit, dissolution limited by solubility, variable efflux transporter expression along the gut and linear and non-linear metabolism in the gut and liver. Four different approximations to the theoretical model were developed in order to validate both the new software and modelling methodology. RESULTS: Plasmatic concentrations correlation plots as well as relative errors in AUC0-48 and Cmax predictions revealed the accuracy of PhysPK in the prediction of these exposition parameters. Physiological and acausal object oriented version systematically under-estimated AUC0-48 and Cmax of the parent drug, whereas metabolites were over-estimated when taking the semi-mechanistic and extraction-based metabolism version as the reference. CONCLUSIONS: PhysPK has been properly validated, where differences are related to numerical precision of integrators and solvers. A systematic bias for the parent drug and active metabolites was predicted when a semi-mechanistic approach including extraction-based metabolism was compared to the physiologic and acausal approach, showing that interchangeability might be possible when intrinsic-clearance metabolism is implemented in the semi-mechanistic approach. The acausal and object-oriented methodology allows for defining the semi-mechanistic model through its local mechanisms and relationships among entities, without the need to build the final set of Ordinary Differential Equations.
BACKGROUND AND OBJECTIVE: The aims of this study are (i) to assess the predictive reliability of the physiologically based software PhysPK versus the well-known population approach software NONMEM for the cited semi-mechanistic PK model, (ii) to determine whether these modelling approaches are interchangeable and (iii) to compare acausal with causal modelling approaches in the framework of semi-mechanistic PK models. METHODS: A semi-mechanistic model was proposed, which assumed oral administration of a solid dosage form with a peripheral compartment and two active metabolites. The model incorporates intestinal transit, dissolution limited by solubility, variable efflux transporter expression along the gut and linear and non-linear metabolism in the gut and liver. Four different approximations to the theoretical model were developed in order to validate both the new software and modelling methodology. RESULTS: Plasmatic concentrations correlation plots as well as relative errors in AUC0-48 and Cmax predictions revealed the accuracy of PhysPK in the prediction of these exposition parameters. Physiological and acausal object oriented version systematically under-estimated AUC0-48 and Cmax of the parent drug, whereas metabolites were over-estimated when taking the semi-mechanistic and extraction-based metabolism version as the reference. CONCLUSIONS: PhysPK has been properly validated, where differences are related to numerical precision of integrators and solvers. A systematic bias for the parent drug and active metabolites was predicted when a semi-mechanistic approach including extraction-based metabolism was compared to the physiologic and acausal approach, showing that interchangeability might be possible when intrinsic-clearance metabolism is implemented in the semi-mechanistic approach. The acausal and object-oriented methodology allows for defining the semi-mechanistic model through its local mechanisms and relationships among entities, without the need to build the final set of Ordinary Differential Equations.
Authors: Hinojal Zazo; Eduardo Lagarejos; Manuel Prado-Velasco; Sergio Sánchez-Herrero; Jenifer Serna; Almudena Rueda-Ferreiro; Ana Martín-Suárez; M Victoria Calvo; Jonás Samuel Pérez-Blanco; José M Lanao Journal: Front Pharmacol Date: 2022-09-28 Impact factor: 5.988