A multilevel object-oriented modelling methodology for physiologically-based pharmacokinetics (PBPK): Evaluation with a semi-mechanistic pharmacokinetic model. (June 2020)

• Record Type: Journal Article
• Authors: Reig-Lopez, J.; Merino-Sanjuan, M.; Mangas-Sanjuan, V.; Prado-Velasco, M.
• Is Part Of: Computer methods and programs in biomedicine. Volume 189(2020)
• Publication Date: 2020-06
• Subjects: PBPK -- Acausal modelling -- Semi-mechanistic -- Intrinsic clearance -- P-glycoprotein -- Metabolites; AUC0-48 area under the curve from 0h to 48h -- Cmax maximal concentration -- EL EcosimPro language -- MAE mean absolute error -- ODEs ordinary differential equations -- P-gp P-glycoprotein -- PBPK physiologically based pharmacokinetic -- PD parent drug -- PhysPK PhysPK Biosimulation software -- PK pharmacokinetic -- PM primary metabolite -- RE relative error -- RMSE root mean squared error -- SM secondary metabolite; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2020.105322
• Languages: English
• ISSNs: 0169-2607

Abstract

Highlights: PhysPK Biosimulation Software was successfully validated versus NONMEM. Extraction-based clearance should be limited to BCS class IV drugs. Intrinsic-CL metabolism is adequate for parent drug using semi-mechanistic models. Multilevel-acausal differentiates simulation components to mathematical functions of the system. 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.