Application of physiologically based pharmacokinetic-pharmacodynamic modelling strategies in the preclinical and clinical setting

Resumen

Modelling and simulation strategies are a powerful resource to increase the efficiency in the drug discovery and development process. Able to differentiate system- and drug-related parameters, physiologically based pharmacokinetics (PBPK) allows to "easily" develop mechanistic models to check untested or untestable scenarios and to answer "what-if" questions in the safest possible way. Open software and designed modelling software tools do exist to develop PBPK models, being the latter necessarily qualified for its purpose. Because of its algorithmic nature, these software need systems of ordinary differential equations defining local processes and relation among the tissues/organs that ultimately constitute the system/organism. And these equations must be defined from scratch by the modeller or by the designer. The present Thesis will start with the validation of a multilevel object-oriented and acausal (non-algorithmic) modelling methodology and will be proposed as an alternative to algorithmic methodologies because of its re-usability (object-oriented) and comfort (no need to define ordinary differential equations systems) for the modeller. In the second part of the Thesis, preclinical utility of PBPK modelling will be highlighted through the development of a PBPK/pharmacodynamic model for the small molecule MBQ-167 to predict tumour growth inhibition for two breast cancer cell lines (i.e., HER2 positive and triple negative) in mice. Additionally, model simulations will be performed to explore the effect of more intensive dosing regimens in tumour size reduction. After an extensive review of the pharmacokinetic parameters driving atorvastatin absorption, distribution, metabolism and excretion processes, the development of a PBPK model for atorvastatin and its metabolites to in silico assess the drug-gene interaction with SLCO1B1 polymorphisms will be presented, moving the application of PBPK modelling and simulations to the clinical setting. Finally, the last part of the present Thesis will focus on the PBPK modelling of large molecules in oncology by means of the development of PBPK models for the monoclonal antibodies directed to EGFR family membrane receptors pertuzumab, trastuzumab, and cetuximab