Fysiologisch gebaseerd farmacokinetisch modelleren van geneesmiddelen die worden gemetaboliseerd door niet-CYP450-enzymen en de toepassing ervan om de farmacokinetiek te voorspellen bij patiënten met levercirrose

BACKGROUND PBPK modeling is routinely applied to predict pharmacokinetics and drug interaction potential at all stages from Phase 0 through to Phase 3 and filing based on in vitro data. However, these predictions are made with high confidence only when the major metabolic routes are due to the CYP 450 enzymes. This is because reliable scaling of in vitro data generated in standardized systems such as human liver microsomes, human hepatocytes and recombinantly expressed isoforms has been demonstrated only for the CYPs. Quantitative scaling for non-CYP enzymes such as UGTs and AO is still challenging due to gaps in the in vitro toolkit and the significant extra-hepatic expression of these enzymes. However, for certain non-P450 metabolized drugs the gap in in vitro to in vivo extrapolation (IVIVE) can be overcome by top-down fitting of PBPK model parameters to clinical data. This was recently demonstrated using lorazepam and oxazepam, 2 drugs cleared by multiple UGT enzyme isoforms. The availability of clinical data from mass balance studies and studies in genotyped subjects were used to fit clearance and fraction metabolized parameters in a GastroPlus model. The model was then applied to predict additional clinical studies and verify the back calculated parameters (PhD project of Luca Docci and paper recently submitted for publication). Similar work has been performed using pRED development compounds (e.g. previous taar1 project candidate cleared majorly via a specific UGT isoform demonstrated by Kenichi). Aldehyde oxidase is another non-P450 enzyme family which is appearing more frequently in our pre-clinical portfolio (e.g. TLR789) and where the lack of IVIVE presents a challenge. Thus, we envisage, that by a combination of data collection from the literature and in-house sources, and detailed PBPK modelling, we can build up a set of well verified PBPK models for drugs which are substrates of specific UGT and AO isoforms. These models can then be leveraged when pRED development compounds are cleared by the same enzymes isoforms, using the scaling factors derived for the reference drugs to fill the gaps in IVIVE. IMPACT This work would address a current gap in the start-of-art in PBPK modelling and high quality papers should be acceptable for publication and should be of interest to the community. Furthermore as we see more and more non-CYP metabolized molecules in our pre-clinical and clinical portfolio, there should be an immediate benefit for pRED projects. RESOURCES We envisage this as a pure modelling project leveraging existing data. In addition the RPF could take advantage of ongoing research by a recently formed cross-company UGT enzyme working group formed under the umbrella of the SimCYP consortium. MENTORING TEAM Neil Parrott (tM&S) and Kenichi Umehara (iSAFE) are expert users of GastroPlus and SimCYP and would jointly mentor this project.