A compatibility evaluation between the physiologically based pharmacokinetic (PBPK) model and the compartmental PK model using the lumping method with real cases

Lead exposure estimation through a physiologically based toxicokinetic model using human biomonitoring data and comparison with scenario-based exposure assessment: A case study in Korean adults

Pb toxicity is linked to cardiovascular and nephrotoxicity issues. Exposure to this heavy metal can occur through food and drinking water. Therefore, this study aimed to evaluate Pb exposure and assess health risks in Korean adults using a physiologically based toxicokinetic (PBTK) model. Human blood Pb concentrations were monitored using the Korean National Environmental Health Survey (KoNEHS) Cycle 4. The average Pb exposure in Korean adults was 0.520 μg/kg bw/day. The PBTK results were compared with scenario-based results from the 2021 risk assessment report of five heavy metals, including Pb, conducted by the MFDS. Exposure determined through reverse dosimetry was approximately two times higher than scenario-based exposure (0.264 μg/kg bw/day). The higher exposure levels obtained during PBTK analysis may be attributed to sustained exposure within historically more contaminated living environments and the long half-life of Pb. These findings suggest that the PBTK-based method can quantify aggregated exposure levels in the body over time, potentially serving as a complementary tool to address the constraints of scenario-based assessment methods for integrated risk assessment. Moreover, this model is convenient and cost-effective compared with scenario-based exposure estimation. These findings can facilitate the application of model for tracking continuous national changes in hazardous substance levels.

A minimal PBPK model to accelerate preclinical development of drugs against tuberculosis

Introduction: Understanding drug exposure at disease target sites is pivotal to profiling new drug candidates in terms of tolerability and efficacy. Such quantification is particularly tedious for anti-tuberculosis (TB) compounds as the heterogeneous pulmonary microenvironment due to the infection may alter lung permeability and affect drug disposition. Murine models have been a longstanding support in TB research so far and are here used as human surrogates to unveil the distribution of several anti-TB compounds at the site-of-action via a novel and centralized PBPK design framework. Methods: As an intermediate approach between data-driven pharmacokinetic (PK) models and whole-body physiologically based (PB) PK models, we propose a parsimonious framework for PK investigation (minimal PBPK approach) that retains key physiological processes involved in TB disease, while reducing computational costs and prior knowledge requirements. By lumping together pulmonary TB-unessential organs, our minimal PBPK model counts 9 equations compared to the 36 of published full models, accelerating the simulation more than 3-folds in Matlab 2022b. Results: The model has been successfully tested and validated against 11 anti-TB compounds-rifampicin, rifapentine, pyrazinamide, ethambutol, isoniazid, moxifloxacin, delamanid, pretomanid, bedaquiline, OPC-167832, GSK2556286 - showing robust predictability power in recapitulating PK dynamics in mice. Structural inspections on the proposed design have ensured global identifiability and listed free fraction in plasma and blood-to-plasma ratio as top sensitive parameters for PK metrics. The platform-oriented implementation allows fast comparison of the compounds in terms of exposure and target attainment. Discrepancies in plasma and lung levels for the latest BPaMZ and HPMZ regimens have been analyzed in terms of their impact on preclinical experiment design and on PK/PD indices. Conclusion: The framework we developed requires limited drug- and species-specific information to reconstruct accurate PK dynamics, delivering a unified viewpoint on anti-TB drug distribution at the site-of-action and a flexible fit-for-purpose tool to accelerate model-informed drug design pipelines and facilitate translation into the clinic.