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

Abstract

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.

Extrapolation of lung pharmacokinetics of antitubercular drugs from preclinical species to humans using PBPK modelling

“…The authors concluded that both plasma and lung PK profiles were well summarized by AUC and C max values. 29 Hence, in our analysis, these measures were used as metrics of model performance for extrapolation purposes together with visual inspection of concentration–time profiles.…”

Targeting decaprenylphosphoryl-β-D-ribose 2′-epimerase for Innovative Drug Development Against Mycobacterium Tuberculosis Drug-Resistant Strains

“…To compare the results obtained from these selected compounds, 4 reference inhibitors against DprE1 were selected from the literature: BTZ043, OPC_167832, TBA_7371, and PBTBZ169. 22 - 25 …”

stormTB: A web-based simulator of a murine minimal-PBPK model for anti-tuberculosis treatments

“…stormTB implements the minimal physiologically based pharmacokinetics model (mPBPK) presented by (Reali et al, 2024) that describes the disposition of 11 anti-pulmonary-TB drugs in murine models. The supported drugs are rifampicin (RIF, R), rifapentine (RPT, P), pyrazinamide (PZA, Z), ethambutol (EMB, E), isoniazid (INH, H), moxifloxacin (MOX, M), delamanid (DEL), pretomanid (PRE, Pa), bedaquiline (BDQ, B), Quabodepistat (QBS, OPC-167832), and GSK2556286 (G286).…”

“…Here, we present a web-based tool tailored for anti-TB drug dynamics and PK/PD metrics in the treatment scenarios to support model-informed treatment development under a unified perspective. It leverages a previously published minimal physiologically based pharmacokinetic (mPBPK) model that supports 11 historical and under-development anti-TB drugs in a common pre-clinical murine model (Reali et al, 2024). We have then consolidated the results from model calibration and virtual population-based uncertainty quantification in the herein introduced R-based web app, stormTB, streamlining model inspection and enabling users to conduct independent what-if analyses using the mPBPK platform.…”

“…We have then consolidated the results from model calibration and virtual population-based uncertainty quantification in the herein introduced R-based web app, stormTB, streamlining model inspection and enabling users to conduct independent what-if analyses using the mPBPK platform. Users can compose a treating scenario by selecting one drug from the 11 originally included in (Reali et al, 2024), the dosage and the treatment length. Scientists can iteratively adjust the experimental settings based on the simulated PK/PD performance and save the resulting scenario in the workspace.…”