Evangelos Karakitsios1,2, Professor Oscar Della Pasqua2, Associate Professor Aristides Dokoumetzidis1,3
1Department of Pharmacy, National and Kapodistrian University of Athens, 2Institute for Applied Computing “Mauro Picone”, National Research Council (CNR), 3Athena Research Center, Pharma-Informatics Unit
Objectives Tuberculosis (TB) is a major global infectious disease, primarily affecting the lungs (pulmonary TB). Active disease leads to focal lesions (cavitation) that progress into granulomas [1]. Current treatments are based on empirical efficacy and safety, often neglecting complex pharmacokinetic (PK)–pharmacodynamic (PD) relationships and tissue equilibration processes. This gap hinders regimen selection and treatment optimization to be tested in the clinic. This study aimed to develop physiologically based pharmacokinetic (PBPK) models for key anti-TB drugs—rifampicin, pyrazinamide, isoniazid, ethambutol, and moxifloxacin—focusing on lung PK in healthy and TB-infected tissue (cellular lesions and caseum) in preclinical species, with subsequent extrapolation to humans. PBPK modeling was also applied to bedaquiline, used for multidrug-resistant TB, with notable PK properties but limited lung PK data in humans. The main question we address was whether unbound plasma PK reliably predicts unbound lung tissue PK, and as such can be used for dose selection in humans. The ultimate goal is to develop a lung PBPK extrapolation platform-from preclinical species to humans- that can be applied to novel anti-TB candidates, using specific in vitro and preclinical in vivo data. Methods Preclinical in vivo data from mice, rats, dogs, and rabbits, along with clinical data in patients, were collected from the literature [2-12] or provided by Janssen R&D, a partner in the ERA4TB consortium. It is noted that preclinical in vivo datasets from various distinct species were available for every drug. Empirical plasma PK models for each species were linked to multi-compartment, permeability-limited lung models using a middle-out PBPK approach [13]. Physiological parameters were then incorporated to enable lung PK scaling across species. Additionally, lung’s extracellular water (EW) served as the connection between healthy and infected tissue, assuming permeability limitation between EW and cellular lesions, as well as passive diffusion for drug transport between cellular lesions and caseum. Finally, for each drug, key lung PK parameters were optimized based on in vivo preclinical data in the smallest available species, before extrapolating lung PK to bigger species and, eventually, to humans. A basic assumption in our approach, in accordance with the mechanistic model of Rodgers and Rowland, is that strong to moderate bases, such as rifampicin, moxifloxacin and ethambutol, will predominantly bind to acidic phospholipids of intracellular water (IW), while weak bases, such as pyrazinamide and isoniazid, will mainly bind to albumin within EW. The relevant affinity constants were kept constant across species for lung PK extrapolation purposes [14]. It is also noted that in case of bedaquiline, lysosomal trapping and anomalous diffusion kinetics in TB-infected caseum were incorporated to explain its noteworthy PK characteristics. Results and Discussion In rabbits, the optimized unbound fractions of rifampicin, moxifloxacin, and ethambutol in IW were 1.5%, 5.6%, and 8%, respectively. For pyrazinamide and isoniazid in mice, the optimized unbound fractions in EW were 25% and 17%, respectively. For all these drugs in humans, the extrapolated average daily tissue AUC (area under the curve) and Cmax (maximum concentration) values across different lung regions were within twofold of the observed values. Additionally, predicted unbound concentrations in human caseum were lower than in plasma for both rifampicin and moxifloxacin. In the cellular rim, predicted unbound concentrations of rifampicin were slightly lower than plasma levels, whereas moxifloxacin unbound concentrations were significantly higher. On the other hand, predicted free pyrazinamide concentrations in the cellular rim were nearly identical to plasma levels. Similarly, for bedaquiline, average extrapolated healthy lung tissue AUC, Cmax and single concentration-time points for rats and dogs were all within two-fold of observed values. Regarding infected tissue, caseum concentrations were significantly lower than WCC90 value (minimum bactericidal concentration achieving a one-log kill of non-replicating bacteria under hypoxic, nutrient-rich conditions-Wayne Cidal Concentration). On the contrary, unbound drug concentrations in lysosomes of foamy macrophages exceeded MIC50 (minimum inhibitory concentration at which 50% of the isolates are inhibited), suggesting a potential new mechanism of action given the drug’s minimal unbound fraction in plasma. Conclusions The developed PBPK modeling platform enabled extrapolation of lung PK from preclinical species to humans for a set of known anti-tubercular drugs, allowing prediction of unbound drug concentrations in different lung compartments, which are usually unaccessible in patients in standard clinical trials. In addition, unlike empirical models, our PBPK analysis revealed that unbound plasma PK does not consistently predict unbound lung tissue PK. More specifically, ionization differences between EW and cellular granuloma compartments, as well as extended time to reach steady state in caseum, contribute to these discrepancies. Incorporating drug-specific parameters, preclinical in vivo and in vitro data into PBPK models may highlight which candidates may exhibit these discrepancies. Furthermore, the availability of unbound tissue concentrations provides the basis for a more systematic evaluation of the PD effects of both existing and new anti-TB drugs, ensuring accurate interpretation of the potency and maximum antibacterial activity of selected regimens. Moreover, our analysis identified a potential new mechanism of action for bedaquiline. The model predicted unbound concentrations above MIC50 in lysosomes of foamy macrophages, highlighting its potential efficacy against bacteria within phagolysosomes, which are cytoplasmic bodies, being formed through the fusion of phagosomes and lysosomes. These insights underscore the value of PBPK approaches in guiding the design of second-generation diarylquinolines (e.g., TBAJ-587 and TBAJ-876) in order to improve treatment outcome. Conclusively, the current work highlights the value of the middle-out approach which uses data-driven models but with PBPK parametrisation, for the purpose of translation of PK preclinical data in tuberculosis. The method uses total drug PK in homogenates in preclinical species to ultimately predict unbound pharmacologically relevant PK in lung compartments in humans, that can be used to inform clinical outcomes and/or design biorelevant in vitro PKPD experiments. Acknowledgments This work has received support from the Innovative Medicines Initiatives 2 Joint Undertaking (grant No 853989).
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Reference: PAGE 33 (2025) Abstr 11490 [www.page-meeting.org/?abstract=11490]
Poster: Drug/Disease Modelling - Infection