Pietro Laddomada 1,2, Marie Sylvianne Rabodoarivelo 3, Evangelos Karakitsios 1,2, Jordana Galizia 3, Alessandro Di Deo 1,2, Chenyao Liu 1,2, Rebeca Bailo 3, Santiago Ramón-García 3,4,5, Oscar Della Pasqua 1,2
1 Institute For Applied Mathematics (IAC), CNR (Rome, Italy), 2 Clinical Pharmacology & Therapeutics Group, University College London (London, UK), 3 Department of Microbiology, Pediatrics, Radiology and Public Health, University of Zaragoza (Zaragoza, Spain), 4 Spanish Network for Research on Respiratory Diseases (CIBERES), Carlos III Health Institute (Madrid, Spain), 5 Research and Development Agency of Aragón (ARAID) Foundation (Zaragoza, Spain)
The authors Pietro Laddomada and Marie Sylvianne Rabodoarivelo contributed equally to this work.
Objectives:
Phase IIa pulmonary tuberculosis (TB) trials typically evaluate early the bactericidal activity (EBA) of monotherapy over 14 days. While translational pharmacokinetic–pharmacodynamic (PK-PD) modeling has successfully predicted human EBA from preclinical in vivo monotherapy data [1], prediction directly from in vitro data remains limited. Such approaches are nonetheless important, as TB treatment ultimately relies on drug combinations [2] and extensive in vivo studies in TB-infected animals are impractical. The objective of this work was to develop and evaluate a translational monotherapy PK-PD framework to predict human EBA of bedaquiline and pretomanid by integrating PBPK-derived free lung concentration–time profiles with in vitro time-kill assay CFU data. This will enable the subsequent translation of combination regimens incorporating these agents.
Methods:
Successful TB treatment requires drug penetration into heterogeneous lung lesions and access to intracellular mycobacterial targets [3]. Accordingly, both PK and PD determinants were considered. Bacterial growth was described using a published Gompertz model parameterized with CFU data under stationary growth conditions in cholesterol medium, while monotherapy drug effects of bedaquiline and pretomanid were characterized using EMAX models, including EC₅₀ and EMAX parameters [4]. Free lung concentration–time profiles were derived using physiologically based pharmacokinetic (PBPK) modeling. For bedaquiline, a previously developed middle-out PBPK model captured lysosomal accumulation due to ionization [5], and free lysosomal concentrations in macrophage-rich cellular lesions were linked to the PD model. For pretomanid, which does not exhibit lysosomal trapping, a published PBPK model was used to derive free lung lesion concentrations in TB patients [6]. Observed monotherapy EBA sputum CFU data were obtained from the literature [7, 8]. Additionally, sensitivity analyses were conducted to assess key assumptions. Baseline bacterial burden and carrying capacity were set to 5.64 CFU/mL, corresponding to the median pre-treatment value. Clinical outcomes were predicted by simulating sputum CFU trajectories in TB patients (1000 simulations), incorporating variability in PK profiles and baseline CFU, as well as demographics representative of Phase IIa EBA populations. Model performance was assessed using visual predictive checks (VPCs). All modeling and simulations were performed in NONMEM, with graphical analyses in R.
Results:
Sensitivity analyses identified lesion volume as a key determinant of predicted sputum CFU decline. Use of a mean lesion volume of approximately 14 mL in the original PBPK model [9], corresponding to total cavitary volume, resulted in underprediction of EBA. In contrast, use of an individual lesion volume of 0.01 mL, consistent with micro-CT estimates of human TB lesions [10], substantially improved agreement with observed CFU reduction. This supports the assumption that drug transfer occurs from the extracellular space into individual lesions and that drug concentrations are equivalent across lesions within the PBPK framework. VPCs demonstrated adequate description of Phase IIa EBA data across all tested doses for both drugs. For pretomanid, numerical predictive checks showed that median EBA values (5th–95th C.I. for median ΔCFU/mL predictions) were EBA50mg = [0.067–1.39], EBA100mg = [0.30–1.95], EBA150mg = [0.58–2.33], and EBA200mg = [0.82–2.63], in agreement with the median observed ΔCFU/mL values of 0.65, 1.22, 0.91, and 1.55, respectively. For bedaquiline, numerical predictive checks showed median EBA values (5th–95th C.I. for median ΔCFU/mL predictions) of EBA1 (200 mg on day 1, 100 mg on days 2–14) = [0.28756–1.08], EBA2 (400 mg on day 1, 300 mg on day 2, 200 mg on days 3–14) = [0.041–1.35], EBA3 (500 mg on day 1, 400 mg on day 2, 300 mg on days 3–14) = [0.13–1.54], and EBA4 (700 mg on day 1, 500 mg on day 2, 400 mg on days 3–14) = [0.27–1.68], consistent with observed median ΔCFU/mL values of 0.72, 1.12, 1.12, and 1.76, respectively.
Conclusions:
A translational monotherapy PK-PD framework integrating PBPK-derived free lung exposures with in vitro time-kill assay data successfully predicted human EBA of bedaquiline and pretomanid across multiple dose levels. Additionally, given that pretomanid is frequently used as a companion drug in bedaquiline-based regimens, this framework can be applied to define clinically relevant pretomanid concentrations for in vitro time-kill assays with bedaquiline, thereby supporting translational evaluation of bedaquiline–pretomanid combinations.
This work has received support from the Innovative Medicines Initiatives 2 Joint Undertaking (grant No 853989).
References:
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[4] www.page-meeting.org/?abstract=11387
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[10] Wells, Gordon et al. “Micro-Computed Tomography Analysis of the Human Tuberculous Lung Reveals Remarkable Heterogeneity in Three-dimensional Granuloma Morphology.” American journal of respiratory and critical care medicine vol. 204,5 (2021): 583-595. doi:10.1164/rccm.202101-0032OC
Reference: PAGE 34 (2026) Abstr 12060 [www.page-meeting.org/?abstract=12060]
Poster: Drug/Disease Modelling - Infection