Quantitative Systems Pharmacology Group Leader Fondazione COSBI Rovereto, Trentino-Alto Adige, Italy
Disclosure(s):
Federico Reali: No financial relationships to disclose
Objectives: Tuberculosis (TB) is an infectious disease that still affects and kills millions of people each year [1]. Recent initiatives have produced new anti-TB compounds currently in various stages of clinical development. New regimens are being investigated to shorten treatment durations and provide safer alternatives to current standards of care. In this context, TBD11 (mCLB073) is a small-molecule agonist of Rv1625c that disrupts cholesterol utilization by Mycobacterium tuberculosis [2]. Nonclinical studies have demonstrated acceptable drug metabolism and pharmacokinetics properties and a favorable toxicological profile for TBD11, making it a promising candidate for inclusion in novel anti-TB regimens. To support its preclinical and clinical development, we trained and validated a recently published minimal physiologically based pharmacokinetic (mPBPK) model [3] using various animal models to suggest a TBD11 dose range for its first-in-human (FIH) study.
Methods: The previously published mPBPK model [3] was adapted and extended to describe the disposition of anti-TB compounds in both TB-infected and non-infected rabbits, mice, rats, dogs, and humans. Tissue-to-plasma partition coefficients were calculated using the Rodgers and Rowland equations [4], and species-specific anatomical parameters were retrieved from the literature [5]. The model was implemented in MATLAB R2024b and simulated using the ode15s solver. Parameter estimation was carried out via the Covariance Matrix Adaptation – Evolution Strategy [6], and the parameters’ uncertainty was quantified via Monte Carlo simulations.
Results: To suggest human doses for TBD11, we iteratively calibrated and validated the mPBPK model presented in [3] for various species, starting from TB-infected and uninfected rabbit data. Based on the rabbit model, rat- and mouse-specific parameterizations were derived adjusting species-specific physiological parameters, applying allometric scaling to body clearance, and were validated on rat and mouse data. Additionally, a dedicated version of the model was developed for a different formulation using beagle dog data. Human exposure predictions were obtained by integrating physiological data with modeling outputs. By combining pharmacodynamic targets, e.g., in vivo target area-under-the-curve and time above the Minimal Inhibitory Concentration (MIC), and toxicological information, such as the preliminary No Observed Adverse Effect Level (NOAEL), the model was used to define an efficacious and tolerable dose range for the FIH study. Leveraging on the features of the mPBPK model, the results were drawn not only for plasma, but also for the sites of action, namely, lungs and TB-lesions.
Conclusions: The application of a multispecies mPBPK model to support the FIH dose selection highlights a promising example in the landscape of model-informed drug development, where cross-species preclinical and in vitro results are combined to identify tolerable and efficacious dose selection. The results support the regulatory process for TBD11. In future extensions, the model will also be used to evaluate the efficacy in combination with other anti-TB treatments to support the design of novel therapeutic regimens.
Citations: [1] World Health Organization (2023), Global tuberculosis report 2023 [2]Wilburn et al, Pharmacological and genetic activation of cAMP synthesis disrupts cholesterol utilization in Mycobacterium tuberculosis. PLoS Pathogens, 18(2): e1009862, 2022. [3] Reali et al, A minimal PBPK model to accelerate preclinical development of drugs against tuberculosis, Frontiers in Pharmacology, vol. 14, p. 1272091, 2024, [4] Rodgers et al., Physiologically based pharmacokinetic modeling 2: predicting the tissue distribution of acids, very weak bases, neutrals and zwitterions, Journal of Pharmaceutical Sciences 95(6):1238-57, 2006 [5] Mavroudis et al., Development and validation of a physiology-based model for the prediction of pharmacokinetics/toxicokinetics in rabbits, Plos One, 2021 [6] Hansen Nikolaus, The CMA Evolution Strategy: A Comparing Review; in Lozano et al., Towards a New Evolutionary Computation. Studies in Fuzziness and Soft Computing, vol 192, pp 75-102, Springer, 2006
