Umberto Villani (1), Albin A.M. Leding (2), Peter Velickovic (1), Salvatore D’Agate (1), Eik Hoffmann (3), Cyril Gaudin (3), Ulrika S.H. Simonsson (2), Oscar Della Pasqua(1)
(1) Istituto per le Applicazioni del Calcolo, Consiglio Nazionale delle Ricerche, Rome, Italy; (2) Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden; (3) Institut Pasteur de Lille, Lille, France
Objectives:
Molecules that target the host rather than the pathogen offer an attractive paradigm shift in the treatment of tuberculosis (TB). These ‘host-directed therapeutics’(HDTs) [1] affect M. tuberculosis (Mtb) in two general ways. Some HDTs impair Mtb survival by disrupting macrophage (and/or other myeloid cells) signalling pathways exploited by the pathogen to thrive intracellularly, rendering the bacteria more sensitive to host defences/antibiotics. Other HDTs boost the host-mediated bacterial clearance, disrupting the equilibrium that the bacteria have established with the host to avoid elimination. Potentially synergising with traditional antimicrobial drugs, HDTs hold great potential to be exploited as adjunctive therapies in TB.
The ERA4TB consortium [2] is at the forefront of HDTs development efforts, promoting the implementation of novel experimental models and a translational framework aimed at identifying and evaluating potential candidate molecules from their discovery up to early clinical development. Indeed, pharmacokinetic-pharmacodynamic relationships and model-informed drug development concepts hold a pivotal role in providing the pharmacological rationale for the progression of these compounds. As such, in this work, we have implemented a modelling strategy to characterise the concentration-effect relationship of HDTs in preliminary in vitro studies, repurposing ferrostatin-1 (Fe–1) [3], a potent ferroptosis inhibitor believed to promote host cells survival in TB, as a case study.
Methods:
In vitro time-kill assays of Mtb H37Rv were available for this analysis. The time course of bacterial growth and killing was studied, both in absence of host cells (i.e., extracellular conditions) and inside infected THP-1 cells [4] (i.e., intracellular conditions) over a period of 10 days. The following experimental settings were tested: no treatment – extracellular conditions, Fe-1 treatment – extracellular conditions, no treatment – intracellular conditions, Fe-1 treatment – intracellular conditions. In total, 13 concentration levels were tested for Fe-1, starting from 800 μM and proceeding with log2 dilutions.
The overall pharmacokinetic-pharmacodynamic (PKPD) data analysis strategy aimed to quantify bactericidal/bacteriostatic effects from extracellular settings and, assuming additivity of effects, to provide an unbiased estimation of augmented bacterial clearance due to a putative host-directed effect in intracellular conditions. This analysis comprised three stages: (1) development of a model of intracellular/extracellular natural bacterial growth, (2) parameterisation of ‘bactericidal’ effects of Fe-1 from extracellular conditions and (3) parameterisation of ‘host-directed’ effects of Fe-1 from intracellular-treated conditions. Regarding the natural bacterial growth, different models were tested (e.g. Gompertz’s and Velhurst’s). Both bactericidal and host-directed effects of Fe-1 were investigated with linear, sigmoidal EMAX or generalised EMAX models.
Model selection was based on goodness-of-fit plots, changes in the objective function value (OFV), and the biological plausibility of estimates and their precision. Parameter estimation was conducted using NONMEM 7.5 and PsN 5.2.6. Graphical analyses were performed in R version 4.1.2.
Results:
The Gompertz growth model was found to be the most suitable model to parameterise the natural growth of Mtb in both conditions (intra/extracellular growth rate (CV%) = 0.267 (2.6%) / 0.888(6.9 %) day-1). The effect of Fe-1 in extracellular conditions was best described by a bactericidal EMAX function with a fixed slope parameter (EMAX= 1.06 (0.2%) day-1; EC50=190 (4.8%) μM). Fixing parameters from natural growth and bactericidal effect models, an EMAX model, with a sigmoidal time onset (empirically parameterising penetration into cells and possible time dependent effects) was found to best describe the available intracellular data (EMAX= 2.45 (3.4%) day-1; EC50=2.74 (6.6%) μM; Slope=0.757(4%), T50=3.28 (2.5%) days)
Conclusions:
The proposed stepwise approach allows one to disentangle the bactericidal activity of a compound from host-directed effects in a pragmatic, yet semi-mechanistic fashion. Notably, this framework will facilitate the screening and ranking of promising HDTs. Moreover, the availability of PKPD estimates also provide the basis for further selection of suitable dosing regimens in in vivo animal models, ultimately paving the way to patients.
References:
[1] T. R. Hawn, J. A. Shah, and D. Kalman, “New tricks for old dogs: Countering antibiotic resistance in tuberculosis with host-directed therapeutics,” Immunol Rev, vol. 264, no. 1, pp. 344–362, Mar. 2015, doi: 10.1111/imr.12255.
[2] “The ERA4TB consortium” https://era4tb.org/.
[3] O. Zilka et al., “On the Mechanism of Cytoprotection by Ferrostatin-1 and Liproxstatin-1 and the Role of Lipid Peroxidation in Ferroptotic Cell Death,” ACS Cent Sci, vol. 3, no. 3, pp. 232–243, Mar. 2017, doi: 10.1021/acscentsci.7b00028.
[4] W. Chanput, J. J. Mes, and H. J. Wichers, “THP-1 cell line: An in vitro cell model for immune modulation approach,” International Immunopharmacology, vol. 23, no. 1. Elsevier, pp. 37–45, 2014. doi: 10.1016/j.intimp.2014.08.002.
Reference: PAGE 32 (2024) Abstr 11229 [www.page-meeting.org/?abstract=11229]
Poster: Drug/Disease Modelling - Other Topics