Bart van Lieshout1, Dr. Robin van den Biggelaar2, Prof. dr. Coen van Hasselt1, Dr. Anno Saris2, Dr. Rob van Wijk1
1Leiden Academic Centre for Drug Research (LACDR), Leiden University, 2Leiden University Center for Infectious Diseases (LUCID), Leiden University Medical Centre
Introduction/Objectives Intracellular pathogens, specifically bacteria that evade the immune system and establish persistent infections, remain a therapeutic challenge [1]. Existing antibiotic treatments are often prolonged with limited intracellular effects, underlining the need for innovative approaches. Host-directed therapies (HDT) represent a promising therapeutic strategy that enhances the host’s mechanisms to eradicate pathogens [2]. The development of HDTs is difficult due to intricate host-pathogen-drug interactions, necessitating model-informed drug development (MIDD) for improved decision-making. For the quantification and translation of HDT pharmacodynamics (PD), both a mechanistic description of host-pathogen dynamics and intracellular growth are required, which are currently lacking [3,4]. Therefore, this study aims to (1) develop a mechanistic model for intracellular bacteria dynamics (2) formulate a framework for quantifying HDT effects, and (3) apply the framework to in vitro data as a proof-of-concept. Methods Model structure development and characterization: To describe the required dynamics, an established viral dynamic model that delays pathogen release with a transit structure was used as a foundation [5]. The transit compartments were set to represent intracellular growth through a ratio between the growth rate, host carrying capacity, and number of compartments. Each compartment represented an increasing number of pathogens, to approximate continuous exponential growth with the transit rate constant reflecting the growth rate constant. To characterize and adapt the mechanistic model into a practical modeling framework, different scenarios were simulated in rxode2, and intracellular pathogen counts over time were compared against direct simulations of exponential growth [6]. These evaluated the deviation between intra- and extracellular growth curves across a range of compartment numbers, determining the minimum required number of compartments. Application to HDT and antibiotic therapy: As a proof-of-concept for the quantification of HDT PD, the mechanistic model was applied to an HDT in vitro dataset. Experimental data was acquired by co-culturing HeLa cells with luminescent methicillin-resistant Staphylococcus aureus (USA300 LAC JE2), treated with HDT candidate GW296115X and vancomycin as a mono- or combination therapy in concentrations ranging from 0-10,000 nM [7]. Luminescence was measured every 15 minutes for 16 hours. Population PD modeling was performed using NONMEM 7.5 (ICON, Maryland, USA). Different parameterizations of drug effects, described by Emax or sigmoid Emax models, were evaluated initially with the determined minimum number of compartments, followed by a stepwise evaluation to the optimal number of transit compartments. Models were evaluated based on objective function values, goodness-of-fit (GOF) plots, and visual-predictive checks (VPC). Results The developed mechanistic model successfully approximated exponential growth through the transit compartment structure, with HDT drug effects modeled on each transit compartment to define intracellular HDT efficacy. Concretely, simulated intracellular growth rates were equivalent to exponential extracellular growth rates when using more than 10 compartments, which was determined to be the minimum and initial number for fitting models. For the proof-of-concept, the in vitro data was fitted well by a model with GW296115X as a first-order clearance of infected host cells and vancomycin’s effect parameterized as proportional to extracellular growth. This model utilized 17 transit compartments after stepwise addition, during which estimates, excluding lysis rate, remained within 0.5 log2 fold-change. Parameter estimates included the intra- and extracellular growth rate constants (0.39 /h and 0.50 /h) and PD of GW296115X (Emax: 0.38 /h, EC50: 1.51 µM, and Hill exponent: 1.53) and vancomycin (Emax: 4.16 /h, EC50: 5.62 µM, and Hill exponent: 2.21). Additionally, GOF and VPC plots confirmed the model’s ability to capture the observed host-pathogen-drug dynamics in mono- and combination therapy. Conclusions The developed modeling framework based on a novel mechanistic description of intracellular pathogen dynamics and drug effect thereon serves as an impactful new tool for quantifying HDT PD. It may contribute to the translation of host-pathogen-drug dynamics to (pre-)clinical studies and acceleration of the development of HDTs through MIDD.
[1] Fisher RA, Gollan B, Helaine S. Persistent bacterial infections and persister cells. Nature Reviews Microbiology. 2017 May 22;15(8):453–64. [2] Shapira T, Christofferson M, Yossef Av-Gay. The antimicrobial activity of innate host-directed therapies: A systematic review. International Journal of Antimicrobial Agents. 2024 Mar 13;63(5):107138–8. [3] Villani U, Leding AMA, Velickovic P, D’Agate S, Hoffmann E, Gaundin C, Simonsson USH, Della Pasqua O, Model-based characterisation of host-directed therapeutics against M. tuberculosis in an in vitro experimental model. PAGE 2025 Abstr 11229 [www.page-meeting.org/?abstract=11229] [4] Zhang S, Agyeman AA, Hadjichrysanthou C, Standing JF. SARS-CoV-2 viral dynamic modeling to inform model selection and timing and efficacy of antiviral therapy. CPT: Pharmacometrics & Systems Pharmacology. 2023 Aug 21;12(10):1450–60. [5] Bai F, Huff K, Allen L. The effect of delay in viral production in within-host models during early infection. Journal of Biological Dynamics. 2018 Jul 19;13(sup1):47–73. [6] Wang W, Hallow K, James D. A Tutorial on RxODE: Simulating Differential Equation Pharmacometric Models in R. CPT: pharmacometrics & systems pharmacology. 2015 Dec 19;5(1):3–10. [7] Biggelaar RHGA, Walburg KV, Van den Eeden SJF, Van Doorn CLR, Meiler E, De Ries AS, et al. Identification of kinase modulators as host-directed therapeutics against intracellular methicillin-resistant Staphylococcus aureus. Frontiers in Cellular and Infection Microbiology. 2024 Mar 25;14.
Reference: PAGE 33 (2025) Abstr 11723 [www.page-meeting.org/?abstract=11723]
Poster: Drug/Disease Modelling - Other Topics