Model-based translation of antibiotic effects from novel in vitro models to patients
The overall aim of my PhD project is to establish a framework that can be applied to predict treatment strategies of antibiotics in a clinical setting from novel experimental systems that recapitulate in vivo-like conditions and consider bacterial physiology within patients, based on pharmacokinetics/pharmacodynamics (PKPD) approaches.
A variety of experimental settings that better mimic physiologically relevant conditions in vitro have been developed by collaborators, ranging from simple monolayer cell models to complex tissue and organ-on-a-chip models systems emulating conditions in the human body at different levels of complexity and physiological relevance. These new models are expected to mimic bacteria-host interaction better than the conventional time-kill systems.
This work combines the development of mathematic models using non-linear mixed effects modeling approach, i.e. the software NONMEM for estimation of model parameters, as well as various R-packages to perform predictions and simulations. Different structural models, and models that describe variability within and between experiments, will be explored to fit available data. A simulation and estimation procedure will be applied to optimize experimental designs.
This project is also part of the NCCR Antiresist consortium (NCCR AntiResist | A New Paradigm in Antibiotic Discovery | Switzerland).
PhD Student Grigory Nesvijevski working on his project
Related published research
- Abdul-Aziz, Mohd H., Jan-Willem C. Alffenaar, Matteo Bassetti, Hendrik Bracht, George Dimopoulos, Deborah Marriott, Michael N. Neely, et al. ‘Antimicrobial Therapeutic Drug Monitoring in Critically Ill Adult Patients: A Position Paper#’. Intensive Care Medicine 46, no. 6 (1 June 2020): 1127–53. https://doi.org/10.1007/s00134-020-06050-1
- Friberg, Lena E. ‘Pivotal Role of Translation in Anti-Infective Development’. Clinical Pharmacology & Therapeutics 109, no. 4 (2021): 856–66. https://doi.org/10.1002/cpt.2182
- Sollier, Julie, Marek Basler, Petr Broz, Petra S. Dittrich, Knut Drescher, Adrian Egli, Alexander Harms, et al. ‘Revitalizing Antibiotic Discovery and Development through in Vitro Modelling of In-Patient Conditions’. Nature Microbiology 9, no. 1 (4 January 2024): 1–3. https://doi.org/10.1038/s41564-023-01566-w
- Swart, A. Leoni, Benoît-Joseph Laventie, Rosmarie Sütterlin, Tina Junne, Luisa Lauer, Pablo Manfredi, Sandro Jakonia, et al. ‘Pseudomonas Aeruginosa Breaches Respiratory Epithelia through Goblet Cell Invasion in a Microtissue Model’. Nature Microbiology 9, no. 7 (10 June 2024): 1725–37. https://doi.org/10.1038/s41564-024-01718-6
- Minichmayr, Iris K., Vincent Aranzana-Climent, and Lena E. Friberg. ‘Pharmacokinetic/Pharmacodynamic Models for Time Courses of Antibiotic Effects’. International Journal of Antimicrobial Agents 60, no. 3 (September 2022): 106616. https://doi.org/10.1016/j.ijantimicag.2022.106616
- Drwiega, Emily N., and Keith A. Rodvold. ‘Penetration of Antibacterial Agents into Pulmonary Epithelial Lining Fluid: An Update’. Clinical Pharmacokinetics 61, no. 1 (January 2022): 17–46. https://doi.org/10.1007/s40262-021-01061-7