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Updated: Jul 18, 2025

Design and Use of a Low Cost, Automated Morbidostat for Adaptive Evolution of Bacteria Under Antibiotic Drug Selection
Published on: September 27, 2016
A 3D-printed multi-compartment device that enables dynamic PK/PD profiles of antibiotics
Andrew A Heller1,2, Morgan K Geiger2, Dana M Spence3,4,5
1Department of Chemistry, Michigan State University, East Lansing, MI, 48824, USA.
Abstract:
Pathogens develop resistance to various drugs while under the selective pressure of antibiotics resulting in the emergence of bacterial strains that are resistant to multiple treatment options. Unfortunately, the resistance to antibiotics has also been accompanied by a reduction in the development of novel antibiotics to combat various pathogens. Current diagnostic tools, which are used in parts of the early developmental process of antibiotics, primarily consist of static susceptibility tests that do not resemble the pharmacokinetics of the therapy in vivo. Here, we designed and 3D-printed cubical inserts with membranes on two of the cube faces that allow diffusion of a molecule across two planes. These inserts are used with a 3D-printed device to create a two-compartment model to mimic the pharmacokinetics of a molecule in humans from multiple types of administration. Fluorescein was used to characterize the device and the diffusion of molecules from a flowing channel, through a membrane in the first plane (representing the primary compartment in vivo, or plasma), followed by measurement in the second compartment (that represents the interstitial fluid). The dynamic, two-compartment model was tested using both gram-positive and gram-negative bacterial strains in the secondary compartment. The ATP/OD600 (a measure of antibiotic activity) of a kanamycin-resistant E. coli strain challenged with the antibiotic levofloxacin increased after reaching an effective concentration of the antibiotic at 2 h, equating to a secondary compartment concentration of 3.5 ± 1.3 µM levofloxacin. The ATP/OD600 of a chloramphenicol-resistant B. subtilis strain challenged with the antibiotic levofloxacin remained steady or increased slightly after reaching an effective concentration of the antibiotic. The earliest statistical difference was detected 3 h after the start of the PK curve, which corresponds with a secondary compartment concentration of 4.8 ± 1.8 µM levofloxacin. Our results demonstrate that a fabricated 2-compartment model (1) provides realistic PK values to those published from in vivo studies and (2) can be used to determine antibiotic pharmacodynamics.
Insights
Researchers developed a 3D-printed two-compartment model to better simulate antibiotic pharmacokinetics (PK) in vivo. This dynamic model accurately predicts antibiotic activity against resistant bacteria, improving drug development.
Area of Science:
- Biomedical Engineering
- Pharmacology
- Microbiology
Background:
- Antibiotic resistance is a growing threat, exacerbated by a lack of novel drug development.
- Current antibiotic susceptibility tests lack in vivo pharmacokinetic relevance.
- Static susceptibility tests do not accurately reflect how drugs behave in the body.
Purpose of the Study:
- To design and validate a novel 3D-printed two-compartment model for simulating in vivo pharmacokinetics.
- To assess the model's utility in evaluating antibiotic activity against resistant bacterial strains.
- To provide a more realistic platform for early-stage antibiotic development.
Main Methods:
- Fabrication of a 3D-printed device with cubical inserts featuring membranes for molecular diffusion.
- Characterization of the model using fluorescein to mimic drug diffusion from plasma to interstitial fluid.
- Testing the dynamic model with gram-positive and gram-negative bacteria in the secondary compartment, measuring antibiotic activity (ATP/OD600).
Main Results:
- The 3D-printed model generated pharmacokinetic (PK) values comparable to published in vivo data.
- The model successfully demonstrated antibiotic activity against resistant strains of E. coli and B. subtilis.
- Statistically significant differences in antibiotic activity were detected as early as 3 hours, correlating with specific drug concentrations.
Conclusions:
- The fabricated two-compartment model accurately mimics human pharmacokinetics.
- This dynamic model is effective for determining antibiotic pharmacodynamics.
- The platform offers a valuable tool for advancing antibiotic research and development.
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