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.

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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