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Frontiers in Bioengineering and BiotechnologyBioengineeringPeer-reviewed journal article

In vitro design of intrathecal drug administration therapies

Ayankola O. AyansijiiD, Caleb Gardner, Sebastien Dors, Daniel S. Gehrke, Francisco Moral-PulidoiD, Konstantin V. SlaviniD, Andreas A. LinningeriD

PDFDOIPreprint

Abstract

1Due to the scarcity of reliable in vivo data, the pharmacokinetics of intrathecally (IT) administered drugs remain inadequately quantified. Designing new therapies is further hindered by variability in experimental methods, inter-individual and inter-species differences, and poor reproducibility across animal and human studies. To address these limitations, we developed an anatomically accurate, subject-specific replica of the cerebrospinal fluid-filled spaces of the human central nervous system (CNS) using a multistep mold/casting process. The 3D-printed, transparent, deformable CNS phantom enables precise control of infusion and physiological parameters, allowing systematic generation of reliable and repeatable biodispersion data for lumbar IT infusion protocols. Pulsatile artificial cerebrospinal fluid (CSF) flow within the closed system was tuned to replicate subject-specific stroke volumes and flow rates observed in MRI. The models optical clarity facilitated high-speed visualization and tracking of tracer dispersion, exceeding the temporal resolution of current neuroimaging techniques. Experimental series spanning physiologically relevant CSF and infusion conditions enabled quantification of the spatiotemporal distribution of IT-administered tracers. Inversion of the parabolic diffusion equation provided estimates of the coefficient of effective dispersion. A distributed pharmacokinetic model was used to evaluate the influence of chemical kinetics and mass transfer on tracer behavior. The proposed experimental apparatus for in vitro design of IT therapies offers a complementary or alternative approach to traditional trial-and-error animal studies.

Citations
2
FWCI
5.02
Field percentile
top 8%

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