Application of Transmural Flow Across In Vitro Microvasculature Enables Direct Sampling of Interstitial Therapeutic Molecule Distribution
Name
Offeddu Small 2019_final1.pdf
Description
Accepted version
Size
1.55 MB
Format
Adobe PDF
Checksum (MD5)
1852c776bd1a28f4064474f60030b9fa
Author(s)
Offeddu, Giovanni
Possenti, Luca
Loessberg‐Zahl, Joshua T
Zunino, Paolo
Roberts, John
Han, Xiaogang
Hickman, Dean
Knutson, Charles G
Kamm, Roger Dale
Date Issued
September 2019
Journal
Small
Publisher
Wiley
Citation
Offeddu, Giovanni et al. "Application of Transmural Flow Across In Vitro Microvasculature Enables Direct Sampling of Interstitial Therapeutic Molecule Distribution." Small 15, 46 (November 2019): 1902393 © 2019 Wiley
Version
Author's final manuscript
Abstract
In vitro prediction of physiologically relevant transport of therapeutic molecules across the microcirculation represents an intriguing opportunity to predict efficacy in human populations. On-chip microvascular networks (MVNs) show physiologically relevant values of molecular permeability, yet like most systems, they lack an important contribution to transport: the ever-present fluid convection through the endothelium. Quantification of transport through the MVNs by current methods also requires confocal imaging and advanced analytical techniques, which can be a bottleneck in industry and academic laboratories. Here, it is shown that by recapitulating physiological transmural flow across the MVNs, the concentration of small and large molecule therapeutics can be directly sampled in the interstitial fluid and analyzed using standard analytical techniques. The magnitudes of transport measured in MVNs reveal trends with molecular size and type (protein versus nonprotein) that are expected in vivo, supporting the use of the MVNs platform as an in vitro tool to predict distribution of therapeutics in vivo.
MIT Department
Massachusetts Institute of Technology. Department of Biological Engineering
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1002/SMLL.201902393
