TY - JOUR
T1 - Intravital microscopy for real-time monitoring of drug delivery and nanobiological processes
AU - Momoh, Jeffrey
AU - Kapsokalyvas, Dimitrios
AU - Vogt, Michael
AU - Hak, Sjoerd
AU - Kiessling, Fabian
AU - van Zandvoort, Marc
AU - Lammers, Twan
AU - Marios Sofias, Alexandros
N1 - Copyright © 2022. Published by Elsevier B.V.
PY - 2022/10
Y1 - 2022/10
N2 - Intravital microscopy (IVM) expands our understanding of cellular and molecular processes, with applications ranging from fundamental biology to (patho)physiology and immunology, as well as from drug delivery to drug processing and drug efficacy testing. In this review, we highlight modalities, methods and model organisms that make up today's IVM landscape, and we present how IVM - via its high spatiotemporal resolution - enables analysis of metabolites, small molecules, nanoparticles, immune cells, and the (tumor) tissue microenvironment. We furthermore present examples of how IVM facilitates the elucidation of nanomedicine kinetics and targeting mechanisms, as well as of biological processes such as immune cell death, host-pathogen interactions, metabolic states, and disease progression. We conclude by discussing the prospects of IVM clinical translation and examining the integration of machine learning in future IVM practice.
AB - Intravital microscopy (IVM) expands our understanding of cellular and molecular processes, with applications ranging from fundamental biology to (patho)physiology and immunology, as well as from drug delivery to drug processing and drug efficacy testing. In this review, we highlight modalities, methods and model organisms that make up today's IVM landscape, and we present how IVM - via its high spatiotemporal resolution - enables analysis of metabolites, small molecules, nanoparticles, immune cells, and the (tumor) tissue microenvironment. We furthermore present examples of how IVM facilitates the elucidation of nanomedicine kinetics and targeting mechanisms, as well as of biological processes such as immune cell death, host-pathogen interactions, metabolic states, and disease progression. We conclude by discussing the prospects of IVM clinical translation and examining the integration of machine learning in future IVM practice.
U2 - 10.1016/j.addr.2022.114528
DO - 10.1016/j.addr.2022.114528
M3 - (Systematic) Review article
C2 - 36067968
SN - 0169-409X
VL - 189
JO - Advanced Drug Delivery Reviews
JF - Advanced Drug Delivery Reviews
M1 - 114528
ER -