Predictive Design and Analysis of Drug Transport by MultiScale Computational Models Under Uncertainty

Date

2022-01-01

Author

Akalın, Ali Aykut
Dedekargınoğlu, Barış
Choi, Sae Rome
Han, Bumsoo
Özçelikkale, Altuğ

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© 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.Computational modeling of drug delivery is becoming an indispensable tool for advancing drug development pipeline, particularly in nanomedicine where a rational design strategy is ultimately sought. While numerous in silico models have been developed that can accurately describe nanoparticle interactions with the bioenvironment within prescribed length and time scales, predictive design of these drug carriers, dosages and treatment schemes will require advanced models that can simulate transport processes across multiple length and time scales from genomic to population levels. In order to address this problem, multiscale modeling efforts that integrate existing discrete and continuum modeling strategies have recently emerged. These multiscale approaches provide a promising direction for bottom-up in silico pipelines of drug design for delivery. However, there are remaining challenges in terms of model parametrization and validation in the presence of variability, introduced by multiple levels of heterogeneities in disease state. Parametrization based on physiologically relevant in vitro data from microphysiological systems as well as widespread adoption of uncertainty quantification and sensitivity analysis will help address these challenges.

Subject Keywords

continuum modeling, discrete modeling, nanomedicine, sensitivity analysis, SMEARED FINITE-ELEMENT, PHARMACOKINETIC MODEL, MICROVESSEL DENSITY, MOLECULAR-DYNAMICS, MASS-TRANSPORT, BLOOD-VESSELS, FE MODEL, TUMOR, SIMULATION, DELIVERY, continuum modeling, discrete modeling, nanomedicine, sensitivity analysis

URI

https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85131305765&origin=inward
https://hdl.handle.net/11511/99169

Journal

Pharmaceutical Research

DOI

https://doi.org/10.1007/s11095-022-03298-8

Collections

Department of Mechanical Engineering, Article

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Citation Formats

A. A. Akalın, B. Dedekargınoğlu, S. R. Choi, B. Han, and A. Özçelikkale, “Predictive Design and Analysis of Drug Transport by MultiScale Computational Models Under Uncertainty,” Pharmaceutical Research, pp. 0–0, 2022, Accessed: 00, 2022. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85131305765&origin=inward.