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

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Abstract

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.

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Funding

This work was partially supported by grants from the National Institutes of Health (U01 HL143403, R01 CA254110, R61 HL159948 and P30 CA023168) and National Science Foundation (MCB-2134603) to BH and the Scientific and Technological Research Council of Turkey (TÜBİTAK 2232 118C200) to AO.

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  1. Ali Aykut Akalın and Barış Dedekargınoğlu contributed equally to the manuscript.

Authors and Affiliations

  1. Department of Mechanical Engineering, Middle East Technical University, 06531, Ankara, Turkey

    Ali Aykut Akalın, Barış Dedekargınoğlu & Altug Ozcelikkale

  2. School of Mechanical Engineering, Purdue University, 585 Purdue Mall, West Lafayette, Indiana, 47907, USA

    Sae Rome Choi & Bumsoo Han

  3. Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana, USA

    Bumsoo Han

  4. Center for Cancer Research, Purdue University, 585 Purdue Mall, West Lafayette, Indiana, 47907, USA

    Bumsoo Han

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  1. Ali Aykut Akalın
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AO and BH conceptualized the work. AAA, DDK and SRC performed the literature survey and drafted the manuscript. All authors made critical revisions and approved the version being submitted for review.

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Akalın, A.A., Dedekargınoğlu, B., Choi, S.R. et al. Predictive Design and Analysis of Drug Transport by Multiscale Computational Models Under Uncertainty. Pharm Res 40, 501–523 (2023). https://doi.org/10.1007/s11095-022-03298-8

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