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    Rights statement: This document is the Accepted Manuscript version of a Published Work that appeared in final form in ACS Omega, copyright © American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see https://pubs.acs.org/doi/10.1021/acsomega.9b03487

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Prediction of Drug Loading in the Gelatin Matrix Using Computational Methods

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Prediction of Drug Loading in the Gelatin Matrix Using Computational Methods. / Hathout, R.M.; Metwally, A.A.; Woodman, T.J.; Hardy, J.G.

In: ACS Omega, Vol. 5, No. 3, 28.01.2020, p. 1549-1556.

Research output: Contribution to journalJournal articlepeer-review

Harvard

Hathout, RM, Metwally, AA, Woodman, TJ & Hardy, JG 2020, 'Prediction of Drug Loading in the Gelatin Matrix Using Computational Methods', ACS Omega, vol. 5, no. 3, pp. 1549-1556. https://doi.org/10.1021/acsomega.9b03487

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Author

Hathout, R.M. ; Metwally, A.A. ; Woodman, T.J. ; Hardy, J.G. / Prediction of Drug Loading in the Gelatin Matrix Using Computational Methods. In: ACS Omega. 2020 ; Vol. 5, No. 3. pp. 1549-1556.

Bibtex

@article{e10e271635f7427a8e260f2f6e292609,
title = "Prediction of Drug Loading in the Gelatin Matrix Using Computational Methods",
abstract = "The delivery of drugs is a topic of intense research activity in both academia and industry with potential for positive economic, health, and societal impacts. The selection of the appropriate formulation (carrier and drug) with optimal delivery is a challenge investigated by researchers in academia and industry, in which millions of dollars are invested annually. Experiments involving different carriers and determination of their capacity for drug loading are very time-consuming and therefore expensive; consequently, approaches that employ computational/theoretical chemistry to speed have the potential to make hugely beneficial economic, environmental, and health impacts through savings in costs associated with chemicals (and their safe disposal) and time. Here, we report the use of computational tools (data mining of the available literature, principal component analysis, hierarchical clustering analysis, partial least squares regression, autocovariance calculations, molecular dynamics simulations, and molecular docking) to successfully predict drug loading into model drug delivery systems (gelatin nanospheres). We believe that this methodology has the potential to lead to significant change in drug formulation studies across the world.",
author = "R.M. Hathout and A.A. Metwally and T.J. Woodman and J.G. Hardy",
note = "This document is the Accepted Manuscript version of a Published Work that appeared in final form in ACS Omega, copyright {\textcopyright} American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see https://pubs.acs.org/doi/10.1021/acsomega.9b03487",
year = "2020",
month = jan,
day = "28",
doi = "10.1021/acsomega.9b03487",
language = "English",
volume = "5",
pages = "1549--1556",
journal = "ACS Omega",
issn = "2470-1343",
publisher = "American Chemical Society",
number = "3",

}

RIS

TY - JOUR

T1 - Prediction of Drug Loading in the Gelatin Matrix Using Computational Methods

AU - Hathout, R.M.

AU - Metwally, A.A.

AU - Woodman, T.J.

AU - Hardy, J.G.

N1 - This document is the Accepted Manuscript version of a Published Work that appeared in final form in ACS Omega, copyright © American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see https://pubs.acs.org/doi/10.1021/acsomega.9b03487

PY - 2020/1/28

Y1 - 2020/1/28

N2 - The delivery of drugs is a topic of intense research activity in both academia and industry with potential for positive economic, health, and societal impacts. The selection of the appropriate formulation (carrier and drug) with optimal delivery is a challenge investigated by researchers in academia and industry, in which millions of dollars are invested annually. Experiments involving different carriers and determination of their capacity for drug loading are very time-consuming and therefore expensive; consequently, approaches that employ computational/theoretical chemistry to speed have the potential to make hugely beneficial economic, environmental, and health impacts through savings in costs associated with chemicals (and their safe disposal) and time. Here, we report the use of computational tools (data mining of the available literature, principal component analysis, hierarchical clustering analysis, partial least squares regression, autocovariance calculations, molecular dynamics simulations, and molecular docking) to successfully predict drug loading into model drug delivery systems (gelatin nanospheres). We believe that this methodology has the potential to lead to significant change in drug formulation studies across the world.

AB - The delivery of drugs is a topic of intense research activity in both academia and industry with potential for positive economic, health, and societal impacts. The selection of the appropriate formulation (carrier and drug) with optimal delivery is a challenge investigated by researchers in academia and industry, in which millions of dollars are invested annually. Experiments involving different carriers and determination of their capacity for drug loading are very time-consuming and therefore expensive; consequently, approaches that employ computational/theoretical chemistry to speed have the potential to make hugely beneficial economic, environmental, and health impacts through savings in costs associated with chemicals (and their safe disposal) and time. Here, we report the use of computational tools (data mining of the available literature, principal component analysis, hierarchical clustering analysis, partial least squares regression, autocovariance calculations, molecular dynamics simulations, and molecular docking) to successfully predict drug loading into model drug delivery systems (gelatin nanospheres). We believe that this methodology has the potential to lead to significant change in drug formulation studies across the world.

U2 - 10.1021/acsomega.9b03487

DO - 10.1021/acsomega.9b03487

M3 - Journal article

C2 - 32010828

VL - 5

SP - 1549

EP - 1556

JO - ACS Omega

JF - ACS Omega

SN - 2470-1343

IS - 3

ER -