Development of fucoidan/polyethyleneimine based sorafenib-loaded self-assembled nanoparticles with machine learning and DoE-ANN implementation: Optimization, characterization, and in-vitro assessment for the anticancer drug delivery.

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Title: Development of fucoidan/polyethyleneimine based sorafenib-loaded self-assembled nanoparticles with machine learning and DoE-ANN implementation: Optimization, characterization, and in-vitro assessment for the anticancer drug delivery.
Authors: Chaurawal N; Department of Pharmacy, School of Chemical Sciences and Pharmacy, Central University of Rajasthan, Bandarsindri, Ajmer, Rajasthan -305817, India., Quadir SS; Department of Pharmaceutical Sciences, Mohanlal Sukhadia University, Udaipur, Rajasthan 313001, India., Joshi G; Department of Pharmaceutical Sciences, Mohanlal Sukhadia University, Udaipur, Rajasthan 313001, India., Barkat MA; Department of Pharmaceutics, College of Pharmacy, University of Hafr Al Batin, 39524, Saudi Arabia., Alanezi AA; Department of Pharmaceutics, College of Pharmacy, University of Hafr Al Batin, 39524, Saudi Arabia., Raza K; Department of Pharmacy, School of Chemical Sciences and Pharmacy, Central University of Rajasthan, Bandarsindri, Ajmer, Rajasthan -305817, India. Electronic address: drkaisar@curaj.ac.in.
Source: International journal of biological macromolecules [Int J Biol Macromol] 2024 Nov; Vol. 279 (Pt 1), pp. 135123. Date of Electronic Publication: 2024 Aug 27.
Publication Type: Journal Article
Journal Info: Publisher: Elsevier Country of Publication: Netherlands NLM ID: 7909578 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-0003 (Electronic) Linking ISSN: 01418130 NLM ISO Abbreviation: Int J Biol Macromol Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: Development of fucoidan/polyethyleneimine based sorafenib-loaded self-assembled nanoparticles with machine learning and DoE-ANN implementation: Optimization, characterization, and in-vitro assessment for the anticancer drug delivery.
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  Data: <searchLink fieldCode="AU" term="%22Chaurawal+N%22">Chaurawal N</searchLink>; Department of Pharmacy, School of Chemical Sciences and Pharmacy, Central University of Rajasthan, Bandarsindri, Ajmer, Rajasthan -305817, India.<br /><searchLink fieldCode="AU" term="%22Quadir+SS%22">Quadir SS</searchLink>; Department of Pharmaceutical Sciences, Mohanlal Sukhadia University, Udaipur, Rajasthan 313001, India.<br /><searchLink fieldCode="AU" term="%22Joshi+G%22">Joshi G</searchLink>; Department of Pharmaceutical Sciences, Mohanlal Sukhadia University, Udaipur, Rajasthan 313001, India.<br /><searchLink fieldCode="AU" term="%22Barkat+MA%22">Barkat MA</searchLink>; Department of Pharmaceutics, College of Pharmacy, University of Hafr Al Batin, 39524, Saudi Arabia.<br /><searchLink fieldCode="AU" term="%22Alanezi+AA%22">Alanezi AA</searchLink>; Department of Pharmaceutics, College of Pharmacy, University of Hafr Al Batin, 39524, Saudi Arabia.<br /><searchLink fieldCode="AU" term="%22Raza+K%22">Raza K</searchLink>; Department of Pharmacy, School of Chemical Sciences and Pharmacy, Central University of Rajasthan, Bandarsindri, Ajmer, Rajasthan -305817, India. Electronic address: drkaisar@curaj.ac.in.
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  Data: <searchLink fieldCode="JN" term="%227909578%22">International journal of biological macromolecules</searchLink> [Int J Biol Macromol] 2024 Nov; Vol. 279 (Pt 1), pp. 135123. <i>Date of Electronic Publication: </i>2024 Aug 27.
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        Value: 10.1016/j.ijbiomac.2024.135123
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      – TitleFull: Development of fucoidan/polyethyleneimine based sorafenib-loaded self-assembled nanoparticles with machine learning and DoE-ANN implementation: Optimization, characterization, and in-vitro assessment for the anticancer drug delivery.
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              Text: 2024 Nov
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