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Current Pharmaceutical Design

Editor-in-Chief

ISSN (Print): 1381-6128
ISSN (Online): 1873-4286

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Editorial

Artificial Intelligence Technologies used for the Assessment of Pharmaceutical Excipients

Author(s): Ashutosh Kumar, Ghanshyam Das Gupta and Sarjana Raikwar*

Volume 30, Issue 6, 2024

Published on: 29 January, 2024

Page: [407 - 409] Pages: 3

DOI: 10.2174/0113816128285827240119095013

Price: $65

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[1]
Chaudhari SP, Patil PS. Pharmaceutical excipients: A review. Int J Adv Pharm Biol Chem 2012; 1: 21-34.
[2]
Patel P, Ahir K, Patel V, Manani L, Patel C. Drug-excipient compatibility studies: First step for dosage form development. Pharma Innov 2015; 4: 14.
[3]
Yang W, Wu D. Microcalorimetry in pharmaceutical development. Encyclopedia of Pharmaceutical Science and Technology CRC Press. 2013; Six : p: p. 2149-56.
[4]
Vora LK, Gholap AD, Jetha K, Thakur RRS, Solanki HK, Chavda VP. Artificial intelligence in pharmaceutical technology and drug delivery design. Pharmaceutics 2023; 15(7): 1916.
[http://dx.doi.org/10.3390/pharmaceutics15071916] [PMID: 37514102]
[5]
Hariry RE,, Barenji RV,, Azizi A. Toward Pharma 4.0 in drug discovery Industry 40: Technologies, Applications, and Challenges Springer. 2022; pp. 221-38.
[6]
Bouhouita-Guermech S, Gogognon P, Bélisle-Pipon J-C. Specific challenges posed by artificial intelligence in research ethics Front. Artif Intell 2023; 6.
[http://dx.doi.org/10.3389/frai.2023.1149082]
[7]
Khalid GM, Usman AG. Application of data-intelligence algorithms for modeling the compaction performance of new pharmaceutical excipients. Future J Pharm Sci 2021; 7(1): 31.
[http://dx.doi.org/10.1186/s43094-021-00183-w]
[8]
Chen C, Yaari Z, Apfelbaum E, Grodzinski P, Shamay Y, Heller DA. Merging data curation and machine learning to improve nanomedicines. Adv Drug Deliv Rev 2022; 183: 114172.
[http://dx.doi.org/10.1016/j.addr.2022.114172] [PMID: 35189266]
[9]
Shah HS, Chaturvedi K, Kuang S, Wang J. Accelerating pre-formulation investigations in early drug product life cycles using predictive methodologies and computational algorithms. Ther Deliv 2021; 12(11): 789-97.
[http://dx.doi.org/10.4155/tde-2021-0043] [PMID: 34792419]
[10]
Tesfay D, Abrha S, Yilma Z, Woldu G, Molla F. Preparation, optimization, and evaluation of epichlorohydrin cross-linked enset (Ensete ventricosum (Welw.) Cheeseman) starch as drug release sustaining excipient in microsphere formulation. Biomed Res Int 2020; 2020.
[11]
Cadden J, Gupta KM, Kanaujia P, Coles SJ, Aitipamula S. Cocrystal formulations: Evaluation of the impact of excipients on dissolution by molecular simulation and experimental approaches. Cryst Growth Des 2021; 21(2): 1006-18.
[http://dx.doi.org/10.1021/acs.cgd.0c01351]
[12]
Ziatdinov M, Ghosh A, Wong CY, Kalinin SV. AtomAI framework for deep learning analysis of image and spectroscopy data in electron and scanning probe microscopy. Nat Mach Intell 2022; 4(12): 1101-12.
[http://dx.doi.org/10.1038/s42256-022-00555-8]
[13]
Sultana A, Maseera R, Rahamanulla A, Misiriya A. Emerging of artificial intelligence and technology in pharmaceuticals: Review. Future J Pharm Sci 2023; 9(1): 65.
[http://dx.doi.org/10.1186/s43094-023-00517-w]
[14]
Wang N, Sun H, Dong J, Ouyang D, Pharm DE, Pharm DE. A new expert system for drug-excipient compatibility evaluation. Int J Pharm 2021; 607: 120962.
[http://dx.doi.org/10.1016/j.ijpharm.2021.120962] [PMID: 34339812]
[15]
Chun Matthew. How artificial intelligence is revolutionizing drug discovery. Artificial Intelligence, Biotechnology Avaialble from: https://blog.petrieflom.law.harvard.edu/2023/03/20/how-artificial-intelligence-is-revolutionizing-drug-discovery/

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