Unlocking therapeutic frontiers: harnessing artificial intelligence in drug discovery for neurodegenerative diseases

被引：0
作者：
Nehmeh, Bilal [1 ]
Rebehmed, Joseph [2 ]
Nehmeh, Riham [3 ]
Taleb, Robin [4 ]
Akoury, Elias [1 ]
机构：
[1] Lebanese Amer Univ, Dept Phys Sci, Beirut 11022801, Lebanon
[2] Lebanese Amer Univ, Dept Comp Sci & Math, Beirut 11022801, Lebanon
[3] INSA Rennes, Inst Elect & Telecommun Rennes IETR, UMR 6164, F-35708 Rennes, France
[4] Lebanese Amer Univ, Dept Phys Sci, Byblos Campus,4M8F 6QF, Blat, Lebanon
来源：
DRUG DISCOVERY TODAY | 2024年 / 29卷 / 12期
关键词：
neurodegenerative diseases; artificial intelligence; drug discovery; machine learning; pathological hallmarks; INTERACTION PREDICTION; TYROSINE KINASE; NEURAL-NETWORKS; CHEMOTHERAPY; GENERATION; INHIBITOR; MOLECULE; MODELS; PEMBROLIZUMAB; ROSUVASTATIN;
D O I：
10.1016/j.drudis.2024.104216
中图分类号：
R9 [药学];
学科分类号：
1007 ;
摘要：
Neurodegenerative diseases (NDs) pose serious healthcare challenges with limited therapeutic treatments and high social burdens. The integration of artificial intelligence (AI) into drug discovery has emerged as a promising approach to address these challenges. This review explores the application of AI techniques to unravel therapeutic frontiers for NDs. We examine the current landscape of AI-driven drug discovery and discuss the potentials of AI in accelerating the identification of novel therapeutic targets on ND research and drug development, optimization of drug candidates, and expediating personalized medicine approaches. Finally, we outline future directions and challenges in harnessing AI for the advancement of therapeutics in this critical area by emphasizing the importance of interdisciplinary collaboration and ethical considerations.
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页数：16
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共 157 条
  • [11] Answer ALS, a large-scale resource for sporadic and familial ALS combining clinical and multi-omics data from induced pluripotent cell lines
    Baxi, Emily G.
    Thompson, Terri
    Li, Jonathan
    Kaye, Julia A.
    Lim, Ryan G.
    Wu, Jie
    Ramamoorthy, Divya
    Lima, Leandro
    Vaibhav, Vineet
    Matlock, Andrea
    Frank, Aaron
    Coyne, Alyssa N.
    Landin, Barry
    Ornelas, Loren
    Mosmiller, Elizabeth
    Thrower, Sara
    Farr, S. Michelle
    Panther, Lindsey
    Gomez, Emilda
    Galvez, Erick
    Perez, Daniel
    Meepe, Imara
    Lei, Susan
    Mandefro, Berhan
    Trost, Hannah
    Pinedo, Louis
    Banuelos, Maria G.
    Liu, Chunyan
    Moran, Ruby
    Garcia, Veronica
    Workman, Michael
    Ho, Richie
    Wyman, Stacia
    Roggenbuck, Jennifer
    Harms, Matthew B.
    Stocksdale, Jennifer
    Miramontes, Ricardo
    Wang, Keona
    Venkatraman, Vidya
    Holewenski, Ronald
    Sundararaman, Niveda
    Pandey, Rakhi
    Manalo, Danica-Mae
    Donde, Aneesh
    Huynh, Nhan
    Adam, Miriam
    Wassie, Brook T.
    Vertudes, Edward
    Amirani, Naufa
    Raja, Krishna
    [J]. NATURE NEUROSCIENCE, 2022, 25 (02) : 226 - +
  • [12] BenevolentAI, 2021, BenevolentAI and AstraZeneca achieve collaboration milestone with novel AI-generated chronic kidney disease target
  • [13] LEREC - A NN/HMM HYBRID FOR ONLINE HANDWRITING RECOGNITION
    BENGIO, Y
    LECUN, Y
    NOHL, C
    BURGES, C
    [J]. NEURAL COMPUTATION, 1995, 7 (06) : 1289 - 1303
  • [14] COMO: a pipeline for multi-omics data integration in metabolic modeling and drug discovery
    Bessell, Brandt
    Loecker, Josh
    Zhao, Zhongyuan
    Aghamiri, Sara Sadat
    Mohanty, Sabyasachi
    Amin, Rada
    Helikar, Tomas
    Puniya, Bhanwar Lal
    [J]. BRIEFINGS IN BIOINFORMATICS, 2023, 24 (06)
  • [15] The Emerging Landscape of Natural Small-molecule Therapeutics for Huntington's Disease
    Bhat, Shahnawaz Ali
    Ahamad, Shakir
    Dar, Nawab John
    Siddique, Yasir Hassan
    Nazir, Aamir
    [J]. CURRENT NEUROPHARMACOLOGY, 2023, 21 (04) : 867 - 889
  • [16] Borok L S, 1997, J Health Care Finance, V23, P20
  • [17] ACEGEN: Reinforcement Learning of Generative Chemical Agents for Drug Discovery
    Bou, Albert
    Thomas, Morgan
    Dittert, Sebastian
    Navarro, Carles
    Majewski, Maciej
    Wang, Ye
    Patel, Shivam
    Tresadern, Gary
    Ahmad, Mazen
    Moens, Vincent
    Sherman, Woody
    Sciabola, Simone
    De Fabritiis, Gianni
    [J]. JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2024, 64 (15) : 5900 - 5911
  • [18] Breiman Leo, 2001, Machine Learning, V45
  • [19] El Escorial revisited: Revised criteria for the diagnosis of amyotrophic lateral sclerosis
    Brooks, BR
    Miller, RG
    Swash, M
    Munsat, TL
    [J]. AMYOTROPHIC LATERAL SCLEROSIS AND OTHER MOTOR NEURON DISORDERS, 2000, 1 (05): : 293 - 299
  • [20] Contemporary QSAR classifiers compared
    Bruce, Craig L.
    Melville, James L.
    Pickett, Stephen D.
    Hirst, Jonathan D.
    [J]. JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2007, 47 (01) : 219 - 227
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