THE IMPACT OF ARTIFICIAL INTELLIGENCE ON DRUG DISCOV-ERY FOR NEUROPSYCHIATRIC DISORDERS

被引:0
作者
Sundaram, Vickram Agaram [1 ]
Saravanan, Bharath [1 ]
Balamurugan, Bhavani Sowndharya [1 ]
Marimuthu, Mathan Muthu Chinnakannu [1 ]
Munjal, Kavita [2 ]
Chopra, Hitesh [3 ]
机构
[1] SIMATS, Saveetha Sch Engn, Dept Biotechnol, Chennai 602105, India
[2] Amity Univ, Amity Inst Pharm, Noida, Uttar Pradesh, India
[3] Chitkara Univ, Chitkara Coll Pharm, Ctr Res Impact & Outcome, Rajpura 140401, Punjab, India
来源
EXCLI JOURNAL | 2025年 / 24卷
关键词
Artificial Intelligence; machine learning; neuropsychiatric disorders; blood-brain barrier; AI-driven drug development; DESIGN;
D O I
10.17179/excli2025-8378
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Artificial intelligence (AI) and machine learning (ML) are transforming medication discovery, particularly in neuropsychiatric illnesses, where traditional drug research presents major obstacles. This paper looks at how artificial intelligence might help advance neuropsychiatric medication development, with an emphasis on early-stage research, drug design, and clinical diagnostics. This review discusses AI's contribution to understanding the blood-brain barrier and its link with the central nervous system, which is an important aspect of medication efficacy in neuropsychiatric treatments. AI-facilitated de novo drug design, using predictive algorithms and deep learning models, speeds up the discovery of new medicinal molecules. AI is employed in brain imaging and diagnosis, boosting the accuracy with which neuropsychiatric diseases are identified. BBB permeability prediction is one of the most important uses of AI in drug discovery, as it improves the selection of CNS-active drugs. Additionally, AI is transforming treatment techniques for neurodevelopmental disorders and assisting in the discovery of novel antidepressant medications through data-driven methodologies. Despite these accomplishments, AI-driven drug discovery still has several constraints, such as data biases, regulatory barriers, and ethical issues. Overcoming these restrictions will be critical to unlocking AI's full potential in neuropsychiatric research. This paper concludes with several future possibilities and opportunities, such as incorporating AI into personalized medicine using sophisticated neural network models and multimodal data fusion techniques. This might increase treatment choices for certain conditions by fine-tuning AI approaches. This paper presents a perspective on AI as a highly transformative instrument for influencing neuropsychiatric drug development, as well as an emerging field that has the potential to impact the modern idea of pharmacology.
引用
收藏
页码:728 / 748
页数:21
相关论文
共 80 条
[1]   The performance of artificial intelligence-driven technologies in diagnosing mental disorders: an umbrella review [J].
Abd-alrazaq, Alaa ;
Alhuwail, Dari ;
Schneider, Jens ;
Toro, Carla T. ;
Ahmed, Arfan ;
Alzubaidi, Mahmood ;
Alajlani, Mohannad ;
Househ, Mowafa .
NPJ DIGITAL MEDICINE, 2022, 5 (01)
[2]   Clinical Pharmacology in Drug Development for Rare Diseases in Neurology: Contributions and Opportunities [J].
Abuasal, Bilal ;
Ahmed, Mariam A. ;
Patel, Priyank ;
Albusaysi, Salwa ;
Sabarinath, Sreedharan ;
Uppoor, Ramana ;
Mehta, Mehul .
CLINICAL PHARMACOLOGY & THERAPEUTICS, 2022, 111 (04) :786-798
[3]   A Review of the Role of Artificial Intelligence in Healthcare [J].
Al Kuwaiti, Ahmed ;
Nazer, Khalid ;
Al-Reedy, Abdullah ;
Al-Shehri, Shaher ;
Al-Muhanna, Afnan ;
Subbarayalu, Arun Vijay ;
Al Muhanna, Dhoha ;
Al-Muhanna, Fahad A. .
JOURNAL OF PERSONALIZED MEDICINE, 2023, 13 (06)
[4]   Knowledge-based approaches to drug discovery for rare diseases [J].
Alves, Vinicius M. ;
Korn, Daniel ;
Pervitsky, Vera ;
Thieme, Andrew ;
Capuzzi, Stephen J. ;
Baker, Nancy ;
Chirkova, Rada ;
Ekins, Sean ;
Muratov, Eugene N. ;
Hickey, Anthony ;
Tropsha, Alexander .
DRUG DISCOVERY TODAY, 2022, 27 (02) :490-502
[5]   New Drug Design Avenues Targeting Alzheimer's Disease by Pharmacoinformatics-Aided Tools [J].
Arrue, Lily ;
Cigna-Mendez, Alexandra ;
Barbosa, Tabata ;
Borrego-Munoz, Paola ;
Struve-Villalobos, Silvia ;
Oviedo, Victoria ;
Martinez-Garcia, Claudia ;
Sepulveda-Lara, Alexis ;
Millan, Natalia ;
Marquez Montesinos, Jose C. E. ;
Munoz, Juana ;
Santana, Paula A. ;
Pena-Varas, Carlos ;
Barreto, George E. ;
Gonzalez, Janneth ;
Ramirez, David .
PHARMACEUTICS, 2022, 14 (09)
[6]   Artificial Intelligence Applied to clinical trials: opportunities and challenges [J].
Askin, Scott ;
Burkhalter, Denis ;
Calado, Gilda ;
El Dakrouni, Samar .
HEALTH AND TECHNOLOGY, 2023, 13 (02) :203-213
[7]   Contribution of Human Pluripotent Stem Cell-Based Models to Drug Discovery for Neurological Disorders [J].
Benchoua, Alexandra ;
Lasbareilles, Marie ;
Tournois, Johana .
CELLS, 2021, 10 (12)
[8]  
Bhatt P, 2024, Curr. Artif. Intell., V2, DOI [10.2174/0129503752250813231124092946, DOI 10.2174/0129503752250813231124092946]
[9]  
Brady LS, 2023, EXPERT OPIN DRUG DIS, V18, P835, DOI [10.1080/17460441.2023.2224555, 10.1017/9781009275811]
[10]   Towards Transforming Neurorehabilitation: The Impact of Artificial Intelligence on Diagnosis and Treatment of Neurological Disorders [J].
Calderone, Andrea ;
Latella, Desiree ;
Bonanno, Mirjam ;
Quartarone, Angelo ;
Mojdehdehbaher, Sepehr ;
Celesti, Antonio ;
Calabro, Rocco Salvatore .
BIOMEDICINES, 2024, 12 (10)