New Era’s of Artificial Intelligence in Pharmaceutical Industries
DOI:
https://doi.org/10.22270/ajprd.v12i2.1362Abstract
Artificial Intelligence (AI) is the future of pharmaceutical industries. We make our tasks easier with help of Artificial Intelligence in future. With help of Artificial Intelligence we can also increase in production in pharmaceutical industry, can be save of dangerous and risky works in the production or manufacturing. Artificial Intelligence can drugs designing in future and discover new drugs and determine the chemical structure of drugs. Artificial Intelligence is very important role play in clinical research. For the pharmacological action drugs are works with the target protein. Than this target proteins are show the pharmacological action and Artificial Intelligence is help in determination of target protein and Artificial Intelligence can easier the drug discovery related work. Artificial Intelligence will used in the marketing such as the patient or customer related information or data collection and deposition. Creation of essential and specialized advertisement for increase product Sell. Different type application will in pharmaceutical industry of Artificial intelligence. And AI will change the pharmaceutical industry or drug associated work and that is come new revolution in pharmacy. Many types AI robots are invented in various pharmacy fields for the help of human being in manufacturing or production in pharmaceutical industry. Artificial Intelligence will advantages and disadvantage for the human beings. This review aims that drug delivery nanosystems design, characterization, and production stand to benefit greatly from artificial intelligence (AI). Furthermore, the ability to perform reverse engineering and ongoing system optimisation is becoming possible with the help of big data.
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Chen, Wei, Xuesong Liu, Sanyin Zhang, and Shilin Chen. "Artificial intelligence for drug discovery: Resources, methods, and applications." Molecular Therapy-Nucleic Acids 31 (2023): 691-702.
Yu, J., Wang, D. and Zheng, M., Uncertainty quantification: Can we trust Artificial Intelligence in drug discovery?. Iscience. . 2022 Aug 19;25(8).
Qayyum A, Qadir J, Bilal M, Al-Fuqaha A. Secure and robust machine learning for healthcare: A survey. IEEE Reviews in Biomedical Engineering. 2020 Jul 31;14:156-80.
Sarkar C, Das B, Rawat VS, Wahlang JB, Nongpiur A, Tiewsoh I, Lyngdoh NM, Das D, Bidarolli M, Sony HT. Artificial intelligence and machine learning technology driven modern drug discovery and development. International Journal of Molecular Sciences. 2023 Jan 19;24(3):2026.
Sharma T, Mankoo A, Sood V. Artificial intelligence in advanced pharmacy. International Journal of Science and Research Archive. 2021;2(1):047-54.
Thomas S, Abraham A, Baldwin J, Piplani S, Petrovsky N. Artificial intelligence in vaccine and drug design. Vaccine Design: Methods and Protocols, Volume 1. Vaccines for Human Diseases. 2022:131-46.
Deng J, Yang Z, Ojima I, Samaras D, Wang F. Artificial intelligence in drug discovery: applications and techniques. Briefings in Bioinformatics. 2022 Jan;23(1):bbab430.
Siddique S, Chow JC. Machine learning in healthcare communication. Encyclopedia. 2021 Feb 14;1(1):220-39.
Jiménez-Luna J, Grisoni F, Weskamp N, Schneider G. Artificial intelligence in drug discovery: recent advances and future perspectives. Expert opinion on drug discovery. 2021 Sep 2;16(9):949-59.
Pallathadka H, Mustafa M, Sanchez DT, Sajja GS, Gour S, Naved M. Impact of machine learning on management, healthcare and agriculture. Materials Today: Proceedings. 2023 Jan 1;80:2803-6.
Del Giorgio Solfa F, Simonato FR. Big data analytics in healthcare: Exploring the role of machine learning in predicting patient outcomes and improving healthcare delivery. International Journal of Computations, Information and Manufacturing (IJCIM). 2023;3.
Cavasotto CN, Di Filippo JI. Artificial intelligence in the early stages of drug discovery. Archives of biochemistry and biophysics. 2021 Feb 15;698:108730.
Ghahramani Z. Probabilistic machine learning and artificial intelligence. Nature. 2015 May 28;521(7553):452-9.
Bhavsar, K.A., Singla, J., Al-Otaibi, Y.D., Song, O.Y., Zikria, Y.B. and Bashir, A.K. Medical diagnosis using machine learning: a statistical review. Computers, Materials and Continua, 2021. 67(1), pp.107-125.
Kononenko I. Machine learning for medical diagnosis: history, state of the art and perspective. Artificial Intelligence in medicine. 2001 Aug 1;23(1):89-109.
Borisa P, Singh D, Rathore KS. Impact of artificial intelligence on pharma industry. Manipal Journal of Pharmaceutical Sciences. 2020;6(1):9.
Selvaraj C, Chandra I, Singh SK. Artificial intelligence and machine learning approaches for drug design: challenges and opportunities for the pharmaceutical industries. Molecular diversity. 2021 Oct 23:1-21.
McCoy LG, Brenna CT, Chen SS, Vold K, Das S. Believing in black boxes: machine learning for healthcare does not need explainability to be evidence-based. Journal of clinical epidemiology. 2022 Feb 1;142:252-7..
Aslan, A., Matschak, T., Greve, M., Trang, S. and Kolbe, L. At What Price? Exploring the Potential and Challenges of Differentially Private Machine Learning for Healthcare. 2023.
Zhavoronkov A, Vanhaelen Q, Oprea TI. Will artificial intelligence for drug discovery impact clinical pharmacology?. Clinical Pharmacology & Therapeutics. 2020 Apr;107(4):780-5.
Rajkomar A, Dean J, Kohane I. Machine learning in medicine. New England Journal of Medicine. 2019 Apr 4;380(14):1347-58.
Balyen L, Peto T. Promising artificial intelligence-machine learning-deep learning algorithms in ophthalmology. The Asia-Pacific Journal of Ophthalmology. 2019 May 1;8(3):264-72.
Patel J, Patel D, Meshram D. Artificial Intelligence in Pharma Industry-A Rising Concept. Journal of Advancement in Pharmacognosy. 2021;1(2).
Ahmad MA, Eckert C, Teredesai A. Interpretable machine learning in healthcare. InProceedings of the 2018 ACM international conference on bioinformatics, computational biology, and health informatics 2018 Aug 15 (pp. 559-560).
Brady, M, Artificial Intelligence and robotics. Artificial intelligence, 1985 26(1), pp.79-121.
Ashrafian H. Artificial intelligence and robot responsibilities: Innovating beyond rights. Science and engineering ethics. 2015 Apr;21:317-26.
Mishra V. Artificial intelligence: the beginning of a new era in pharmacy profession. Asian Journal of Pharmaceutics (AJP). 2018 May 30;12(02).
Ulfa AM, Afandi Saputra Y, Nguyen PT. Role of artificial intelligence in pharma science. Journal of critical reviews. 2019;7(1):2020.
Schneider P, Walters WP, Plowright AT, Sieroka N, Listgarten J, Goodnow Jr RA, Fisher J, Jansen JM, Duca JS, Rush TS, Zentgraf M. Rethinking drug design in the artificial intelligence era. Nature Reviews Drug Discovery. 2020 May;19(5):353-64.
Manikiran SS, Prasanthi NL. Artificial intelligence: milestones and role in pharma and healthcare sector. Pharma times. 2019;51:9-56.
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