Advanced Artificial Intelligence Technologies Transforming Contemporary Pharmaceutical Research
One area of study within machine learning and artificial intelligence (AI) seeks to create computer programs with intelligence that can mimic human focal processes in order to produce results. This technique includes data collection, effective data usage system development, conclusion illustration,...
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MDPI AG
2025-03-01
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| Series: | Bioengineering |
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| author | Parveen Kumar Benu Chaudhary Preeti Arya Rupali Chauhan Sushma Devi Punit B. Parejiya Madan Mohan Gupta |
| author_facet | Parveen Kumar Benu Chaudhary Preeti Arya Rupali Chauhan Sushma Devi Punit B. Parejiya Madan Mohan Gupta |
| author_sort | Parveen Kumar |
| collection | DOAJ |
| description | One area of study within machine learning and artificial intelligence (AI) seeks to create computer programs with intelligence that can mimic human focal processes in order to produce results. This technique includes data collection, effective data usage system development, conclusion illustration, and arrangements. Analysis algorithms that are learning to mimic human cognitive activities are the most widespread application of AI. Artificial intelligence (AI) studies have proliferated, and the field is quickly beginning to understand its potential impact on medical services and investigation. This review delves deeper into the pros and cons of AI across the healthcare and pharmaceutical research industries. Research and review articles published throughout the last few years were selected from PubMed, Google Scholar, and Science Direct, using search terms like ‘artificial intelligence’, ‘drug discovery’, ‘pharmacy research’, ‘clinical trial’, etc. This article provides a comprehensive overview of how artificial intelligence (AI) is being used to diagnose diseases, treat patients digitally, find new drugs, and predict when outbreaks or pandemics may occur. In artificial intelligence, neural networks and deep learning are some of the most popular tools; in clinical research, Bayesian non-parametric approaches hold promise for better results, while smartphones and the processing of natural languages are employed in recognizing patients and trial monitoring. Seasonal flu, Ebola, Zika, COVID-19, tuberculosis, and outbreak predictions were made using deep computation and artificial intelligence. The academic world is hopeful that AI development will lead to more efficient and less expensive medical and pharmaceutical investigations and better public services. |
| format | Article |
| id | doaj-art-17a8755f348545d1bd9b42f00dec1e0a |
| institution | OA Journals |
| issn | 2306-5354 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
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| series | Bioengineering |
| spelling | doaj-art-17a8755f348545d1bd9b42f00dec1e0a2025-08-20T02:17:20ZengMDPI AGBioengineering2306-53542025-03-0112436310.3390/bioengineering12040363Advanced Artificial Intelligence Technologies Transforming Contemporary Pharmaceutical ResearchParveen Kumar0Benu Chaudhary1Preeti Arya2Rupali Chauhan3Sushma Devi4Punit B. Parejiya5Madan Mohan Gupta6Department of Pharmaceutics, NIMS Institute of Pharmacy, NIMS University, Jaipur 303121, Rajasthan, IndiaShri Ram College of Pharmacy, Karnal 132001, Haryana, IndiaShri Ram College of Pharmacy, Karnal 132001, Haryana, IndiaChitkara College of Pharmacy, Chitkara University, Rajpura 140401, Punjab, IndiaChitkara College of Pharmacy, Chitkara University, Rajpura 140401, Punjab, IndiaDepartment of Pharmaceutics, K.B. Institute of Pharmaceutical Education and Research, Kadi Sarva Vishwavidyalaya, Gandhinagar 382 023, Gujarat, IndiaDepartment of Pharmaceutics, NIMS Institute of Pharmacy, NIMS University, Jaipur 303121, Rajasthan, IndiaOne area of study within machine learning and artificial intelligence (AI) seeks to create computer programs with intelligence that can mimic human focal processes in order to produce results. This technique includes data collection, effective data usage system development, conclusion illustration, and arrangements. Analysis algorithms that are learning to mimic human cognitive activities are the most widespread application of AI. Artificial intelligence (AI) studies have proliferated, and the field is quickly beginning to understand its potential impact on medical services and investigation. This review delves deeper into the pros and cons of AI across the healthcare and pharmaceutical research industries. Research and review articles published throughout the last few years were selected from PubMed, Google Scholar, and Science Direct, using search terms like ‘artificial intelligence’, ‘drug discovery’, ‘pharmacy research’, ‘clinical trial’, etc. This article provides a comprehensive overview of how artificial intelligence (AI) is being used to diagnose diseases, treat patients digitally, find new drugs, and predict when outbreaks or pandemics may occur. In artificial intelligence, neural networks and deep learning are some of the most popular tools; in clinical research, Bayesian non-parametric approaches hold promise for better results, while smartphones and the processing of natural languages are employed in recognizing patients and trial monitoring. Seasonal flu, Ebola, Zika, COVID-19, tuberculosis, and outbreak predictions were made using deep computation and artificial intelligence. The academic world is hopeful that AI development will lead to more efficient and less expensive medical and pharmaceutical investigations and better public services.https://www.mdpi.com/2306-5354/12/4/363artificial intelligencecomputational learninghealthcaredrug discoverypersonalized medicinepatient |
| spellingShingle | Parveen Kumar Benu Chaudhary Preeti Arya Rupali Chauhan Sushma Devi Punit B. Parejiya Madan Mohan Gupta Advanced Artificial Intelligence Technologies Transforming Contemporary Pharmaceutical Research Bioengineering artificial intelligence computational learning healthcare drug discovery personalized medicine patient |
| title | Advanced Artificial Intelligence Technologies Transforming Contemporary Pharmaceutical Research |
| title_full | Advanced Artificial Intelligence Technologies Transforming Contemporary Pharmaceutical Research |
| title_fullStr | Advanced Artificial Intelligence Technologies Transforming Contemporary Pharmaceutical Research |
| title_full_unstemmed | Advanced Artificial Intelligence Technologies Transforming Contemporary Pharmaceutical Research |
| title_short | Advanced Artificial Intelligence Technologies Transforming Contemporary Pharmaceutical Research |
| title_sort | advanced artificial intelligence technologies transforming contemporary pharmaceutical research |
| topic | artificial intelligence computational learning healthcare drug discovery personalized medicine patient |
| url | https://www.mdpi.com/2306-5354/12/4/363 |
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